Artificial Intelligence CourseWork 2: Hyperparameter Optimization¶

Introduction¶

The investigation aimes to explore hyperparameter optimization on Wine Quality Dataset. I will follow Chollet's universal workflow of Deep Learning With Python. The overall goal of this project is to develop a program that systematically explores the hyperparameter space to identify the most effective configuration for the model. This involves implementing a search strategy, in this case, random search, to sample different hyperparameter combinations from a predefined space. IWe will assess the model's performance using cross-validation, a robust statistical method that maximizes the use of available data by iteratively splitting the dataset into training and validation subsets. This practice helps in estimating the performance of the model on unseen data, thereby ensuring that our optimization process generalizes well and does not overfit to particular quirks of the training data.

By the end of this investigatiI aimpire to have a model tuned to offer the highest predictive accuracy on the Wine Quality Dataset. This report will detail the steps taken in the universal workflow, the implementation of our hyperparameter optimization program, the results obtained, and a discussion of the outcn ing.

Methodology¶

Step 1: Define the Problem and Assemble a Dataset¶

The Wine Quality dataset typically refers to one of two datasets available in the UCI Machine Learning Repository related to red and white variants of the Portuguese "Vinho Verde" wine. Wine quality is a subjective variable, judged by experts, and scored on a scale from 0 (very bad) to 10 (excellent). The red wine dataset contains 1,597 instance while the white wine dataset contains 4,898 instancs. I will mainly use the red wine dataset for more quicker training.

Each dataset has 11 input features:

  • Fixed acidity,
  • Volatile acidity,
  • Citric acid,
  • Residual sugar,
  • Chlorides,
  • Free sulfur dioxide,
  • Total sulfur dioxide,
  • Density,
  • pH,
  • Sulphates,
  • Alcohol.

The output variable is the quality of the wine, scored on a scale from 0 to 10. Therefore, it can be treated as either a regression problem if we consider the output variable as continuous, or a classification problem for a discrete output.

For the purpose of this project, I converted it into a classification problem where each wine is great(a score of 7 or higher), good(a score between 4 and 6), not good(a score below 4).

In this way, it is transformed into a multi-class classification problem, and my goal is to classify the red wine into the right category. After identifying the problem type, the next step is to determine the choice of model architecture and evaluation metric.

Step 2: Choose a Evaluation Metric¶

For multi-class classfication problems, categorical entropy and accuracy would be the most frequently-used metrics. In this case, given input feature, the model should be able to classified the data into the right category.

Step 3: Decide on a Evaluation Protocol¶

Evaluation Protocol is essential to keep track of the progress as I tune my models. There are three common ways:

  • Hold-out validation set
  • K-fold cross-validation
  • Iterated K-fold validation

I will use both K-fold cross validation and Hold-out validation set as evaluation protocol. The holdout test set will be used to assess the model's final performance after tuning and validating the model through K-fold cross-validation on the training set. Wine Quality dataset is small dataset, where overfitting can be a concern. Cross-validacan be one of the solution to ensure the model generalizes well to unseen data.

For smaller datasets, each fold in K-fold cross-validation contains less data, which means the validation scores might have higher variance. In such cases, K-fold cross-validation is indeed very suitable because it ensures that each observation is used for both training and validation exactly once, making the most out of limited data.

I have an exact quantity of 1597 pieces of data. I am not sure what is the most appropriate number for k, might be 3, 5, or 10. I will conduct experimentations on this to see if there is any differences.

Step 4: Prepare the Data¶

Now I have determined the dataset, the evaluation metrics, the evaluation protocol. It is time to prepare the data and preprocess them.

  • Missing Values

    Missing values in the dataset are being filled with the mean value of their respective columns. This is a common imputation technique to handle misg data.

  • Extract Feature and Target Value

    Input features are being taken from all columns except the last two, and target variable is taken from the second last column of he DataFram. The .to_numpy() method is used to convert the DataFrame slices into numpy arrays.

  • Standardize Input Features

    The input features are being standardIzed using StandardScaler, which removes the mean and scales the data this way. It is an essential preprdocessing step to normalize the data before feeding it to machine learning model.

    The target variable y is being relabelled to three classes: Class 0: for original value between 6 and 9 (inclusive) Class 1: for original value between 4 and 6 (inclusive) Class 2: for all other values

  • One-hot Encode the Target

    The relabeled target variable is one-hot encoded, which is necessary for multi-class classification with neural networks. This creates

matrix representation of the data.

  • Split Data into Training and Test Sets

    The scaled data is split into training and test sets using an 80-20 split. 80% of the data is used for training, and 20% is reserved for testing the model's performance. The random_state parameter ensures reproducibility of the split.

  • Set Up K-Fold Cross-Validation

    A KFold cross-validator is set up to use 3 folds first, as discussed.

In [54]:
import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
from tensorflow.keras.utils import to_categorical
from sklearn.model_selection import train_test_split, KFold

# load the data
df = pd.read_csv('C:/Users/80443/Desktop/Goldsmiths/AI/WineQT.csv')

# fill missing values with the mean
df = df.fillna(df.mean())
X = df.iloc[:, :-2].to_numpy()  #  Input variable
y = df.iloc[:, -2].to_numpy()   # Target variable (the second last column)

scaler = StandardScaler()
X_scaled = scaler.fit_transform(X)
# make it a 3-class classification tasks
y_relabel = np.where((y>=7) & (y<=9), 0,
            np.where((y>=4) & (y<=6), 1, 2)) 
y_encoded = to_categorical(y_relabel, num_classes=3)

# split train set and test set
X_train, X_test, y_train, y_test = train_test_split(X_scaled, y_encoded, test_size=0.2, random_state=42)
# use cross validation to split the train and validation set, k = 3
n_splits=5
cross_validator = KFold(n_splits=n_splits, shuffle=True, random_state=42)

Step 5: Build a Basic Model¶

I will build a neural network between features and the target. Key hyperparameters for tuning included the architecture of the neural network (number of layers and units), learning rate, optimizer type, and regularization parameters. Random search was chosen to efficiently navigate the hyperparameter space with a predefined range for each parameter. And in later experiment, I will try to include more hyperparameters.

In [61]:
from tensorflow.keras import models, layers, regularizers
from tensorflow.keras.optimizers import Adam, RMSprop, SGD
from sklearn.metrics import accuracy_score
import matplotlib.pyplot as plt


def create_model(hidden_units, hidden_layers, optimizer, dropout_rate, l1, l2, learning_rate, adam_beta_1=None, adam_beta_2=None, momentum=None, learning_rate_decay=None, rho=None):
    model = models.Sequential()
    model.add(layers.Dense(hidden_units, activation='relu', input_shape=(11,), kernel_regularizer=regularizers.l1_l2(l1=l1, l2=l2)))
    model.add(layers.Dropout(dropout_rate))
    model.add(layers.Dense(3, activation='softmax'))
    
    if optimizer == 'Adam':
        if adam_beta_1 is not None and adam_beta_2 is not None:
            optimizer = Adam(learning_rate=learning_rate, beta_1=adam_beta_1, beta_2=adam_beta_2)
    elif optimizer == 'RMSprop':
        optimizer = RMSprop(learning_rate=learning_rate, rho=rho)
    elif optimizer == 'momentum':
        optimizer = SGD(learning_rate=learning_rate, momentum=momentum)
    else:
        raise ValueError("Unknown optimizer")
    # I am not sure how to handle the parameter of different optimizers. I asked GPT4 about it, GPT4 paid version, accessed on Jan 25th.
        
    model.compile(loss='categorical_crossentropy', optimizer=optimizer, metrics=['accuracy'])
    return model

# from lab code
def plot_loss(history):
    loss = history.history['loss']
    val_loss = history.history['val_loss']

    epochs = range(1, len(loss) + 1)

    blue_dots = 'bo'
    solid_blue_line = 'b'

    plt.plot(epochs, loss, blue_dots, label = 'Training loss')
    plt.plot(epochs, val_loss, solid_blue_line, label = 'Validation loss')
    plt.title('Training and validation loss')
    plt.xlabel('Epochs')
    plt.ylabel('Loss')
    plt.legend()
    plt.show()

# from lab code
def plot_accuracy(history):
    acc = history.history['accuracy']
    val_acc = history.history['val_accuracy']
    
    epochs = range(1, len(acc) + 1)
    
    plt.plot(epochs, acc, 'bo', label = 'Training acc')
    plt.plot(epochs, val_acc, 'b', label = 'Validation acc')
    plt.title('Training and validation acc')
    plt.xlabel('Epochs')
    plt.ylabel('Accuracy')
    plt.legend()
    plt.show()

Experiment 1: Kfold = 5, basic hyperparameters¶

  • Learning Rate: 0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001

  • Hidden Layers: 1, 2, 3, 4, 5

  • Hidden Units: 8, 16, 32, 64, 128, 256

  • Batch Size: 128, 256, 512

  • Optimizers: SGD, RMSprop, Adam

  • Dropout Rates: 0.2, 0.3, 0.4

Dropout is a regularization technique that randomly sets a fraction of input units to 0 at each update during training time, which helps prevent overfitting. The rates 0.2, 0.3, 0.4 here mean that 20%, 30%, or 40% of the nodes will be turned off.

  • L1 Regularization: 0.001, 0.01, 0.1

These are regularization techniques that constrain the weights of the network during training. L1 regularization adds an L1 penalty equal to the absolute value of the magnitude of coefficients, which can lead to sparse models with some weights pushed to zero.

  • L2 Regularization: 0.001, 0.01, 0.1

L2 regularization adds an L2 penalty equal to the square of the magnitude of coefficients, which tends to spread error among terms but doesn't make weights exactly zero. Values 0.001, 0.01, 0.1 provide a range of regularization strengths to prevent overfitting.

  • Momentum (for SGD): 0.8, 0.9, 0.99, 0.999

Momentum is a term added to the parameter updates that can help accelerate SGD in the correct direction. The options 0.8, 0.9, 0.99, 0.999 offer different levels of momentum.

  • Learning Rate Decay: lr/100 for lr in learning_rate

This is a technique to reduce the learning rate over time. Starting with a larger learning rate can help the model converge quickly, and decreasing it can help the model fine-tune its weights. Nearer the end of training, the more precise the learning rate decay should be tune.

  • Rho (for RMSprop): 0.8, 0.9, 0.99

Rho is a hyperparameter of the RMSprop optimizer that controls the decay rate of the moving average of the squared gradients. It's similar to the momentum term but applied to the gradient squared.

  • Beta Values (for Adam): adam_beta_1 = 0.9, 0.95, adam_beta_2 = 0.999, 0.9995

These hyperparameters control the decay rates of the moving averages of the past gradients (beta_1) and the past squared gradients (beta_2) in the Adam optimizer.

In [62]:
learning_rate = [
    10 ** -i for i in range(1, 6)
]
hidden_layers = [
    1, 2, 3, 4, 5,
]
hidden_units = [
    8, 16, 32, 64, 128, 256,
]
batch_size = [
    128, 256, 512,
]
optimizer = [
    'momentum', 'RMSprop', 'Adam',
]
dropout_rate = [0.2, 0.3, 0.4,]

l1=[0.001, 0.01, 0.1,]
l2=[0.001, 0.01, 0.1,]

momentum = [
    0.8, 0.9, 0.99, 0.999,
]
learning_rate_decay = [lr/100 for lr in learning_rate]

rho = [0.8, 0.9, 0.99]

adam_beta_1 = [0.9, 0.95]
adam_beta_2 = [0.999, 0.9995]

param_space = {
    'learning_rate': learning_rate,
    'hidden_layers': hidden_layers,
    'hidden_units': hidden_units,
    'batch_size': batch_size,
    'learning_rate_decay': learning_rate_decay,
    'optimizer': optimizer,
    'l1': l1,
    'l2': l2,
    'dropout_rate': dropout_rate,
    'momentum': momentum if 'momentum' in optimizer else [None],
    'adam_beta_1': adam_beta_1 if 'Adam' in optimizer else [None],
    'adam_beta_2': adam_beta_2 if 'Adam' in optimizer else [None],
    'rho': rho if 'RMSprop' in optimizer else [None],
}
In [64]:
n_iter = 10
best_score = 0
best_params = {}

for i in range(n_iter):
    print(f"Experiment number: {i+1}")
    sampled_params = {k: np.random.choice(list(v)) for k,v in param_space.items()} # use random search
    model_params = {k:v for k, v in sampled_params.items() if k != 'batch_size'}
    if model_params['optimizer'] != 'momentum':
        model_params['momentum'] = None
    if model_params['optimizer'] != 'Adam':
        model_params['adam_beta_1'] = None
        model_params['adam_beta_2'] = None
    if model_params['optimizer'] != 'RMSprop':
        model_params['rho'] = None

    cv_scores = []
    for train_index, val_index in cross_validator.split(X_train): # I am confused about the data splits here, asked GPT4, accessed on Jan 27th
        X_current_train, X_val = X_train[train_index], X_train[val_index]
        y_current_train, y_val = y_train[train_index], y_train[val_index]
        model = create_model(**model_params)
        print("Model parameters:", model_params)
        print("Batch size:", sampled_params['batch_size'])
        print("X_current_train shape:", X_current_train.shape)
        print("y_current_train shape:", y_current_train.shape)
        history = model.fit(
            X_current_train, y_current_train, 
            epochs=100, 
            batch_size=sampled_params['batch_size'],
            verbose=1,
            validation_data=(X_val, y_val)
        )
        plot_loss(history)
        plot_accuracy(history)
        y_val_pred = model.predict(X_val) # the evaluation and scoring part, I am not sure which libraries to use. Asked GPT4, accessed on Jan 27th
        y_val_pred_classes = np.argmax(y_val_pred, axis=1)
        y_true_classes = np.argmax(y_val, axis=1)
        
        scoring = accuracy_score(y_true_classes, y_val_pred_classes)
        cv_scores.append(scoring)
    mean_cv_scores = np.mean(cv_scores)
        
    if mean_cv_scores > best_score:
        best_score = mean_cv_scores
        if sampled_params['optimizer'] == 'momentum':
            sampled_params['adam_beta_1'] = None
            sampled_params['adam_beta_2'] = None
            sampled_params['rho'] = None
        if sampled_params['optimizer'] == 'RMSprop':
            sampled_params['adam_beta_1'] = None
            sampled_params['adam_beta_2'] = None
            sampled_params['momentum'] = None
        if sampled_params['optimizer'] == 'Adam':
            sampled_params['momentum'] = None
            sampled_params['rho'] = None
        best_params = {k: v for k, v in sampled_params.items() if v is not None}
               
print("Best score:", best_score)
print("Best parameters:", best_params)
print(f"Best model is in {i+1} experiment")

Experiment number: 1
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 219ms/step - loss: 4.0740 - accuracy: 0.2517 - val_loss: 3.4577 - val_accuracy: 0.5246
Epoch 2/100
2/2 [==============================] - 0s 48ms/step - loss: 3.4385 - accuracy: 0.5185 - val_loss: 3.1201 - val_accuracy: 0.7760
Epoch 3/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1000 - accuracy: 0.6676 - val_loss: 2.8832 - val_accuracy: 0.8087
Epoch 4/100
2/2 [==============================] - 0s 50ms/step - loss: 2.8410 - accuracy: 0.7825 - val_loss: 2.7010 - val_accuracy: 0.8087
Epoch 5/100
2/2 [==============================] - 0s 50ms/step - loss: 2.6837 - accuracy: 0.7893 - val_loss: 2.5504 - val_accuracy: 0.8142
Epoch 6/100
2/2 [==============================] - 0s 49ms/step - loss: 2.5370 - accuracy: 0.8358 - val_loss: 2.4197 - val_accuracy: 0.8142
Epoch 7/100
2/2 [==============================] - 0s 42ms/step - loss: 2.3991 - accuracy: 0.8276 - val_loss: 2.3052 - val_accuracy: 0.8142
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 2.2876 - accuracy: 0.8536 - val_loss: 2.2059 - val_accuracy: 0.8142
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1972 - accuracy: 0.8482 - val_loss: 2.1159 - val_accuracy: 0.8142
Epoch 10/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0882 - accuracy: 0.8495 - val_loss: 2.0329 - val_accuracy: 0.8142
Epoch 11/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0099 - accuracy: 0.8536 - val_loss: 1.9560 - val_accuracy: 0.8142
Epoch 12/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9272 - accuracy: 0.8605 - val_loss: 1.8859 - val_accuracy: 0.8142
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8549 - accuracy: 0.8618 - val_loss: 1.8210 - val_accuracy: 0.8142
Epoch 14/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7979 - accuracy: 0.8605 - val_loss: 1.7594 - val_accuracy: 0.8142
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7289 - accuracy: 0.8659 - val_loss: 1.7036 - val_accuracy: 0.8142
Epoch 16/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6742 - accuracy: 0.8550 - val_loss: 1.6498 - val_accuracy: 0.8142
Epoch 17/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6220 - accuracy: 0.8632 - val_loss: 1.6005 - val_accuracy: 0.8142
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5679 - accuracy: 0.8646 - val_loss: 1.5538 - val_accuracy: 0.8142
Epoch 19/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5272 - accuracy: 0.8550 - val_loss: 1.5090 - val_accuracy: 0.8142
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4708 - accuracy: 0.8577 - val_loss: 1.4653 - val_accuracy: 0.8142
Epoch 21/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4287 - accuracy: 0.8577 - val_loss: 1.4255 - val_accuracy: 0.8142
Epoch 22/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3897 - accuracy: 0.8564 - val_loss: 1.3863 - val_accuracy: 0.8142
Epoch 23/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3612 - accuracy: 0.8550 - val_loss: 1.3485 - val_accuracy: 0.8142
Epoch 24/100
2/2 [==============================] - 0s 74ms/step - loss: 1.3167 - accuracy: 0.8605 - val_loss: 1.3140 - val_accuracy: 0.8142
Epoch 25/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2851 - accuracy: 0.8577 - val_loss: 1.2800 - val_accuracy: 0.8142
Epoch 26/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2416 - accuracy: 0.8659 - val_loss: 1.2478 - val_accuracy: 0.8142
Epoch 27/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2108 - accuracy: 0.8605 - val_loss: 1.2167 - val_accuracy: 0.8142
Epoch 28/100
2/2 [==============================] - 0s 52ms/step - loss: 1.1903 - accuracy: 0.8564 - val_loss: 1.1865 - val_accuracy: 0.8142
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1545 - accuracy: 0.8577 - val_loss: 1.1582 - val_accuracy: 0.8142
Epoch 30/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1264 - accuracy: 0.8605 - val_loss: 1.1320 - val_accuracy: 0.8142
Epoch 31/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1001 - accuracy: 0.8618 - val_loss: 1.1045 - val_accuracy: 0.8142
Epoch 32/100
2/2 [==============================] - 0s 45ms/step - loss: 1.0663 - accuracy: 0.8591 - val_loss: 1.0801 - val_accuracy: 0.8142
Epoch 33/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0491 - accuracy: 0.8618 - val_loss: 1.0551 - val_accuracy: 0.8142
Epoch 34/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0167 - accuracy: 0.8591 - val_loss: 1.0328 - val_accuracy: 0.8142
Epoch 35/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9924 - accuracy: 0.8577 - val_loss: 1.0102 - val_accuracy: 0.8142
Epoch 36/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9664 - accuracy: 0.8646 - val_loss: 0.9888 - val_accuracy: 0.8142
Epoch 37/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9555 - accuracy: 0.8591 - val_loss: 0.9668 - val_accuracy: 0.8142
Epoch 38/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9293 - accuracy: 0.8591 - val_loss: 0.9458 - val_accuracy: 0.8142
Epoch 39/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9074 - accuracy: 0.8591 - val_loss: 0.9254 - val_accuracy: 0.8142
Epoch 40/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8915 - accuracy: 0.8591 - val_loss: 0.9070 - val_accuracy: 0.8142
Epoch 41/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8631 - accuracy: 0.8550 - val_loss: 0.8881 - val_accuracy: 0.8142
Epoch 42/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8471 - accuracy: 0.8591 - val_loss: 0.8689 - val_accuracy: 0.8142
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8387 - accuracy: 0.8605 - val_loss: 0.8535 - val_accuracy: 0.8142
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8207 - accuracy: 0.8577 - val_loss: 0.8369 - val_accuracy: 0.8142
Epoch 45/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8017 - accuracy: 0.8591 - val_loss: 0.8206 - val_accuracy: 0.8142
Epoch 46/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7798 - accuracy: 0.8618 - val_loss: 0.8049 - val_accuracy: 0.8142
Epoch 47/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7752 - accuracy: 0.8564 - val_loss: 0.7904 - val_accuracy: 0.8142
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7473 - accuracy: 0.8577 - val_loss: 0.7759 - val_accuracy: 0.8142
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7409 - accuracy: 0.8605 - val_loss: 0.7613 - val_accuracy: 0.8142
Epoch 50/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7219 - accuracy: 0.8591 - val_loss: 0.7486 - val_accuracy: 0.8142
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7088 - accuracy: 0.8632 - val_loss: 0.7349 - val_accuracy: 0.8142
Epoch 52/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7001 - accuracy: 0.8605 - val_loss: 0.7226 - val_accuracy: 0.8142
Epoch 53/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6802 - accuracy: 0.8605 - val_loss: 0.7116 - val_accuracy: 0.8142
Epoch 54/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6654 - accuracy: 0.8618 - val_loss: 0.6992 - val_accuracy: 0.8142
Epoch 55/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6674 - accuracy: 0.8605 - val_loss: 0.6882 - val_accuracy: 0.8142
Epoch 56/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6545 - accuracy: 0.8605 - val_loss: 0.6765 - val_accuracy: 0.8142
Epoch 57/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6345 - accuracy: 0.8605 - val_loss: 0.6674 - val_accuracy: 0.8142
Epoch 58/100
2/2 [==============================] - 0s 42ms/step - loss: 0.6343 - accuracy: 0.8605 - val_loss: 0.6579 - val_accuracy: 0.8142
Epoch 59/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6270 - accuracy: 0.8577 - val_loss: 0.6474 - val_accuracy: 0.8142
Epoch 60/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6117 - accuracy: 0.8618 - val_loss: 0.6384 - val_accuracy: 0.8142
Epoch 61/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5985 - accuracy: 0.8618 - val_loss: 0.6291 - val_accuracy: 0.8142
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5958 - accuracy: 0.8591 - val_loss: 0.6205 - val_accuracy: 0.8142
Epoch 63/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5834 - accuracy: 0.8646 - val_loss: 0.6111 - val_accuracy: 0.8142
Epoch 64/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5832 - accuracy: 0.8618 - val_loss: 0.6031 - val_accuracy: 0.8142
Epoch 65/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5700 - accuracy: 0.8605 - val_loss: 0.5953 - val_accuracy: 0.8142
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5545 - accuracy: 0.8591 - val_loss: 0.5872 - val_accuracy: 0.8142
Epoch 67/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5592 - accuracy: 0.8618 - val_loss: 0.5799 - val_accuracy: 0.8142
Epoch 68/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5384 - accuracy: 0.8605 - val_loss: 0.5731 - val_accuracy: 0.8142
Epoch 69/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5358 - accuracy: 0.8605 - val_loss: 0.5670 - val_accuracy: 0.8142
Epoch 70/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5362 - accuracy: 0.8577 - val_loss: 0.5610 - val_accuracy: 0.8142
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5247 - accuracy: 0.8605 - val_loss: 0.5551 - val_accuracy: 0.8142
Epoch 72/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5205 - accuracy: 0.8605 - val_loss: 0.5498 - val_accuracy: 0.8142
Epoch 73/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5054 - accuracy: 0.8591 - val_loss: 0.5437 - val_accuracy: 0.8142
Epoch 74/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5094 - accuracy: 0.8632 - val_loss: 0.5374 - val_accuracy: 0.8142
Epoch 75/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4953 - accuracy: 0.8618 - val_loss: 0.5309 - val_accuracy: 0.8142
Epoch 76/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5015 - accuracy: 0.8632 - val_loss: 0.5266 - val_accuracy: 0.8142
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4959 - accuracy: 0.8605 - val_loss: 0.5223 - val_accuracy: 0.8142
Epoch 78/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4868 - accuracy: 0.8632 - val_loss: 0.5175 - val_accuracy: 0.8142
Epoch 79/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4804 - accuracy: 0.8632 - val_loss: 0.5130 - val_accuracy: 0.8142
Epoch 80/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4771 - accuracy: 0.8632 - val_loss: 0.5090 - val_accuracy: 0.8142
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4651 - accuracy: 0.8659 - val_loss: 0.5037 - val_accuracy: 0.8142
Epoch 82/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4669 - accuracy: 0.8618 - val_loss: 0.4997 - val_accuracy: 0.8142
Epoch 83/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4678 - accuracy: 0.8646 - val_loss: 0.4948 - val_accuracy: 0.8142
Epoch 84/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4581 - accuracy: 0.8659 - val_loss: 0.4931 - val_accuracy: 0.8142
Epoch 85/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4586 - accuracy: 0.8632 - val_loss: 0.4888 - val_accuracy: 0.8142
Epoch 86/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4510 - accuracy: 0.8646 - val_loss: 0.4861 - val_accuracy: 0.8142
Epoch 87/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4491 - accuracy: 0.8618 - val_loss: 0.4843 - val_accuracy: 0.8142
Epoch 88/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4496 - accuracy: 0.8632 - val_loss: 0.4809 - val_accuracy: 0.8142
Epoch 89/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4350 - accuracy: 0.8618 - val_loss: 0.4788 - val_accuracy: 0.8142
Epoch 90/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4374 - accuracy: 0.8632 - val_loss: 0.4750 - val_accuracy: 0.8142
Epoch 91/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4414 - accuracy: 0.8632 - val_loss: 0.4717 - val_accuracy: 0.8142
Epoch 92/100
2/2 [==============================] - 0s 44ms/step - loss: 0.4330 - accuracy: 0.8673 - val_loss: 0.4697 - val_accuracy: 0.8142
Epoch 93/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4302 - accuracy: 0.8646 - val_loss: 0.4678 - val_accuracy: 0.8142
Epoch 94/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4324 - accuracy: 0.8605 - val_loss: 0.4641 - val_accuracy: 0.8142
Epoch 95/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4278 - accuracy: 0.8618 - val_loss: 0.4615 - val_accuracy: 0.8142
Epoch 96/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4240 - accuracy: 0.8632 - val_loss: 0.4594 - val_accuracy: 0.8142
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4235 - accuracy: 0.8618 - val_loss: 0.4565 - val_accuracy: 0.8142
Epoch 98/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4142 - accuracy: 0.8646 - val_loss: 0.4564 - val_accuracy: 0.8142
Epoch 99/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4179 - accuracy: 0.8659 - val_loss: 0.4549 - val_accuracy: 0.8142
Epoch 100/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4188 - accuracy: 0.8618 - val_loss: 0.4537 - val_accuracy: 0.8142
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 231ms/step - loss: 3.9221 - accuracy: 0.5130 - val_loss: 3.3483 - val_accuracy: 0.7978
Epoch 2/100
2/2 [==============================] - 0s 41ms/step - loss: 3.2995 - accuracy: 0.7565 - val_loss: 3.0280 - val_accuracy: 0.8197
Epoch 3/100
2/2 [==============================] - 0s 38ms/step - loss: 3.0166 - accuracy: 0.7852 - val_loss: 2.7981 - val_accuracy: 0.8361
Epoch 4/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8084 - accuracy: 0.8167 - val_loss: 2.6177 - val_accuracy: 0.8361
Epoch 5/100
2/2 [==============================] - 0s 41ms/step - loss: 2.6123 - accuracy: 0.8468 - val_loss: 2.4712 - val_accuracy: 0.8415
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 2.4776 - accuracy: 0.8509 - val_loss: 2.3423 - val_accuracy: 0.8415
Epoch 7/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3553 - accuracy: 0.8454 - val_loss: 2.2310 - val_accuracy: 0.8361
Epoch 8/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2357 - accuracy: 0.8454 - val_loss: 2.1317 - val_accuracy: 0.8415
Epoch 9/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1491 - accuracy: 0.8495 - val_loss: 2.0411 - val_accuracy: 0.8415
Epoch 10/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0588 - accuracy: 0.8440 - val_loss: 1.9585 - val_accuracy: 0.8415
Epoch 11/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9703 - accuracy: 0.8495 - val_loss: 1.8835 - val_accuracy: 0.8415
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8961 - accuracy: 0.8550 - val_loss: 1.8132 - val_accuracy: 0.8415
Epoch 13/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8254 - accuracy: 0.8523 - val_loss: 1.7487 - val_accuracy: 0.8415
Epoch 14/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7613 - accuracy: 0.8523 - val_loss: 1.6883 - val_accuracy: 0.8415
Epoch 15/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6990 - accuracy: 0.8536 - val_loss: 1.6319 - val_accuracy: 0.8415
Epoch 16/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6350 - accuracy: 0.8564 - val_loss: 1.5786 - val_accuracy: 0.8415
Epoch 17/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5945 - accuracy: 0.8550 - val_loss: 1.5278 - val_accuracy: 0.8415
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5457 - accuracy: 0.8536 - val_loss: 1.4812 - val_accuracy: 0.8415
Epoch 19/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5024 - accuracy: 0.8536 - val_loss: 1.4349 - val_accuracy: 0.8415
Epoch 20/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4506 - accuracy: 0.8523 - val_loss: 1.3927 - val_accuracy: 0.8415
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4106 - accuracy: 0.8523 - val_loss: 1.3523 - val_accuracy: 0.8415
Epoch 22/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3697 - accuracy: 0.8482 - val_loss: 1.3131 - val_accuracy: 0.8415
Epoch 23/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3275 - accuracy: 0.8509 - val_loss: 1.2768 - val_accuracy: 0.8415
Epoch 24/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2970 - accuracy: 0.8523 - val_loss: 1.2409 - val_accuracy: 0.8415
Epoch 25/100
2/2 [==============================] - 0s 28ms/step - loss: 1.2601 - accuracy: 0.8536 - val_loss: 1.2077 - val_accuracy: 0.8415
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2297 - accuracy: 0.8495 - val_loss: 1.1760 - val_accuracy: 0.8415
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1934 - accuracy: 0.8509 - val_loss: 1.1434 - val_accuracy: 0.8415
Epoch 28/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1680 - accuracy: 0.8550 - val_loss: 1.1138 - val_accuracy: 0.8415
Epoch 29/100
2/2 [==============================] - 0s 35ms/step - loss: 1.1316 - accuracy: 0.8536 - val_loss: 1.0853 - val_accuracy: 0.8415
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1016 - accuracy: 0.8495 - val_loss: 1.0585 - val_accuracy: 0.8415
Epoch 31/100
2/2 [==============================] - 0s 34ms/step - loss: 1.0711 - accuracy: 0.8536 - val_loss: 1.0322 - val_accuracy: 0.8415
Epoch 32/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0504 - accuracy: 0.8536 - val_loss: 1.0073 - val_accuracy: 0.8415
Epoch 33/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0264 - accuracy: 0.8523 - val_loss: 0.9829 - val_accuracy: 0.8415
Epoch 34/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9997 - accuracy: 0.8577 - val_loss: 0.9589 - val_accuracy: 0.8415
Epoch 35/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9784 - accuracy: 0.8536 - val_loss: 0.9367 - val_accuracy: 0.8415
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9503 - accuracy: 0.8536 - val_loss: 0.9157 - val_accuracy: 0.8415
Epoch 37/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9284 - accuracy: 0.8509 - val_loss: 0.8947 - val_accuracy: 0.8415
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9072 - accuracy: 0.8523 - val_loss: 0.8737 - val_accuracy: 0.8415
Epoch 39/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8953 - accuracy: 0.8536 - val_loss: 0.8538 - val_accuracy: 0.8415
Epoch 40/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8731 - accuracy: 0.8550 - val_loss: 0.8347 - val_accuracy: 0.8415
Epoch 41/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8476 - accuracy: 0.8523 - val_loss: 0.8166 - val_accuracy: 0.8415
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8375 - accuracy: 0.8577 - val_loss: 0.8004 - val_accuracy: 0.8415
Epoch 43/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8174 - accuracy: 0.8523 - val_loss: 0.7838 - val_accuracy: 0.8415
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8016 - accuracy: 0.8523 - val_loss: 0.7668 - val_accuracy: 0.8415
Epoch 45/100
2/2 [==============================] - 0s 28ms/step - loss: 0.7865 - accuracy: 0.8523 - val_loss: 0.7502 - val_accuracy: 0.8415
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7708 - accuracy: 0.8536 - val_loss: 0.7354 - val_accuracy: 0.8415
Epoch 47/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7548 - accuracy: 0.8523 - val_loss: 0.7211 - val_accuracy: 0.8415
Epoch 48/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7428 - accuracy: 0.8523 - val_loss: 0.7066 - val_accuracy: 0.8415
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7327 - accuracy: 0.8550 - val_loss: 0.6938 - val_accuracy: 0.8415
Epoch 50/100
2/2 [==============================] - 0s 29ms/step - loss: 0.7149 - accuracy: 0.8523 - val_loss: 0.6803 - val_accuracy: 0.8415
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7057 - accuracy: 0.8523 - val_loss: 0.6682 - val_accuracy: 0.8415
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6843 - accuracy: 0.8523 - val_loss: 0.6556 - val_accuracy: 0.8415
Epoch 53/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6824 - accuracy: 0.8509 - val_loss: 0.6449 - val_accuracy: 0.8415
Epoch 54/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6669 - accuracy: 0.8523 - val_loss: 0.6326 - val_accuracy: 0.8415
Epoch 55/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6580 - accuracy: 0.8523 - val_loss: 0.6218 - val_accuracy: 0.8415
Epoch 56/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6440 - accuracy: 0.8523 - val_loss: 0.6118 - val_accuracy: 0.8415
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6281 - accuracy: 0.8523 - val_loss: 0.6026 - val_accuracy: 0.8415
Epoch 58/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6191 - accuracy: 0.8536 - val_loss: 0.5952 - val_accuracy: 0.8415
Epoch 59/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6170 - accuracy: 0.8509 - val_loss: 0.5851 - val_accuracy: 0.8415
Epoch 60/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6069 - accuracy: 0.8523 - val_loss: 0.5773 - val_accuracy: 0.8415
Epoch 61/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6012 - accuracy: 0.8523 - val_loss: 0.5679 - val_accuracy: 0.8415
Epoch 62/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5854 - accuracy: 0.8523 - val_loss: 0.5602 - val_accuracy: 0.8415
Epoch 63/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5817 - accuracy: 0.8564 - val_loss: 0.5533 - val_accuracy: 0.8415
Epoch 64/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5630 - accuracy: 0.8523 - val_loss: 0.5460 - val_accuracy: 0.8415
Epoch 65/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5575 - accuracy: 0.8536 - val_loss: 0.5397 - val_accuracy: 0.8415
Epoch 66/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5554 - accuracy: 0.8523 - val_loss: 0.5322 - val_accuracy: 0.8415
Epoch 67/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5510 - accuracy: 0.8523 - val_loss: 0.5264 - val_accuracy: 0.8415
Epoch 68/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5421 - accuracy: 0.8564 - val_loss: 0.5218 - val_accuracy: 0.8415
Epoch 69/100
2/2 [==============================] - 0s 81ms/step - loss: 0.5412 - accuracy: 0.8523 - val_loss: 0.5163 - val_accuracy: 0.8415
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5275 - accuracy: 0.8536 - val_loss: 0.5116 - val_accuracy: 0.8415
Epoch 71/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5274 - accuracy: 0.8523 - val_loss: 0.5031 - val_accuracy: 0.8415
Epoch 72/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5158 - accuracy: 0.8523 - val_loss: 0.4981 - val_accuracy: 0.8415
Epoch 73/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5144 - accuracy: 0.8550 - val_loss: 0.4927 - val_accuracy: 0.8415
Epoch 74/100
2/2 [==============================] - 0s 28ms/step - loss: 0.5107 - accuracy: 0.8509 - val_loss: 0.4884 - val_accuracy: 0.8415
Epoch 75/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5040 - accuracy: 0.8509 - val_loss: 0.4825 - val_accuracy: 0.8415
Epoch 76/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4944 - accuracy: 0.8523 - val_loss: 0.4781 - val_accuracy: 0.8415
Epoch 77/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4904 - accuracy: 0.8509 - val_loss: 0.4734 - val_accuracy: 0.8415
Epoch 78/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4928 - accuracy: 0.8523 - val_loss: 0.4685 - val_accuracy: 0.8415
Epoch 79/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4949 - accuracy: 0.8495 - val_loss: 0.4645 - val_accuracy: 0.8415
Epoch 80/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4862 - accuracy: 0.8523 - val_loss: 0.4615 - val_accuracy: 0.8415
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4760 - accuracy: 0.8550 - val_loss: 0.4555 - val_accuracy: 0.8525
Epoch 82/100
2/2 [==============================] - 0s 45ms/step - loss: 0.4752 - accuracy: 0.8523 - val_loss: 0.4536 - val_accuracy: 0.8415
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4693 - accuracy: 0.8523 - val_loss: 0.4480 - val_accuracy: 0.8415
Epoch 84/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4684 - accuracy: 0.8550 - val_loss: 0.4460 - val_accuracy: 0.8415
Epoch 85/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4642 - accuracy: 0.8536 - val_loss: 0.4408 - val_accuracy: 0.8415
Epoch 86/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4586 - accuracy: 0.8495 - val_loss: 0.4382 - val_accuracy: 0.8415
Epoch 87/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4556 - accuracy: 0.8536 - val_loss: 0.4368 - val_accuracy: 0.8415
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4524 - accuracy: 0.8523 - val_loss: 0.4324 - val_accuracy: 0.8415
Epoch 89/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4532 - accuracy: 0.8495 - val_loss: 0.4304 - val_accuracy: 0.8415
Epoch 90/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4471 - accuracy: 0.8550 - val_loss: 0.4263 - val_accuracy: 0.8415
Epoch 91/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4422 - accuracy: 0.8536 - val_loss: 0.4255 - val_accuracy: 0.8415
Epoch 92/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4443 - accuracy: 0.8550 - val_loss: 0.4234 - val_accuracy: 0.8415
Epoch 93/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4380 - accuracy: 0.8536 - val_loss: 0.4213 - val_accuracy: 0.8415
Epoch 94/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4406 - accuracy: 0.8536 - val_loss: 0.4192 - val_accuracy: 0.8415
Epoch 95/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4333 - accuracy: 0.8523 - val_loss: 0.4180 - val_accuracy: 0.8415
Epoch 96/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4340 - accuracy: 0.8509 - val_loss: 0.4139 - val_accuracy: 0.8415
Epoch 97/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4264 - accuracy: 0.8523 - val_loss: 0.4121 - val_accuracy: 0.8415
Epoch 98/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4263 - accuracy: 0.8550 - val_loss: 0.4098 - val_accuracy: 0.8415
Epoch 99/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4348 - accuracy: 0.8577 - val_loss: 0.4077 - val_accuracy: 0.8415
Epoch 100/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4244 - accuracy: 0.8577 - val_loss: 0.4080 - val_accuracy: 0.8415
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 229ms/step - loss: 4.4019 - accuracy: 0.1382 - val_loss: 3.6999 - val_accuracy: 0.3005
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 3.6802 - accuracy: 0.2955 - val_loss: 3.3129 - val_accuracy: 0.4973
Epoch 3/100
2/2 [==============================] - 0s 38ms/step - loss: 3.2990 - accuracy: 0.4706 - val_loss: 3.0489 - val_accuracy: 0.6503
Epoch 4/100
2/2 [==============================] - 0s 40ms/step - loss: 3.0715 - accuracy: 0.5472 - val_loss: 2.8435 - val_accuracy: 0.8033
Epoch 5/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8433 - accuracy: 0.6813 - val_loss: 2.6773 - val_accuracy: 0.8361
Epoch 6/100
2/2 [==============================] - 0s 42ms/step - loss: 2.6858 - accuracy: 0.7264 - val_loss: 2.5360 - val_accuracy: 0.8470
Epoch 7/100
2/2 [==============================] - 0s 38ms/step - loss: 2.5317 - accuracy: 0.7852 - val_loss: 2.4128 - val_accuracy: 0.8470
Epoch 8/100
2/2 [==============================] - 0s 37ms/step - loss: 2.4379 - accuracy: 0.7798 - val_loss: 2.3043 - val_accuracy: 0.8470
Epoch 9/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3088 - accuracy: 0.8098 - val_loss: 2.2065 - val_accuracy: 0.8470
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 2.2232 - accuracy: 0.8276 - val_loss: 2.1179 - val_accuracy: 0.8470
Epoch 11/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1239 - accuracy: 0.8263 - val_loss: 2.0375 - val_accuracy: 0.8470
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0394 - accuracy: 0.8331 - val_loss: 1.9633 - val_accuracy: 0.8470
Epoch 13/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9705 - accuracy: 0.8345 - val_loss: 1.8945 - val_accuracy: 0.8470
Epoch 14/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8930 - accuracy: 0.8345 - val_loss: 1.8301 - val_accuracy: 0.8470
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8356 - accuracy: 0.8427 - val_loss: 1.7700 - val_accuracy: 0.8470
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7707 - accuracy: 0.8454 - val_loss: 1.7141 - val_accuracy: 0.8470
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7117 - accuracy: 0.8495 - val_loss: 1.6614 - val_accuracy: 0.8470
Epoch 18/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6729 - accuracy: 0.8440 - val_loss: 1.6109 - val_accuracy: 0.8470
Epoch 19/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6189 - accuracy: 0.8482 - val_loss: 1.5631 - val_accuracy: 0.8470
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5640 - accuracy: 0.8495 - val_loss: 1.5175 - val_accuracy: 0.8470
Epoch 21/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5184 - accuracy: 0.8454 - val_loss: 1.4750 - val_accuracy: 0.8470
Epoch 22/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4764 - accuracy: 0.8523 - val_loss: 1.4343 - val_accuracy: 0.8470
Epoch 23/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4216 - accuracy: 0.8523 - val_loss: 1.3955 - val_accuracy: 0.8470
Epoch 24/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4016 - accuracy: 0.8495 - val_loss: 1.3576 - val_accuracy: 0.8470
Epoch 25/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3528 - accuracy: 0.8509 - val_loss: 1.3220 - val_accuracy: 0.8470
Epoch 26/100
2/2 [==============================] - 0s 27ms/step - loss: 1.3226 - accuracy: 0.8468 - val_loss: 1.2872 - val_accuracy: 0.8470
Epoch 27/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2901 - accuracy: 0.8495 - val_loss: 1.2547 - val_accuracy: 0.8470
Epoch 28/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2453 - accuracy: 0.8509 - val_loss: 1.2234 - val_accuracy: 0.8470
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2303 - accuracy: 0.8523 - val_loss: 1.1930 - val_accuracy: 0.8470
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2047 - accuracy: 0.8468 - val_loss: 1.1635 - val_accuracy: 0.8470
Epoch 31/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1631 - accuracy: 0.8509 - val_loss: 1.1352 - val_accuracy: 0.8470
Epoch 32/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1375 - accuracy: 0.8509 - val_loss: 1.1081 - val_accuracy: 0.8470
Epoch 33/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1118 - accuracy: 0.8495 - val_loss: 1.0814 - val_accuracy: 0.8470
Epoch 34/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0834 - accuracy: 0.8509 - val_loss: 1.0556 - val_accuracy: 0.8470
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0563 - accuracy: 0.8523 - val_loss: 1.0316 - val_accuracy: 0.8470
Epoch 36/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0387 - accuracy: 0.8536 - val_loss: 1.0083 - val_accuracy: 0.8470
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0148 - accuracy: 0.8523 - val_loss: 0.9851 - val_accuracy: 0.8470
Epoch 38/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9947 - accuracy: 0.8482 - val_loss: 0.9631 - val_accuracy: 0.8470
Epoch 39/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9714 - accuracy: 0.8509 - val_loss: 0.9422 - val_accuracy: 0.8470
Epoch 40/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9441 - accuracy: 0.8509 - val_loss: 0.9222 - val_accuracy: 0.8470
Epoch 41/100
2/2 [==============================] - 0s 30ms/step - loss: 0.9277 - accuracy: 0.8495 - val_loss: 0.9018 - val_accuracy: 0.8470
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9014 - accuracy: 0.8536 - val_loss: 0.8838 - val_accuracy: 0.8470
Epoch 43/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8842 - accuracy: 0.8536 - val_loss: 0.8650 - val_accuracy: 0.8470
Epoch 44/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8627 - accuracy: 0.8509 - val_loss: 0.8475 - val_accuracy: 0.8470
Epoch 45/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8557 - accuracy: 0.8523 - val_loss: 0.8302 - val_accuracy: 0.8470
Epoch 46/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8370 - accuracy: 0.8509 - val_loss: 0.8135 - val_accuracy: 0.8470
Epoch 47/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8234 - accuracy: 0.8495 - val_loss: 0.7970 - val_accuracy: 0.8470
Epoch 48/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8024 - accuracy: 0.8509 - val_loss: 0.7812 - val_accuracy: 0.8470
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7895 - accuracy: 0.8495 - val_loss: 0.7656 - val_accuracy: 0.8470
Epoch 50/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7627 - accuracy: 0.8550 - val_loss: 0.7513 - val_accuracy: 0.8470
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7565 - accuracy: 0.8536 - val_loss: 0.7378 - val_accuracy: 0.8470
Epoch 52/100
2/2 [==============================] - 0s 45ms/step - loss: 0.7465 - accuracy: 0.8550 - val_loss: 0.7240 - val_accuracy: 0.8470
Epoch 53/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7252 - accuracy: 0.8523 - val_loss: 0.7113 - val_accuracy: 0.8470
Epoch 54/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7083 - accuracy: 0.8550 - val_loss: 0.6987 - val_accuracy: 0.8470
Epoch 55/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7043 - accuracy: 0.8523 - val_loss: 0.6863 - val_accuracy: 0.8470
Epoch 56/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6887 - accuracy: 0.8482 - val_loss: 0.6745 - val_accuracy: 0.8470
Epoch 57/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6786 - accuracy: 0.8495 - val_loss: 0.6636 - val_accuracy: 0.8470
Epoch 58/100
2/2 [==============================] - 0s 42ms/step - loss: 0.6694 - accuracy: 0.8523 - val_loss: 0.6527 - val_accuracy: 0.8470
Epoch 59/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6672 - accuracy: 0.8495 - val_loss: 0.6427 - val_accuracy: 0.8470
Epoch 60/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6525 - accuracy: 0.8550 - val_loss: 0.6329 - val_accuracy: 0.8470
Epoch 61/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6377 - accuracy: 0.8495 - val_loss: 0.6237 - val_accuracy: 0.8470
Epoch 62/100
2/2 [==============================] - 0s 42ms/step - loss: 0.6289 - accuracy: 0.8482 - val_loss: 0.6145 - val_accuracy: 0.8470
Epoch 63/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6112 - accuracy: 0.8509 - val_loss: 0.6056 - val_accuracy: 0.8470
Epoch 64/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6119 - accuracy: 0.8482 - val_loss: 0.5970 - val_accuracy: 0.8470
Epoch 65/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6098 - accuracy: 0.8509 - val_loss: 0.5888 - val_accuracy: 0.8470
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5990 - accuracy: 0.8550 - val_loss: 0.5809 - val_accuracy: 0.8470
Epoch 67/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5811 - accuracy: 0.8536 - val_loss: 0.5737 - val_accuracy: 0.8470
Epoch 68/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5753 - accuracy: 0.8523 - val_loss: 0.5662 - val_accuracy: 0.8470
Epoch 69/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5751 - accuracy: 0.8523 - val_loss: 0.5593 - val_accuracy: 0.8470
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5614 - accuracy: 0.8536 - val_loss: 0.5530 - val_accuracy: 0.8470
Epoch 71/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5606 - accuracy: 0.8523 - val_loss: 0.5470 - val_accuracy: 0.8470
Epoch 72/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5541 - accuracy: 0.8536 - val_loss: 0.5401 - val_accuracy: 0.8470
Epoch 73/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5443 - accuracy: 0.8509 - val_loss: 0.5335 - val_accuracy: 0.8470
Epoch 74/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5454 - accuracy: 0.8536 - val_loss: 0.5276 - val_accuracy: 0.8470
Epoch 75/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5406 - accuracy: 0.8509 - val_loss: 0.5224 - val_accuracy: 0.8470
Epoch 76/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5236 - accuracy: 0.8495 - val_loss: 0.5174 - val_accuracy: 0.8470
Epoch 77/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5268 - accuracy: 0.8523 - val_loss: 0.5116 - val_accuracy: 0.8470
Epoch 78/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5211 - accuracy: 0.8536 - val_loss: 0.5059 - val_accuracy: 0.8470
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5138 - accuracy: 0.8509 - val_loss: 0.5008 - val_accuracy: 0.8470
Epoch 80/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5121 - accuracy: 0.8495 - val_loss: 0.4962 - val_accuracy: 0.8470
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5073 - accuracy: 0.8564 - val_loss: 0.4923 - val_accuracy: 0.8470
Epoch 82/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4965 - accuracy: 0.8482 - val_loss: 0.4875 - val_accuracy: 0.8470
Epoch 83/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4883 - accuracy: 0.8495 - val_loss: 0.4826 - val_accuracy: 0.8470
Epoch 84/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4885 - accuracy: 0.8536 - val_loss: 0.4790 - val_accuracy: 0.8470
Epoch 85/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4788 - accuracy: 0.8564 - val_loss: 0.4748 - val_accuracy: 0.8470
Epoch 86/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4786 - accuracy: 0.8564 - val_loss: 0.4716 - val_accuracy: 0.8470
Epoch 87/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4760 - accuracy: 0.8536 - val_loss: 0.4681 - val_accuracy: 0.8470
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4823 - accuracy: 0.8495 - val_loss: 0.4643 - val_accuracy: 0.8470
Epoch 89/100
2/2 [==============================] - 0s 46ms/step - loss: 0.4729 - accuracy: 0.8509 - val_loss: 0.4616 - val_accuracy: 0.8470
Epoch 90/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4680 - accuracy: 0.8536 - val_loss: 0.4590 - val_accuracy: 0.8470
Epoch 91/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4733 - accuracy: 0.8536 - val_loss: 0.4557 - val_accuracy: 0.8470
Epoch 92/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4653 - accuracy: 0.8564 - val_loss: 0.4522 - val_accuracy: 0.8470
Epoch 93/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4527 - accuracy: 0.8550 - val_loss: 0.4492 - val_accuracy: 0.8470
Epoch 94/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4553 - accuracy: 0.8550 - val_loss: 0.4463 - val_accuracy: 0.8470
Epoch 95/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4506 - accuracy: 0.8632 - val_loss: 0.4439 - val_accuracy: 0.8470
Epoch 96/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4443 - accuracy: 0.8564 - val_loss: 0.4410 - val_accuracy: 0.8470
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4501 - accuracy: 0.8591 - val_loss: 0.4383 - val_accuracy: 0.8470
Epoch 98/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4476 - accuracy: 0.8564 - val_loss: 0.4366 - val_accuracy: 0.8470
Epoch 99/100
2/2 [==============================] - 0s 29ms/step - loss: 0.4414 - accuracy: 0.8509 - val_loss: 0.4338 - val_accuracy: 0.8470
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4417 - accuracy: 0.8495 - val_loss: 0.4316 - val_accuracy: 0.8470
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 221ms/step - loss: 4.0579 - accuracy: 0.3885 - val_loss: 3.4976 - val_accuracy: 0.6721
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 3.4546 - accuracy: 0.6430 - val_loss: 3.1505 - val_accuracy: 0.7923
Epoch 3/100
2/2 [==============================] - 0s 91ms/step - loss: 3.1201 - accuracy: 0.7305 - val_loss: 2.9102 - val_accuracy: 0.8525
Epoch 4/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8904 - accuracy: 0.7866 - val_loss: 2.7184 - val_accuracy: 0.8689
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 2.7150 - accuracy: 0.8167 - val_loss: 2.5623 - val_accuracy: 0.8634
Epoch 6/100
2/2 [==============================] - 0s 43ms/step - loss: 2.5533 - accuracy: 0.8249 - val_loss: 2.4301 - val_accuracy: 0.8689
Epoch 7/100
2/2 [==============================] - 0s 44ms/step - loss: 2.4406 - accuracy: 0.8181 - val_loss: 2.3147 - val_accuracy: 0.8798
Epoch 8/100
2/2 [==============================] - 0s 44ms/step - loss: 2.3232 - accuracy: 0.8358 - val_loss: 2.2100 - val_accuracy: 0.8798
Epoch 9/100
2/2 [==============================] - 0s 30ms/step - loss: 2.2142 - accuracy: 0.8331 - val_loss: 2.1176 - val_accuracy: 0.8798
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1279 - accuracy: 0.8495 - val_loss: 2.0326 - val_accuracy: 0.8852
Epoch 11/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0450 - accuracy: 0.8440 - val_loss: 1.9534 - val_accuracy: 0.8852
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9634 - accuracy: 0.8427 - val_loss: 1.8813 - val_accuracy: 0.8852
Epoch 13/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8953 - accuracy: 0.8523 - val_loss: 1.8141 - val_accuracy: 0.8852
Epoch 14/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8351 - accuracy: 0.8372 - val_loss: 1.7532 - val_accuracy: 0.8852
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7646 - accuracy: 0.8550 - val_loss: 1.6933 - val_accuracy: 0.8852
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7115 - accuracy: 0.8495 - val_loss: 1.6390 - val_accuracy: 0.8852
Epoch 17/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6462 - accuracy: 0.8591 - val_loss: 1.5873 - val_accuracy: 0.8852
Epoch 18/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6051 - accuracy: 0.8482 - val_loss: 1.5399 - val_accuracy: 0.8852
Epoch 19/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5610 - accuracy: 0.8440 - val_loss: 1.4938 - val_accuracy: 0.8852
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5085 - accuracy: 0.8440 - val_loss: 1.4490 - val_accuracy: 0.8852
Epoch 21/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4656 - accuracy: 0.8358 - val_loss: 1.4077 - val_accuracy: 0.8852
Epoch 22/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4338 - accuracy: 0.8468 - val_loss: 1.3680 - val_accuracy: 0.8852
Epoch 23/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3837 - accuracy: 0.8605 - val_loss: 1.3302 - val_accuracy: 0.8852
Epoch 24/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3492 - accuracy: 0.8509 - val_loss: 1.2937 - val_accuracy: 0.8852
Epoch 25/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3069 - accuracy: 0.8482 - val_loss: 1.2588 - val_accuracy: 0.8852
Epoch 26/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2845 - accuracy: 0.8523 - val_loss: 1.2251 - val_accuracy: 0.8852
Epoch 27/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2429 - accuracy: 0.8468 - val_loss: 1.1933 - val_accuracy: 0.8852
Epoch 28/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2067 - accuracy: 0.8550 - val_loss: 1.1623 - val_accuracy: 0.8852
Epoch 29/100
2/2 [==============================] - 0s 29ms/step - loss: 1.1770 - accuracy: 0.8468 - val_loss: 1.1329 - val_accuracy: 0.8852
Epoch 30/100
2/2 [==============================] - 0s 48ms/step - loss: 1.1593 - accuracy: 0.8509 - val_loss: 1.1042 - val_accuracy: 0.8852
Epoch 31/100
2/2 [==============================] - 0s 43ms/step - loss: 1.1152 - accuracy: 0.8495 - val_loss: 1.0765 - val_accuracy: 0.8852
Epoch 32/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1033 - accuracy: 0.8509 - val_loss: 1.0511 - val_accuracy: 0.8852
Epoch 33/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0731 - accuracy: 0.8482 - val_loss: 1.0261 - val_accuracy: 0.8852
Epoch 34/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0444 - accuracy: 0.8523 - val_loss: 1.0017 - val_accuracy: 0.8852
Epoch 35/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0233 - accuracy: 0.8523 - val_loss: 0.9772 - val_accuracy: 0.8852
Epoch 36/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9933 - accuracy: 0.8509 - val_loss: 0.9562 - val_accuracy: 0.8852
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9752 - accuracy: 0.8482 - val_loss: 0.9345 - val_accuracy: 0.8852
Epoch 38/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9475 - accuracy: 0.8495 - val_loss: 0.9135 - val_accuracy: 0.8852
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9349 - accuracy: 0.8427 - val_loss: 0.8924 - val_accuracy: 0.8852
Epoch 40/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9083 - accuracy: 0.8495 - val_loss: 0.8735 - val_accuracy: 0.8852
Epoch 41/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8867 - accuracy: 0.8468 - val_loss: 0.8544 - val_accuracy: 0.8852
Epoch 42/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8692 - accuracy: 0.8482 - val_loss: 0.8362 - val_accuracy: 0.8852
Epoch 43/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8573 - accuracy: 0.8509 - val_loss: 0.8183 - val_accuracy: 0.8852
Epoch 44/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8416 - accuracy: 0.8454 - val_loss: 0.8025 - val_accuracy: 0.8852
Epoch 45/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8205 - accuracy: 0.8454 - val_loss: 0.7874 - val_accuracy: 0.8852
Epoch 46/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8100 - accuracy: 0.8509 - val_loss: 0.7721 - val_accuracy: 0.8852
Epoch 47/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7865 - accuracy: 0.8440 - val_loss: 0.7565 - val_accuracy: 0.8852
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7739 - accuracy: 0.8413 - val_loss: 0.7428 - val_accuracy: 0.8852
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7663 - accuracy: 0.8468 - val_loss: 0.7291 - val_accuracy: 0.8852
Epoch 50/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7486 - accuracy: 0.8509 - val_loss: 0.7150 - val_accuracy: 0.8852
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7323 - accuracy: 0.8482 - val_loss: 0.7005 - val_accuracy: 0.8852
Epoch 52/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7198 - accuracy: 0.8509 - val_loss: 0.6888 - val_accuracy: 0.8852
Epoch 53/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7147 - accuracy: 0.8495 - val_loss: 0.6769 - val_accuracy: 0.8852
Epoch 54/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7035 - accuracy: 0.8454 - val_loss: 0.6649 - val_accuracy: 0.8852
Epoch 55/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6856 - accuracy: 0.8482 - val_loss: 0.6531 - val_accuracy: 0.8852
Epoch 56/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6688 - accuracy: 0.8509 - val_loss: 0.6419 - val_accuracy: 0.8852
Epoch 57/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6621 - accuracy: 0.8523 - val_loss: 0.6309 - val_accuracy: 0.8852
Epoch 58/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6479 - accuracy: 0.8495 - val_loss: 0.6226 - val_accuracy: 0.8852
Epoch 59/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6404 - accuracy: 0.8523 - val_loss: 0.6126 - val_accuracy: 0.8852
Epoch 60/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6307 - accuracy: 0.8495 - val_loss: 0.6043 - val_accuracy: 0.8798
Epoch 61/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6245 - accuracy: 0.8454 - val_loss: 0.5942 - val_accuracy: 0.8852
Epoch 62/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6051 - accuracy: 0.8564 - val_loss: 0.5862 - val_accuracy: 0.8852
Epoch 63/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6025 - accuracy: 0.8536 - val_loss: 0.5776 - val_accuracy: 0.8743
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5943 - accuracy: 0.8495 - val_loss: 0.5681 - val_accuracy: 0.8743
Epoch 65/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5881 - accuracy: 0.8468 - val_loss: 0.5609 - val_accuracy: 0.8743
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5740 - accuracy: 0.8550 - val_loss: 0.5553 - val_accuracy: 0.8798
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5690 - accuracy: 0.8577 - val_loss: 0.5496 - val_accuracy: 0.8798
Epoch 68/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5526 - accuracy: 0.8605 - val_loss: 0.5413 - val_accuracy: 0.8798
Epoch 69/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5518 - accuracy: 0.8536 - val_loss: 0.5357 - val_accuracy: 0.8798
Epoch 70/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5417 - accuracy: 0.8536 - val_loss: 0.5288 - val_accuracy: 0.8798
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5360 - accuracy: 0.8550 - val_loss: 0.5218 - val_accuracy: 0.8798
Epoch 72/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5325 - accuracy: 0.8523 - val_loss: 0.5159 - val_accuracy: 0.8798
Epoch 73/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5221 - accuracy: 0.8605 - val_loss: 0.5096 - val_accuracy: 0.8798
Epoch 74/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5228 - accuracy: 0.8468 - val_loss: 0.5040 - val_accuracy: 0.8798
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5191 - accuracy: 0.8605 - val_loss: 0.5022 - val_accuracy: 0.8798
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5150 - accuracy: 0.8536 - val_loss: 0.4946 - val_accuracy: 0.8798
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5086 - accuracy: 0.8605 - val_loss: 0.4903 - val_accuracy: 0.8798
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4998 - accuracy: 0.8618 - val_loss: 0.4835 - val_accuracy: 0.8798
Epoch 79/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4916 - accuracy: 0.8618 - val_loss: 0.4777 - val_accuracy: 0.8798
Epoch 80/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4936 - accuracy: 0.8440 - val_loss: 0.4741 - val_accuracy: 0.8798
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4769 - accuracy: 0.8550 - val_loss: 0.4699 - val_accuracy: 0.8798
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4809 - accuracy: 0.8523 - val_loss: 0.4665 - val_accuracy: 0.8798
Epoch 83/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4707 - accuracy: 0.8495 - val_loss: 0.4653 - val_accuracy: 0.8798
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4650 - accuracy: 0.8618 - val_loss: 0.4583 - val_accuracy: 0.8798
Epoch 85/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4669 - accuracy: 0.8550 - val_loss: 0.4551 - val_accuracy: 0.8798
Epoch 86/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4662 - accuracy: 0.8577 - val_loss: 0.4503 - val_accuracy: 0.8798
Epoch 87/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4513 - accuracy: 0.8646 - val_loss: 0.4449 - val_accuracy: 0.8798
Epoch 88/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4578 - accuracy: 0.8577 - val_loss: 0.4447 - val_accuracy: 0.8798
Epoch 89/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4485 - accuracy: 0.8523 - val_loss: 0.4390 - val_accuracy: 0.8798
Epoch 90/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4450 - accuracy: 0.8605 - val_loss: 0.4375 - val_accuracy: 0.8798
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4454 - accuracy: 0.8550 - val_loss: 0.4352 - val_accuracy: 0.8798
Epoch 92/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4406 - accuracy: 0.8536 - val_loss: 0.4332 - val_accuracy: 0.8798
Epoch 93/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4329 - accuracy: 0.8646 - val_loss: 0.4306 - val_accuracy: 0.8798
Epoch 94/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4384 - accuracy: 0.8632 - val_loss: 0.4313 - val_accuracy: 0.8689
Epoch 95/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4367 - accuracy: 0.8577 - val_loss: 0.4270 - val_accuracy: 0.8743
Epoch 96/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4324 - accuracy: 0.8659 - val_loss: 0.4216 - val_accuracy: 0.8798
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4221 - accuracy: 0.8618 - val_loss: 0.4172 - val_accuracy: 0.8798
Epoch 98/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4252 - accuracy: 0.8618 - val_loss: 0.4154 - val_accuracy: 0.8798
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4232 - accuracy: 0.8550 - val_loss: 0.4174 - val_accuracy: 0.8743
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4213 - accuracy: 0.8495 - val_loss: 0.4187 - val_accuracy: 0.8689
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
2/2 [==============================] - 1s 227ms/step - loss: 4.3021 - accuracy: 0.1462 - val_loss: 3.6382 - val_accuracy: 0.3462
Epoch 2/100
2/2 [==============================] - 0s 44ms/step - loss: 3.6220 - accuracy: 0.3074 - val_loss: 3.2524 - val_accuracy: 0.5220
Epoch 3/100
2/2 [==============================] - 0s 39ms/step - loss: 3.2489 - accuracy: 0.5164 - val_loss: 2.9822 - val_accuracy: 0.7308
Epoch 4/100
2/2 [==============================] - 0s 41ms/step - loss: 2.9947 - accuracy: 0.6120 - val_loss: 2.7748 - val_accuracy: 0.8297
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 2.7921 - accuracy: 0.6844 - val_loss: 2.6085 - val_accuracy: 0.8626
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 2.6389 - accuracy: 0.7363 - val_loss: 2.4665 - val_accuracy: 0.8681
Epoch 7/100
2/2 [==============================] - 0s 37ms/step - loss: 2.4899 - accuracy: 0.7937 - val_loss: 2.3442 - val_accuracy: 0.8681
Epoch 8/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3816 - accuracy: 0.8087 - val_loss: 2.2354 - val_accuracy: 0.8626
Epoch 9/100
2/2 [==============================] - 0s 36ms/step - loss: 2.2568 - accuracy: 0.8183 - val_loss: 2.1376 - val_accuracy: 0.8626
Epoch 10/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1687 - accuracy: 0.8224 - val_loss: 2.0508 - val_accuracy: 0.8626
Epoch 11/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0841 - accuracy: 0.8456 - val_loss: 1.9696 - val_accuracy: 0.8626
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0011 - accuracy: 0.8374 - val_loss: 1.8952 - val_accuracy: 0.8626
Epoch 13/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9182 - accuracy: 0.8333 - val_loss: 1.8267 - val_accuracy: 0.8626
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8543 - accuracy: 0.8429 - val_loss: 1.7621 - val_accuracy: 0.8626
Epoch 15/100
2/2 [==============================] - 0s 68ms/step - loss: 1.8001 - accuracy: 0.8333 - val_loss: 1.7031 - val_accuracy: 0.8571
Epoch 16/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7362 - accuracy: 0.8525 - val_loss: 1.6472 - val_accuracy: 0.8626
Epoch 17/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6602 - accuracy: 0.8484 - val_loss: 1.5939 - val_accuracy: 0.8626
Epoch 18/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6270 - accuracy: 0.8429 - val_loss: 1.5452 - val_accuracy: 0.8626
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5677 - accuracy: 0.8484 - val_loss: 1.4977 - val_accuracy: 0.8626
Epoch 20/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5160 - accuracy: 0.8511 - val_loss: 1.4541 - val_accuracy: 0.8626
Epoch 21/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4617 - accuracy: 0.8497 - val_loss: 1.4123 - val_accuracy: 0.8626
Epoch 22/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4322 - accuracy: 0.8511 - val_loss: 1.3716 - val_accuracy: 0.8626
Epoch 23/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3960 - accuracy: 0.8456 - val_loss: 1.3342 - val_accuracy: 0.8626
Epoch 24/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3573 - accuracy: 0.8470 - val_loss: 1.2978 - val_accuracy: 0.8626
Epoch 25/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3176 - accuracy: 0.8484 - val_loss: 1.2626 - val_accuracy: 0.8626
Epoch 26/100
2/2 [==============================] - 0s 46ms/step - loss: 1.2792 - accuracy: 0.8511 - val_loss: 1.2300 - val_accuracy: 0.8626
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2477 - accuracy: 0.8511 - val_loss: 1.1980 - val_accuracy: 0.8626
Epoch 28/100
2/2 [==============================] - 0s 28ms/step - loss: 1.2249 - accuracy: 0.8497 - val_loss: 1.1672 - val_accuracy: 0.8626
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1894 - accuracy: 0.8511 - val_loss: 1.1377 - val_accuracy: 0.8626
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1516 - accuracy: 0.8497 - val_loss: 1.1096 - val_accuracy: 0.8626
Epoch 31/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1242 - accuracy: 0.8497 - val_loss: 1.0826 - val_accuracy: 0.8626
Epoch 32/100
2/2 [==============================] - 0s 27ms/step - loss: 1.0970 - accuracy: 0.8497 - val_loss: 1.0565 - val_accuracy: 0.8626
Epoch 33/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0658 - accuracy: 0.8511 - val_loss: 1.0310 - val_accuracy: 0.8626
Epoch 34/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0370 - accuracy: 0.8484 - val_loss: 1.0066 - val_accuracy: 0.8626
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0237 - accuracy: 0.8470 - val_loss: 0.9845 - val_accuracy: 0.8626
Epoch 36/100
2/2 [==============================] - 0s 44ms/step - loss: 0.9849 - accuracy: 0.8484 - val_loss: 0.9612 - val_accuracy: 0.8626
Epoch 37/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9738 - accuracy: 0.8443 - val_loss: 0.9396 - val_accuracy: 0.8626
Epoch 38/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9487 - accuracy: 0.8497 - val_loss: 0.9189 - val_accuracy: 0.8626
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9366 - accuracy: 0.8470 - val_loss: 0.8987 - val_accuracy: 0.8626
Epoch 40/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9080 - accuracy: 0.8470 - val_loss: 0.8796 - val_accuracy: 0.8626
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8969 - accuracy: 0.8511 - val_loss: 0.8616 - val_accuracy: 0.8626
Epoch 42/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8703 - accuracy: 0.8525 - val_loss: 0.8439 - val_accuracy: 0.8626
Epoch 43/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8578 - accuracy: 0.8511 - val_loss: 0.8264 - val_accuracy: 0.8626
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8389 - accuracy: 0.8484 - val_loss: 0.8104 - val_accuracy: 0.8626
Epoch 45/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8206 - accuracy: 0.8470 - val_loss: 0.7945 - val_accuracy: 0.8626
Epoch 46/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8053 - accuracy: 0.8511 - val_loss: 0.7792 - val_accuracy: 0.8626
Epoch 47/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7946 - accuracy: 0.8484 - val_loss: 0.7646 - val_accuracy: 0.8626
Epoch 48/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7796 - accuracy: 0.8484 - val_loss: 0.7505 - val_accuracy: 0.8626
Epoch 49/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7666 - accuracy: 0.8443 - val_loss: 0.7374 - val_accuracy: 0.8626
Epoch 50/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7429 - accuracy: 0.8497 - val_loss: 0.7248 - val_accuracy: 0.8626
Epoch 51/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7348 - accuracy: 0.8511 - val_loss: 0.7124 - val_accuracy: 0.8626
Epoch 52/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7180 - accuracy: 0.8456 - val_loss: 0.7008 - val_accuracy: 0.8626
Epoch 53/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7096 - accuracy: 0.8484 - val_loss: 0.6882 - val_accuracy: 0.8626
Epoch 54/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6993 - accuracy: 0.8470 - val_loss: 0.6777 - val_accuracy: 0.8626
Epoch 55/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6854 - accuracy: 0.8470 - val_loss: 0.6667 - val_accuracy: 0.8626
Epoch 56/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6665 - accuracy: 0.8497 - val_loss: 0.6563 - val_accuracy: 0.8626
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6670 - accuracy: 0.8497 - val_loss: 0.6461 - val_accuracy: 0.8681
Epoch 58/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6511 - accuracy: 0.8484 - val_loss: 0.6362 - val_accuracy: 0.8681
Epoch 59/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6410 - accuracy: 0.8456 - val_loss: 0.6279 - val_accuracy: 0.8681
Epoch 60/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6386 - accuracy: 0.8538 - val_loss: 0.6178 - val_accuracy: 0.8681
Epoch 61/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6217 - accuracy: 0.8497 - val_loss: 0.6097 - val_accuracy: 0.8681
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6096 - accuracy: 0.8538 - val_loss: 0.6012 - val_accuracy: 0.8681
Epoch 63/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6143 - accuracy: 0.8443 - val_loss: 0.5931 - val_accuracy: 0.8681
Epoch 64/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5932 - accuracy: 0.8456 - val_loss: 0.5843 - val_accuracy: 0.8681
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5880 - accuracy: 0.8511 - val_loss: 0.5770 - val_accuracy: 0.8681
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5827 - accuracy: 0.8525 - val_loss: 0.5702 - val_accuracy: 0.8681
Epoch 67/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5720 - accuracy: 0.8525 - val_loss: 0.5622 - val_accuracy: 0.8681
Epoch 68/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5660 - accuracy: 0.8497 - val_loss: 0.5559 - val_accuracy: 0.8681
Epoch 69/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5673 - accuracy: 0.8456 - val_loss: 0.5489 - val_accuracy: 0.8681
Epoch 70/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5554 - accuracy: 0.8484 - val_loss: 0.5428 - val_accuracy: 0.8681
Epoch 71/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5444 - accuracy: 0.8456 - val_loss: 0.5371 - val_accuracy: 0.8681
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5420 - accuracy: 0.8566 - val_loss: 0.5309 - val_accuracy: 0.8681
Epoch 73/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5319 - accuracy: 0.8538 - val_loss: 0.5258 - val_accuracy: 0.8681
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5297 - accuracy: 0.8511 - val_loss: 0.5200 - val_accuracy: 0.8681
Epoch 75/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5247 - accuracy: 0.8497 - val_loss: 0.5147 - val_accuracy: 0.8681
Epoch 76/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5210 - accuracy: 0.8525 - val_loss: 0.5103 - val_accuracy: 0.8681
Epoch 77/100
2/2 [==============================] - 0s 75ms/step - loss: 0.5082 - accuracy: 0.8538 - val_loss: 0.5055 - val_accuracy: 0.8681
Epoch 78/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5065 - accuracy: 0.8470 - val_loss: 0.5011 - val_accuracy: 0.8681
Epoch 79/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5001 - accuracy: 0.8497 - val_loss: 0.4970 - val_accuracy: 0.8681
Epoch 80/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4913 - accuracy: 0.8538 - val_loss: 0.4928 - val_accuracy: 0.8681
Epoch 81/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4912 - accuracy: 0.8593 - val_loss: 0.4890 - val_accuracy: 0.8681
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4859 - accuracy: 0.8579 - val_loss: 0.4839 - val_accuracy: 0.8681
Epoch 83/100
2/2 [==============================] - 0s 46ms/step - loss: 0.4850 - accuracy: 0.8525 - val_loss: 0.4796 - val_accuracy: 0.8681
Epoch 84/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4745 - accuracy: 0.8552 - val_loss: 0.4755 - val_accuracy: 0.8681
Epoch 85/100
2/2 [==============================] - 0s 44ms/step - loss: 0.4717 - accuracy: 0.8552 - val_loss: 0.4723 - val_accuracy: 0.8681
Epoch 86/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4707 - accuracy: 0.8511 - val_loss: 0.4683 - val_accuracy: 0.8681
Epoch 87/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4670 - accuracy: 0.8511 - val_loss: 0.4642 - val_accuracy: 0.8681
Epoch 88/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4668 - accuracy: 0.8538 - val_loss: 0.4607 - val_accuracy: 0.8681
Epoch 89/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4563 - accuracy: 0.8525 - val_loss: 0.4574 - val_accuracy: 0.8681
Epoch 90/100
2/2 [==============================] - 0s 49ms/step - loss: 0.4670 - accuracy: 0.8497 - val_loss: 0.4549 - val_accuracy: 0.8681
Epoch 91/100
2/2 [==============================] - 0s 48ms/step - loss: 0.4552 - accuracy: 0.8484 - val_loss: 0.4519 - val_accuracy: 0.8681
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4506 - accuracy: 0.8511 - val_loss: 0.4491 - val_accuracy: 0.8681
Epoch 93/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4518 - accuracy: 0.8538 - val_loss: 0.4468 - val_accuracy: 0.8681
Epoch 94/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4427 - accuracy: 0.8525 - val_loss: 0.4446 - val_accuracy: 0.8626
Epoch 95/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4429 - accuracy: 0.8470 - val_loss: 0.4423 - val_accuracy: 0.8626
Epoch 96/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4373 - accuracy: 0.8497 - val_loss: 0.4392 - val_accuracy: 0.8681
Epoch 97/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4349 - accuracy: 0.8538 - val_loss: 0.4380 - val_accuracy: 0.8626
Epoch 98/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4327 - accuracy: 0.8497 - val_loss: 0.4373 - val_accuracy: 0.8626
Epoch 99/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4371 - accuracy: 0.8538 - val_loss: 0.4346 - val_accuracy: 0.8626
Epoch 100/100
2/2 [==============================] - 0s 46ms/step - loss: 0.4321 - accuracy: 0.8593 - val_loss: 0.4322 - val_accuracy: 0.8626
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Experiment number: 2
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 1, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 115ms/step - loss: 1.4071 - accuracy: 0.1601 - val_loss: 1.3684 - val_accuracy: 0.2022
Epoch 2/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4082 - accuracy: 0.1683 - val_loss: 1.3681 - val_accuracy: 0.2022
Epoch 3/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3951 - accuracy: 0.1915 - val_loss: 1.3677 - val_accuracy: 0.2022
Epoch 4/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3917 - accuracy: 0.1614 - val_loss: 1.3672 - val_accuracy: 0.2022
Epoch 5/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4097 - accuracy: 0.1956 - val_loss: 1.3666 - val_accuracy: 0.2077
Epoch 6/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4046 - accuracy: 0.1710 - val_loss: 1.3660 - val_accuracy: 0.2077
Epoch 7/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4110 - accuracy: 0.1806 - val_loss: 1.3654 - val_accuracy: 0.2077
Epoch 8/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3997 - accuracy: 0.1874 - val_loss: 1.3647 - val_accuracy: 0.2077
Epoch 9/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4026 - accuracy: 0.1888 - val_loss: 1.3641 - val_accuracy: 0.2077
Epoch 10/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4039 - accuracy: 0.1696 - val_loss: 1.3634 - val_accuracy: 0.2077
Epoch 11/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4064 - accuracy: 0.1860 - val_loss: 1.3627 - val_accuracy: 0.2077
Epoch 12/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4002 - accuracy: 0.1902 - val_loss: 1.3620 - val_accuracy: 0.2077
Epoch 13/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3993 - accuracy: 0.1956 - val_loss: 1.3613 - val_accuracy: 0.2131
Epoch 14/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3981 - accuracy: 0.2038 - val_loss: 1.3606 - val_accuracy: 0.2131
Epoch 15/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3990 - accuracy: 0.1860 - val_loss: 1.3599 - val_accuracy: 0.2131
Epoch 16/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3913 - accuracy: 0.2025 - val_loss: 1.3592 - val_accuracy: 0.2186
Epoch 17/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3834 - accuracy: 0.2025 - val_loss: 1.3585 - val_accuracy: 0.2186
Epoch 18/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4066 - accuracy: 0.1778 - val_loss: 1.3578 - val_accuracy: 0.2186
Epoch 19/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3916 - accuracy: 0.2011 - val_loss: 1.3571 - val_accuracy: 0.2186
Epoch 20/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3891 - accuracy: 0.1874 - val_loss: 1.3564 - val_accuracy: 0.2186
Epoch 21/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3807 - accuracy: 0.1833 - val_loss: 1.3557 - val_accuracy: 0.2186
Epoch 22/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3956 - accuracy: 0.1915 - val_loss: 1.3550 - val_accuracy: 0.2186
Epoch 23/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3981 - accuracy: 0.1860 - val_loss: 1.3543 - val_accuracy: 0.2186
Epoch 24/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3796 - accuracy: 0.1956 - val_loss: 1.3536 - val_accuracy: 0.2186
Epoch 25/100
3/3 [==============================] - 0s 23ms/step - loss: 1.3849 - accuracy: 0.1874 - val_loss: 1.3529 - val_accuracy: 0.2240
Epoch 26/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3819 - accuracy: 0.2025 - val_loss: 1.3522 - val_accuracy: 0.2240
Epoch 27/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3866 - accuracy: 0.1888 - val_loss: 1.3515 - val_accuracy: 0.2240
Epoch 28/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3805 - accuracy: 0.1984 - val_loss: 1.3508 - val_accuracy: 0.2240
Epoch 29/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3792 - accuracy: 0.1929 - val_loss: 1.3501 - val_accuracy: 0.2240
Epoch 30/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3801 - accuracy: 0.1929 - val_loss: 1.3494 - val_accuracy: 0.2240
Epoch 31/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3893 - accuracy: 0.1902 - val_loss: 1.3487 - val_accuracy: 0.2240
Epoch 32/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3768 - accuracy: 0.2079 - val_loss: 1.3480 - val_accuracy: 0.2240
Epoch 33/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3987 - accuracy: 0.1984 - val_loss: 1.3473 - val_accuracy: 0.2240
Epoch 34/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3844 - accuracy: 0.1778 - val_loss: 1.3466 - val_accuracy: 0.2240
Epoch 35/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3748 - accuracy: 0.1997 - val_loss: 1.3459 - val_accuracy: 0.2240
Epoch 36/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4036 - accuracy: 0.1902 - val_loss: 1.3452 - val_accuracy: 0.2240
Epoch 37/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3860 - accuracy: 0.1929 - val_loss: 1.3445 - val_accuracy: 0.2240
Epoch 38/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3717 - accuracy: 0.2161 - val_loss: 1.3438 - val_accuracy: 0.2295
Epoch 39/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3832 - accuracy: 0.1833 - val_loss: 1.3431 - val_accuracy: 0.2295
Epoch 40/100
3/3 [==============================] - 0s 23ms/step - loss: 1.3852 - accuracy: 0.1860 - val_loss: 1.3424 - val_accuracy: 0.2295
Epoch 41/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3830 - accuracy: 0.1970 - val_loss: 1.3417 - val_accuracy: 0.2295
Epoch 42/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3795 - accuracy: 0.1970 - val_loss: 1.3410 - val_accuracy: 0.2295
Epoch 43/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3749 - accuracy: 0.1997 - val_loss: 1.3404 - val_accuracy: 0.2295
Epoch 44/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3689 - accuracy: 0.2093 - val_loss: 1.3397 - val_accuracy: 0.2295
Epoch 45/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3772 - accuracy: 0.2175 - val_loss: 1.3390 - val_accuracy: 0.2295
Epoch 46/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3824 - accuracy: 0.1902 - val_loss: 1.3383 - val_accuracy: 0.2295
Epoch 47/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3806 - accuracy: 0.1819 - val_loss: 1.3376 - val_accuracy: 0.2295
Epoch 48/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3707 - accuracy: 0.2257 - val_loss: 1.3369 - val_accuracy: 0.2295
Epoch 49/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3766 - accuracy: 0.1984 - val_loss: 1.3362 - val_accuracy: 0.2295
Epoch 50/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3653 - accuracy: 0.1970 - val_loss: 1.3355 - val_accuracy: 0.2295
Epoch 51/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3735 - accuracy: 0.2038 - val_loss: 1.3348 - val_accuracy: 0.2295
Epoch 52/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3624 - accuracy: 0.2093 - val_loss: 1.3342 - val_accuracy: 0.2295
Epoch 53/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3738 - accuracy: 0.2120 - val_loss: 1.3335 - val_accuracy: 0.2295
Epoch 54/100
3/3 [==============================] - 0s 23ms/step - loss: 1.3584 - accuracy: 0.1970 - val_loss: 1.3328 - val_accuracy: 0.2295
Epoch 55/100
3/3 [==============================] - 0s 23ms/step - loss: 1.3765 - accuracy: 0.1997 - val_loss: 1.3321 - val_accuracy: 0.2295
Epoch 56/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3801 - accuracy: 0.2202 - val_loss: 1.3314 - val_accuracy: 0.2295
Epoch 57/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3670 - accuracy: 0.2134 - val_loss: 1.3307 - val_accuracy: 0.2295
Epoch 58/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3565 - accuracy: 0.2353 - val_loss: 1.3301 - val_accuracy: 0.2295
Epoch 59/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3774 - accuracy: 0.2079 - val_loss: 1.3294 - val_accuracy: 0.2295
Epoch 60/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3688 - accuracy: 0.1997 - val_loss: 1.3287 - val_accuracy: 0.2295
Epoch 61/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3676 - accuracy: 0.2175 - val_loss: 1.3280 - val_accuracy: 0.2295
Epoch 62/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3734 - accuracy: 0.2038 - val_loss: 1.3273 - val_accuracy: 0.2295
Epoch 63/100
3/3 [==============================] - 0s 24ms/step - loss: 1.3479 - accuracy: 0.2257 - val_loss: 1.3266 - val_accuracy: 0.2295
Epoch 64/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3665 - accuracy: 0.2257 - val_loss: 1.3260 - val_accuracy: 0.2295
Epoch 65/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3460 - accuracy: 0.2244 - val_loss: 1.3253 - val_accuracy: 0.2295
Epoch 66/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3566 - accuracy: 0.2257 - val_loss: 1.3246 - val_accuracy: 0.2295
Epoch 67/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3608 - accuracy: 0.2312 - val_loss: 1.3239 - val_accuracy: 0.2295
Epoch 68/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3593 - accuracy: 0.2038 - val_loss: 1.3233 - val_accuracy: 0.2295
Epoch 69/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3548 - accuracy: 0.2189 - val_loss: 1.3226 - val_accuracy: 0.2295
Epoch 70/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3621 - accuracy: 0.2298 - val_loss: 1.3219 - val_accuracy: 0.2295
Epoch 71/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3668 - accuracy: 0.2175 - val_loss: 1.3212 - val_accuracy: 0.2350
Epoch 72/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3657 - accuracy: 0.2052 - val_loss: 1.3206 - val_accuracy: 0.2350
Epoch 73/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3480 - accuracy: 0.2339 - val_loss: 1.3199 - val_accuracy: 0.2350
Epoch 74/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3651 - accuracy: 0.2216 - val_loss: 1.3192 - val_accuracy: 0.2350
Epoch 75/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3652 - accuracy: 0.2120 - val_loss: 1.3185 - val_accuracy: 0.2350
Epoch 76/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3589 - accuracy: 0.2134 - val_loss: 1.3179 - val_accuracy: 0.2350
Epoch 77/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3618 - accuracy: 0.2353 - val_loss: 1.3172 - val_accuracy: 0.2350
Epoch 78/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3496 - accuracy: 0.2230 - val_loss: 1.3165 - val_accuracy: 0.2350
Epoch 79/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3543 - accuracy: 0.2462 - val_loss: 1.3159 - val_accuracy: 0.2350
Epoch 80/100
3/3 [==============================] - 0s 23ms/step - loss: 1.3462 - accuracy: 0.2326 - val_loss: 1.3152 - val_accuracy: 0.2350
Epoch 81/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3520 - accuracy: 0.2271 - val_loss: 1.3145 - val_accuracy: 0.2404
Epoch 82/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3424 - accuracy: 0.2285 - val_loss: 1.3139 - val_accuracy: 0.2459
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3666 - accuracy: 0.1929 - val_loss: 1.3132 - val_accuracy: 0.2459
Epoch 84/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3407 - accuracy: 0.2230 - val_loss: 1.3125 - val_accuracy: 0.2459
Epoch 85/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3385 - accuracy: 0.2244 - val_loss: 1.3119 - val_accuracy: 0.2514
Epoch 86/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3355 - accuracy: 0.2449 - val_loss: 1.3112 - val_accuracy: 0.2514
Epoch 87/100
3/3 [==============================] - 0s 14ms/step - loss: 1.3558 - accuracy: 0.2326 - val_loss: 1.3105 - val_accuracy: 0.2568
Epoch 88/100
3/3 [==============================] - 0s 16ms/step - loss: 1.3474 - accuracy: 0.2298 - val_loss: 1.3099 - val_accuracy: 0.2623
Epoch 89/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3533 - accuracy: 0.2230 - val_loss: 1.3092 - val_accuracy: 0.2623
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3292 - accuracy: 0.2353 - val_loss: 1.3086 - val_accuracy: 0.2623
Epoch 91/100
3/3 [==============================] - 0s 16ms/step - loss: 1.3344 - accuracy: 0.2244 - val_loss: 1.3079 - val_accuracy: 0.2623
Epoch 92/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3494 - accuracy: 0.2230 - val_loss: 1.3072 - val_accuracy: 0.2623
Epoch 93/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3381 - accuracy: 0.2298 - val_loss: 1.3066 - val_accuracy: 0.2623
Epoch 94/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3433 - accuracy: 0.2257 - val_loss: 1.3059 - val_accuracy: 0.2623
Epoch 95/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3358 - accuracy: 0.2285 - val_loss: 1.3053 - val_accuracy: 0.2623
Epoch 96/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3353 - accuracy: 0.2394 - val_loss: 1.3046 - val_accuracy: 0.2623
Epoch 97/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3505 - accuracy: 0.2380 - val_loss: 1.3039 - val_accuracy: 0.2623
Epoch 98/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3485 - accuracy: 0.2312 - val_loss: 1.3033 - val_accuracy: 0.2623
Epoch 99/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3455 - accuracy: 0.2462 - val_loss: 1.3026 - val_accuracy: 0.2623
Epoch 100/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3430 - accuracy: 0.2161 - val_loss: 1.3020 - val_accuracy: 0.2732
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 1, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 110ms/step - loss: 1.2202 - accuracy: 0.4118 - val_loss: 1.2247 - val_accuracy: 0.4372
Epoch 2/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2196 - accuracy: 0.4063 - val_loss: 1.2245 - val_accuracy: 0.4372
Epoch 3/100
3/3 [==============================] - 0s 22ms/step - loss: 1.2172 - accuracy: 0.4104 - val_loss: 1.2242 - val_accuracy: 0.4372
Epoch 4/100
3/3 [==============================] - 0s 22ms/step - loss: 1.2301 - accuracy: 0.4172 - val_loss: 1.2239 - val_accuracy: 0.4372
Epoch 5/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2180 - accuracy: 0.4159 - val_loss: 1.2236 - val_accuracy: 0.4372
Epoch 6/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2262 - accuracy: 0.4172 - val_loss: 1.2232 - val_accuracy: 0.4372
Epoch 7/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2145 - accuracy: 0.4145 - val_loss: 1.2228 - val_accuracy: 0.4426
Epoch 8/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2295 - accuracy: 0.4022 - val_loss: 1.2224 - val_accuracy: 0.4426
Epoch 9/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2080 - accuracy: 0.4186 - val_loss: 1.2219 - val_accuracy: 0.4481
Epoch 10/100
3/3 [==============================] - 0s 13ms/step - loss: 1.2178 - accuracy: 0.4227 - val_loss: 1.2215 - val_accuracy: 0.4481
Epoch 11/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2324 - accuracy: 0.4200 - val_loss: 1.2210 - val_accuracy: 0.4481
Epoch 12/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2137 - accuracy: 0.4282 - val_loss: 1.2206 - val_accuracy: 0.4481
Epoch 13/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2217 - accuracy: 0.4295 - val_loss: 1.2201 - val_accuracy: 0.4481
Epoch 14/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2004 - accuracy: 0.4432 - val_loss: 1.2197 - val_accuracy: 0.4481
Epoch 15/100
3/3 [==============================] - 0s 23ms/step - loss: 1.2105 - accuracy: 0.4213 - val_loss: 1.2192 - val_accuracy: 0.4481
Epoch 16/100
3/3 [==============================] - 0s 16ms/step - loss: 1.2070 - accuracy: 0.4378 - val_loss: 1.2188 - val_accuracy: 0.4481
Epoch 17/100
3/3 [==============================] - 0s 18ms/step - loss: 1.2261 - accuracy: 0.4172 - val_loss: 1.2183 - val_accuracy: 0.4481
Epoch 18/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2221 - accuracy: 0.4200 - val_loss: 1.2179 - val_accuracy: 0.4481
Epoch 19/100
3/3 [==============================] - 0s 19ms/step - loss: 1.2117 - accuracy: 0.4200 - val_loss: 1.2174 - val_accuracy: 0.4481
Epoch 20/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2118 - accuracy: 0.4378 - val_loss: 1.2170 - val_accuracy: 0.4481
Epoch 21/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2299 - accuracy: 0.4090 - val_loss: 1.2165 - val_accuracy: 0.4481
Epoch 22/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2160 - accuracy: 0.4254 - val_loss: 1.2160 - val_accuracy: 0.4481
Epoch 23/100
3/3 [==============================] - 0s 19ms/step - loss: 1.2066 - accuracy: 0.4432 - val_loss: 1.2156 - val_accuracy: 0.4481
Epoch 24/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2226 - accuracy: 0.4172 - val_loss: 1.2151 - val_accuracy: 0.4481
Epoch 25/100
3/3 [==============================] - 0s 22ms/step - loss: 1.2078 - accuracy: 0.4049 - val_loss: 1.2147 - val_accuracy: 0.4481
Epoch 26/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2242 - accuracy: 0.4309 - val_loss: 1.2142 - val_accuracy: 0.4481
Epoch 27/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2105 - accuracy: 0.4405 - val_loss: 1.2138 - val_accuracy: 0.4481
Epoch 28/100
3/3 [==============================] - 0s 22ms/step - loss: 1.2374 - accuracy: 0.4036 - val_loss: 1.2133 - val_accuracy: 0.4536
Epoch 29/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2106 - accuracy: 0.4213 - val_loss: 1.2129 - val_accuracy: 0.4536
Epoch 30/100
3/3 [==============================] - 0s 19ms/step - loss: 1.2120 - accuracy: 0.4254 - val_loss: 1.2124 - val_accuracy: 0.4536
Epoch 31/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2143 - accuracy: 0.4282 - val_loss: 1.2119 - val_accuracy: 0.4536
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2167 - accuracy: 0.4282 - val_loss: 1.2115 - val_accuracy: 0.4536
Epoch 33/100
3/3 [==============================] - 0s 18ms/step - loss: 1.2115 - accuracy: 0.4282 - val_loss: 1.2110 - val_accuracy: 0.4536
Epoch 34/100
3/3 [==============================] - 0s 26ms/step - loss: 1.2009 - accuracy: 0.4432 - val_loss: 1.2106 - val_accuracy: 0.4536
Epoch 35/100
3/3 [==============================] - 0s 17ms/step - loss: 1.2047 - accuracy: 0.4337 - val_loss: 1.2101 - val_accuracy: 0.4536
Epoch 36/100
3/3 [==============================] - 0s 17ms/step - loss: 1.2126 - accuracy: 0.4337 - val_loss: 1.2097 - val_accuracy: 0.4536
Epoch 37/100
3/3 [==============================] - 0s 40ms/step - loss: 1.2088 - accuracy: 0.4446 - val_loss: 1.2092 - val_accuracy: 0.4536
Epoch 38/100
3/3 [==============================] - 0s 22ms/step - loss: 1.2129 - accuracy: 0.4254 - val_loss: 1.2088 - val_accuracy: 0.4536
Epoch 39/100
3/3 [==============================] - 0s 22ms/step - loss: 1.2022 - accuracy: 0.4295 - val_loss: 1.2083 - val_accuracy: 0.4536
Epoch 40/100
3/3 [==============================] - 0s 18ms/step - loss: 1.2241 - accuracy: 0.4077 - val_loss: 1.2079 - val_accuracy: 0.4536
Epoch 41/100
3/3 [==============================] - 0s 15ms/step - loss: 1.2064 - accuracy: 0.4254 - val_loss: 1.2074 - val_accuracy: 0.4536
Epoch 42/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1889 - accuracy: 0.4637 - val_loss: 1.2070 - val_accuracy: 0.4536
Epoch 43/100
3/3 [==============================] - 0s 19ms/step - loss: 1.2047 - accuracy: 0.4419 - val_loss: 1.2066 - val_accuracy: 0.4590
Epoch 44/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1917 - accuracy: 0.4378 - val_loss: 1.2061 - val_accuracy: 0.4590
Epoch 45/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2023 - accuracy: 0.4555 - val_loss: 1.2057 - val_accuracy: 0.4645
Epoch 46/100
3/3 [==============================] - 0s 19ms/step - loss: 1.2169 - accuracy: 0.3995 - val_loss: 1.2052 - val_accuracy: 0.4754
Epoch 47/100
3/3 [==============================] - 0s 25ms/step - loss: 1.1970 - accuracy: 0.4364 - val_loss: 1.2048 - val_accuracy: 0.4754
Epoch 48/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2177 - accuracy: 0.4309 - val_loss: 1.2044 - val_accuracy: 0.4754
Epoch 49/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2026 - accuracy: 0.4446 - val_loss: 1.2039 - val_accuracy: 0.4754
Epoch 50/100
3/3 [==============================] - 0s 25ms/step - loss: 1.2031 - accuracy: 0.4446 - val_loss: 1.2035 - val_accuracy: 0.4754
Epoch 51/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2065 - accuracy: 0.4077 - val_loss: 1.2030 - val_accuracy: 0.4754
Epoch 52/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1869 - accuracy: 0.4528 - val_loss: 1.2026 - val_accuracy: 0.4754
Epoch 53/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1950 - accuracy: 0.4295 - val_loss: 1.2021 - val_accuracy: 0.4754
Epoch 54/100
3/3 [==============================] - 0s 16ms/step - loss: 1.2015 - accuracy: 0.4460 - val_loss: 1.2017 - val_accuracy: 0.4809
Epoch 55/100
3/3 [==============================] - 0s 18ms/step - loss: 1.1942 - accuracy: 0.4501 - val_loss: 1.2013 - val_accuracy: 0.4809
Epoch 56/100
3/3 [==============================] - 0s 25ms/step - loss: 1.2034 - accuracy: 0.4323 - val_loss: 1.2008 - val_accuracy: 0.4809
Epoch 57/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2089 - accuracy: 0.4583 - val_loss: 1.2004 - val_accuracy: 0.4809
Epoch 58/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1976 - accuracy: 0.4528 - val_loss: 1.2000 - val_accuracy: 0.4809
Epoch 59/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1999 - accuracy: 0.4774 - val_loss: 1.1995 - val_accuracy: 0.4809
Epoch 60/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1819 - accuracy: 0.4720 - val_loss: 1.1991 - val_accuracy: 0.4809
Epoch 61/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1906 - accuracy: 0.4596 - val_loss: 1.1986 - val_accuracy: 0.4863
Epoch 62/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1889 - accuracy: 0.4624 - val_loss: 1.1982 - val_accuracy: 0.4863
Epoch 63/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1830 - accuracy: 0.4747 - val_loss: 1.1978 - val_accuracy: 0.4863
Epoch 64/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1924 - accuracy: 0.4706 - val_loss: 1.1973 - val_accuracy: 0.4863
Epoch 65/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1976 - accuracy: 0.4487 - val_loss: 1.1969 - val_accuracy: 0.4918
Epoch 66/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2047 - accuracy: 0.4542 - val_loss: 1.1965 - val_accuracy: 0.4918
Epoch 67/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2051 - accuracy: 0.4542 - val_loss: 1.1960 - val_accuracy: 0.4918
Epoch 68/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1966 - accuracy: 0.4460 - val_loss: 1.1956 - val_accuracy: 0.4973
Epoch 69/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1914 - accuracy: 0.4473 - val_loss: 1.1952 - val_accuracy: 0.4973
Epoch 70/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1917 - accuracy: 0.4405 - val_loss: 1.1947 - val_accuracy: 0.4973
Epoch 71/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1779 - accuracy: 0.4979 - val_loss: 1.1943 - val_accuracy: 0.4973
Epoch 72/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1889 - accuracy: 0.4624 - val_loss: 1.1939 - val_accuracy: 0.5027
Epoch 73/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1966 - accuracy: 0.4569 - val_loss: 1.1934 - val_accuracy: 0.5027
Epoch 74/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1868 - accuracy: 0.4637 - val_loss: 1.1930 - val_accuracy: 0.5027
Epoch 75/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1921 - accuracy: 0.4665 - val_loss: 1.1926 - val_accuracy: 0.5027
Epoch 76/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1957 - accuracy: 0.4514 - val_loss: 1.1921 - val_accuracy: 0.5027
Epoch 77/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1727 - accuracy: 0.4747 - val_loss: 1.1917 - val_accuracy: 0.5027
Epoch 78/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2008 - accuracy: 0.4815 - val_loss: 1.1913 - val_accuracy: 0.5027
Epoch 79/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1796 - accuracy: 0.4761 - val_loss: 1.1908 - val_accuracy: 0.5027
Epoch 80/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1894 - accuracy: 0.4706 - val_loss: 1.1904 - val_accuracy: 0.5027
Epoch 81/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1907 - accuracy: 0.4911 - val_loss: 1.1900 - val_accuracy: 0.5027
Epoch 82/100
3/3 [==============================] - 0s 18ms/step - loss: 1.1785 - accuracy: 0.4788 - val_loss: 1.1895 - val_accuracy: 0.5027
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2014 - accuracy: 0.4501 - val_loss: 1.1891 - val_accuracy: 0.5027
Epoch 84/100
3/3 [==============================] - 0s 17ms/step - loss: 1.1743 - accuracy: 0.5048 - val_loss: 1.1887 - val_accuracy: 0.5027
Epoch 85/100
3/3 [==============================] - 0s 15ms/step - loss: 1.1903 - accuracy: 0.4514 - val_loss: 1.1883 - val_accuracy: 0.5027
Epoch 86/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1853 - accuracy: 0.4610 - val_loss: 1.1878 - val_accuracy: 0.5027
Epoch 87/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1999 - accuracy: 0.4542 - val_loss: 1.1874 - val_accuracy: 0.5082
Epoch 88/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1995 - accuracy: 0.4624 - val_loss: 1.1870 - val_accuracy: 0.5082
Epoch 89/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1897 - accuracy: 0.4802 - val_loss: 1.1865 - val_accuracy: 0.5082
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1768 - accuracy: 0.4979 - val_loss: 1.1861 - val_accuracy: 0.5082
Epoch 91/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1763 - accuracy: 0.4843 - val_loss: 1.1857 - val_accuracy: 0.5082
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1684 - accuracy: 0.4938 - val_loss: 1.1853 - val_accuracy: 0.5082
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1871 - accuracy: 0.4747 - val_loss: 1.1848 - val_accuracy: 0.5082
Epoch 94/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1738 - accuracy: 0.4651 - val_loss: 1.1844 - val_accuracy: 0.5082
Epoch 95/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1839 - accuracy: 0.4651 - val_loss: 1.1840 - val_accuracy: 0.5082
Epoch 96/100
3/3 [==============================] - 0s 17ms/step - loss: 1.1905 - accuracy: 0.4637 - val_loss: 1.1836 - val_accuracy: 0.5082
Epoch 97/100
3/3 [==============================] - 0s 14ms/step - loss: 1.1849 - accuracy: 0.4679 - val_loss: 1.1831 - val_accuracy: 0.5082
Epoch 98/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1704 - accuracy: 0.4870 - val_loss: 1.1827 - val_accuracy: 0.5082
Epoch 99/100
3/3 [==============================] - 0s 17ms/step - loss: 1.1770 - accuracy: 0.4747 - val_loss: 1.1823 - val_accuracy: 0.5082
Epoch 100/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1706 - accuracy: 0.4747 - val_loss: 1.1819 - val_accuracy: 0.5082
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 1, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 115ms/step - loss: 1.4867 - accuracy: 0.2066 - val_loss: 1.4664 - val_accuracy: 0.2186
Epoch 2/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4857 - accuracy: 0.2066 - val_loss: 1.4661 - val_accuracy: 0.2186
Epoch 3/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4712 - accuracy: 0.2107 - val_loss: 1.4657 - val_accuracy: 0.2186
Epoch 4/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4671 - accuracy: 0.2161 - val_loss: 1.4653 - val_accuracy: 0.2186
Epoch 5/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4714 - accuracy: 0.2230 - val_loss: 1.4648 - val_accuracy: 0.2186
Epoch 6/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4777 - accuracy: 0.2134 - val_loss: 1.4642 - val_accuracy: 0.2186
Epoch 7/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4709 - accuracy: 0.2038 - val_loss: 1.4637 - val_accuracy: 0.2186
Epoch 8/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4637 - accuracy: 0.2161 - val_loss: 1.4631 - val_accuracy: 0.2186
Epoch 9/100
3/3 [==============================] - 0s 18ms/step - loss: 1.4782 - accuracy: 0.2134 - val_loss: 1.4625 - val_accuracy: 0.2186
Epoch 10/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4733 - accuracy: 0.2189 - val_loss: 1.4618 - val_accuracy: 0.2186
Epoch 11/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4596 - accuracy: 0.2120 - val_loss: 1.4612 - val_accuracy: 0.2186
Epoch 12/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4708 - accuracy: 0.2066 - val_loss: 1.4606 - val_accuracy: 0.2186
Epoch 13/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4750 - accuracy: 0.2093 - val_loss: 1.4599 - val_accuracy: 0.2186
Epoch 14/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4705 - accuracy: 0.2161 - val_loss: 1.4593 - val_accuracy: 0.2186
Epoch 15/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4857 - accuracy: 0.2216 - val_loss: 1.4586 - val_accuracy: 0.2186
Epoch 16/100
3/3 [==============================] - 0s 28ms/step - loss: 1.4765 - accuracy: 0.1806 - val_loss: 1.4580 - val_accuracy: 0.2186
Epoch 17/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4859 - accuracy: 0.2107 - val_loss: 1.4573 - val_accuracy: 0.2186
Epoch 18/100
3/3 [==============================] - 0s 31ms/step - loss: 1.4712 - accuracy: 0.2134 - val_loss: 1.4567 - val_accuracy: 0.2186
Epoch 19/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4794 - accuracy: 0.2011 - val_loss: 1.4560 - val_accuracy: 0.2186
Epoch 20/100
3/3 [==============================] - 0s 14ms/step - loss: 1.4612 - accuracy: 0.2093 - val_loss: 1.4554 - val_accuracy: 0.2186
Epoch 21/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4818 - accuracy: 0.2038 - val_loss: 1.4547 - val_accuracy: 0.2186
Epoch 22/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4869 - accuracy: 0.2079 - val_loss: 1.4541 - val_accuracy: 0.2186
Epoch 23/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4596 - accuracy: 0.2244 - val_loss: 1.4534 - val_accuracy: 0.2186
Epoch 24/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4617 - accuracy: 0.2312 - val_loss: 1.4528 - val_accuracy: 0.2186
Epoch 25/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4579 - accuracy: 0.2257 - val_loss: 1.4522 - val_accuracy: 0.2186
Epoch 26/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4721 - accuracy: 0.2161 - val_loss: 1.4515 - val_accuracy: 0.2186
Epoch 27/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4672 - accuracy: 0.2148 - val_loss: 1.4509 - val_accuracy: 0.2186
Epoch 28/100
3/3 [==============================] - 0s 18ms/step - loss: 1.4701 - accuracy: 0.2175 - val_loss: 1.4502 - val_accuracy: 0.2186
Epoch 29/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4548 - accuracy: 0.1997 - val_loss: 1.4496 - val_accuracy: 0.2186
Epoch 30/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4533 - accuracy: 0.2148 - val_loss: 1.4489 - val_accuracy: 0.2186
Epoch 31/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4515 - accuracy: 0.2216 - val_loss: 1.4483 - val_accuracy: 0.2186
Epoch 32/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4416 - accuracy: 0.2202 - val_loss: 1.4476 - val_accuracy: 0.2186
Epoch 33/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4523 - accuracy: 0.2271 - val_loss: 1.4470 - val_accuracy: 0.2186
Epoch 34/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4525 - accuracy: 0.2093 - val_loss: 1.4464 - val_accuracy: 0.2186
Epoch 35/100
3/3 [==============================] - 0s 18ms/step - loss: 1.4707 - accuracy: 0.2326 - val_loss: 1.4457 - val_accuracy: 0.2186
Epoch 36/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4496 - accuracy: 0.2257 - val_loss: 1.4451 - val_accuracy: 0.2186
Epoch 37/100
3/3 [==============================] - 0s 14ms/step - loss: 1.4554 - accuracy: 0.2312 - val_loss: 1.4445 - val_accuracy: 0.2186
Epoch 38/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4675 - accuracy: 0.2066 - val_loss: 1.4438 - val_accuracy: 0.2186
Epoch 39/100
3/3 [==============================] - 0s 26ms/step - loss: 1.4536 - accuracy: 0.2244 - val_loss: 1.4432 - val_accuracy: 0.2186
Epoch 40/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4457 - accuracy: 0.2339 - val_loss: 1.4425 - val_accuracy: 0.2186
Epoch 41/100
3/3 [==============================] - 0s 18ms/step - loss: 1.4614 - accuracy: 0.2285 - val_loss: 1.4419 - val_accuracy: 0.2186
Epoch 42/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4468 - accuracy: 0.2230 - val_loss: 1.4413 - val_accuracy: 0.2186
Epoch 43/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4601 - accuracy: 0.2257 - val_loss: 1.4406 - val_accuracy: 0.2186
Epoch 44/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4601 - accuracy: 0.2175 - val_loss: 1.4400 - val_accuracy: 0.2186
Epoch 45/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4594 - accuracy: 0.2312 - val_loss: 1.4393 - val_accuracy: 0.2186
Epoch 46/100
3/3 [==============================] - 0s 29ms/step - loss: 1.4546 - accuracy: 0.2326 - val_loss: 1.4387 - val_accuracy: 0.2186
Epoch 47/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4412 - accuracy: 0.2271 - val_loss: 1.4381 - val_accuracy: 0.2186
Epoch 48/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4353 - accuracy: 0.2216 - val_loss: 1.4374 - val_accuracy: 0.2186
Epoch 49/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4620 - accuracy: 0.2271 - val_loss: 1.4368 - val_accuracy: 0.2186
Epoch 50/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4705 - accuracy: 0.2107 - val_loss: 1.4362 - val_accuracy: 0.2186
Epoch 51/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4541 - accuracy: 0.2244 - val_loss: 1.4355 - val_accuracy: 0.2186
Epoch 52/100
3/3 [==============================] - 0s 18ms/step - loss: 1.4340 - accuracy: 0.2285 - val_loss: 1.4349 - val_accuracy: 0.2240
Epoch 53/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4489 - accuracy: 0.2285 - val_loss: 1.4343 - val_accuracy: 0.2240
Epoch 54/100
3/3 [==============================] - 0s 18ms/step - loss: 1.4461 - accuracy: 0.2394 - val_loss: 1.4336 - val_accuracy: 0.2240
Epoch 55/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4326 - accuracy: 0.2408 - val_loss: 1.4330 - val_accuracy: 0.2240
Epoch 56/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4503 - accuracy: 0.2148 - val_loss: 1.4324 - val_accuracy: 0.2240
Epoch 57/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4361 - accuracy: 0.2503 - val_loss: 1.4317 - val_accuracy: 0.2240
Epoch 58/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4475 - accuracy: 0.2175 - val_loss: 1.4311 - val_accuracy: 0.2240
Epoch 59/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4584 - accuracy: 0.2244 - val_loss: 1.4305 - val_accuracy: 0.2240
Epoch 60/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4298 - accuracy: 0.2257 - val_loss: 1.4299 - val_accuracy: 0.2240
Epoch 61/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4546 - accuracy: 0.2230 - val_loss: 1.4292 - val_accuracy: 0.2240
Epoch 62/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4386 - accuracy: 0.2353 - val_loss: 1.4286 - val_accuracy: 0.2240
Epoch 63/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4475 - accuracy: 0.2394 - val_loss: 1.4280 - val_accuracy: 0.2240
Epoch 64/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4495 - accuracy: 0.2230 - val_loss: 1.4273 - val_accuracy: 0.2240
Epoch 65/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4568 - accuracy: 0.2230 - val_loss: 1.4267 - val_accuracy: 0.2240
Epoch 66/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4383 - accuracy: 0.2339 - val_loss: 1.4261 - val_accuracy: 0.2240
Epoch 67/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4397 - accuracy: 0.2298 - val_loss: 1.4255 - val_accuracy: 0.2240
Epoch 68/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4398 - accuracy: 0.2367 - val_loss: 1.4248 - val_accuracy: 0.2240
Epoch 69/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4350 - accuracy: 0.2312 - val_loss: 1.4242 - val_accuracy: 0.2240
Epoch 70/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4367 - accuracy: 0.2257 - val_loss: 1.4236 - val_accuracy: 0.2240
Epoch 71/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4417 - accuracy: 0.2326 - val_loss: 1.4230 - val_accuracy: 0.2240
Epoch 72/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4451 - accuracy: 0.2326 - val_loss: 1.4223 - val_accuracy: 0.2240
Epoch 73/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4560 - accuracy: 0.2134 - val_loss: 1.4217 - val_accuracy: 0.2240
Epoch 74/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4281 - accuracy: 0.2175 - val_loss: 1.4211 - val_accuracy: 0.2240
Epoch 75/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4400 - accuracy: 0.2490 - val_loss: 1.4205 - val_accuracy: 0.2240
Epoch 76/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4335 - accuracy: 0.2408 - val_loss: 1.4198 - val_accuracy: 0.2240
Epoch 77/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4300 - accuracy: 0.2435 - val_loss: 1.4192 - val_accuracy: 0.2240
Epoch 78/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4278 - accuracy: 0.2421 - val_loss: 1.4186 - val_accuracy: 0.2240
Epoch 79/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4260 - accuracy: 0.2476 - val_loss: 1.4180 - val_accuracy: 0.2240
Epoch 80/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4293 - accuracy: 0.2380 - val_loss: 1.4174 - val_accuracy: 0.2240
Epoch 81/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4330 - accuracy: 0.2421 - val_loss: 1.4167 - val_accuracy: 0.2240
Epoch 82/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4187 - accuracy: 0.2339 - val_loss: 1.4161 - val_accuracy: 0.2240
Epoch 83/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4203 - accuracy: 0.2476 - val_loss: 1.4155 - val_accuracy: 0.2240
Epoch 84/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4265 - accuracy: 0.2353 - val_loss: 1.4149 - val_accuracy: 0.2240
Epoch 85/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4420 - accuracy: 0.2353 - val_loss: 1.4143 - val_accuracy: 0.2240
Epoch 86/100
3/3 [==============================] - 0s 34ms/step - loss: 1.4212 - accuracy: 0.2517 - val_loss: 1.4137 - val_accuracy: 0.2240
Epoch 87/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4168 - accuracy: 0.2202 - val_loss: 1.4130 - val_accuracy: 0.2240
Epoch 88/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4267 - accuracy: 0.2271 - val_loss: 1.4124 - val_accuracy: 0.2240
Epoch 89/100
3/3 [==============================] - 0s 15ms/step - loss: 1.3978 - accuracy: 0.2449 - val_loss: 1.4118 - val_accuracy: 0.2240
Epoch 90/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4323 - accuracy: 0.2408 - val_loss: 1.4112 - val_accuracy: 0.2240
Epoch 91/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4271 - accuracy: 0.2490 - val_loss: 1.4106 - val_accuracy: 0.2240
Epoch 92/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4144 - accuracy: 0.2271 - val_loss: 1.4100 - val_accuracy: 0.2240
Epoch 93/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4198 - accuracy: 0.2367 - val_loss: 1.4094 - val_accuracy: 0.2240
Epoch 94/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4111 - accuracy: 0.2599 - val_loss: 1.4087 - val_accuracy: 0.2240
Epoch 95/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4127 - accuracy: 0.2490 - val_loss: 1.4081 - val_accuracy: 0.2240
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4204 - accuracy: 0.2353 - val_loss: 1.4075 - val_accuracy: 0.2240
Epoch 97/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4206 - accuracy: 0.2462 - val_loss: 1.4069 - val_accuracy: 0.2240
Epoch 98/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4089 - accuracy: 0.2435 - val_loss: 1.4063 - val_accuracy: 0.2240
Epoch 99/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4234 - accuracy: 0.2476 - val_loss: 1.4057 - val_accuracy: 0.2240
Epoch 100/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4204 - accuracy: 0.2326 - val_loss: 1.4051 - val_accuracy: 0.2240
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 1, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 133ms/step - loss: 1.2007 - accuracy: 0.4514 - val_loss: 1.2441 - val_accuracy: 0.3934
Epoch 2/100
3/3 [==============================] - 0s 23ms/step - loss: 1.2195 - accuracy: 0.4118 - val_loss: 1.2439 - val_accuracy: 0.3880
Epoch 3/100
3/3 [==============================] - 0s 24ms/step - loss: 1.2149 - accuracy: 0.4254 - val_loss: 1.2435 - val_accuracy: 0.3880
Epoch 4/100
3/3 [==============================] - 0s 13ms/step - loss: 1.2074 - accuracy: 0.4268 - val_loss: 1.2431 - val_accuracy: 0.3880
Epoch 5/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1907 - accuracy: 0.4473 - val_loss: 1.2427 - val_accuracy: 0.3880
Epoch 6/100
3/3 [==============================] - 0s 16ms/step - loss: 1.2158 - accuracy: 0.4295 - val_loss: 1.2423 - val_accuracy: 0.3934
Epoch 7/100
3/3 [==============================] - 0s 23ms/step - loss: 1.2083 - accuracy: 0.4254 - val_loss: 1.2418 - val_accuracy: 0.3934
Epoch 8/100
3/3 [==============================] - 0s 24ms/step - loss: 1.2245 - accuracy: 0.4378 - val_loss: 1.2413 - val_accuracy: 0.3880
Epoch 9/100
3/3 [==============================] - 0s 26ms/step - loss: 1.2113 - accuracy: 0.4282 - val_loss: 1.2407 - val_accuracy: 0.3934
Epoch 10/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2007 - accuracy: 0.4419 - val_loss: 1.2402 - val_accuracy: 0.3934
Epoch 11/100
3/3 [==============================] - 0s 23ms/step - loss: 1.2020 - accuracy: 0.4446 - val_loss: 1.2397 - val_accuracy: 0.3934
Epoch 12/100
3/3 [==============================] - 0s 24ms/step - loss: 1.2083 - accuracy: 0.4268 - val_loss: 1.2391 - val_accuracy: 0.3934
Epoch 13/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1991 - accuracy: 0.4378 - val_loss: 1.2386 - val_accuracy: 0.3934
Epoch 14/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2052 - accuracy: 0.4350 - val_loss: 1.2380 - val_accuracy: 0.3934
Epoch 15/100
3/3 [==============================] - 0s 13ms/step - loss: 1.2008 - accuracy: 0.4172 - val_loss: 1.2374 - val_accuracy: 0.3989
Epoch 16/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1976 - accuracy: 0.4446 - val_loss: 1.2369 - val_accuracy: 0.3989
Epoch 17/100
3/3 [==============================] - 0s 26ms/step - loss: 1.1936 - accuracy: 0.4542 - val_loss: 1.2363 - val_accuracy: 0.3934
Epoch 18/100
3/3 [==============================] - 0s 25ms/step - loss: 1.2069 - accuracy: 0.4268 - val_loss: 1.2358 - val_accuracy: 0.3934
Epoch 19/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1834 - accuracy: 0.4651 - val_loss: 1.2352 - val_accuracy: 0.3934
Epoch 20/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1961 - accuracy: 0.4514 - val_loss: 1.2347 - val_accuracy: 0.3934
Epoch 21/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1989 - accuracy: 0.4295 - val_loss: 1.2341 - val_accuracy: 0.3934
Epoch 22/100
3/3 [==============================] - 0s 19ms/step - loss: 1.2008 - accuracy: 0.4514 - val_loss: 1.2335 - val_accuracy: 0.3934
Epoch 23/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1942 - accuracy: 0.4460 - val_loss: 1.2330 - val_accuracy: 0.3934
Epoch 24/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1967 - accuracy: 0.4596 - val_loss: 1.2324 - val_accuracy: 0.3934
Epoch 25/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1940 - accuracy: 0.4350 - val_loss: 1.2319 - val_accuracy: 0.3934
Epoch 26/100
3/3 [==============================] - 0s 24ms/step - loss: 1.2074 - accuracy: 0.4213 - val_loss: 1.2313 - val_accuracy: 0.3934
Epoch 27/100
3/3 [==============================] - 0s 15ms/step - loss: 1.2017 - accuracy: 0.4637 - val_loss: 1.2308 - val_accuracy: 0.3934
Epoch 28/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1851 - accuracy: 0.4583 - val_loss: 1.2302 - val_accuracy: 0.3934
Epoch 29/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1984 - accuracy: 0.4378 - val_loss: 1.2297 - val_accuracy: 0.4044
Epoch 30/100
3/3 [==============================] - 0s 23ms/step - loss: 1.2079 - accuracy: 0.4268 - val_loss: 1.2291 - val_accuracy: 0.4098
Epoch 31/100
3/3 [==============================] - 0s 25ms/step - loss: 1.2003 - accuracy: 0.4241 - val_loss: 1.2286 - val_accuracy: 0.4098
Epoch 32/100
3/3 [==============================] - 0s 25ms/step - loss: 1.1895 - accuracy: 0.4624 - val_loss: 1.2280 - val_accuracy: 0.4098
Epoch 33/100
3/3 [==============================] - 0s 18ms/step - loss: 1.1855 - accuracy: 0.4747 - val_loss: 1.2275 - val_accuracy: 0.4098
Epoch 34/100
3/3 [==============================] - 0s 24ms/step - loss: 1.2013 - accuracy: 0.4501 - val_loss: 1.2269 - val_accuracy: 0.4098
Epoch 35/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1815 - accuracy: 0.4542 - val_loss: 1.2264 - val_accuracy: 0.4098
Epoch 36/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1857 - accuracy: 0.4555 - val_loss: 1.2258 - val_accuracy: 0.4098
Epoch 37/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1961 - accuracy: 0.4569 - val_loss: 1.2253 - val_accuracy: 0.4098
Epoch 38/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1988 - accuracy: 0.4501 - val_loss: 1.2247 - val_accuracy: 0.4098
Epoch 39/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1984 - accuracy: 0.4610 - val_loss: 1.2242 - val_accuracy: 0.4098
Epoch 40/100
3/3 [==============================] - 0s 16ms/step - loss: 1.2004 - accuracy: 0.4405 - val_loss: 1.2236 - val_accuracy: 0.4098
Epoch 41/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1855 - accuracy: 0.4364 - val_loss: 1.2231 - val_accuracy: 0.4098
Epoch 42/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1923 - accuracy: 0.4501 - val_loss: 1.2225 - val_accuracy: 0.4153
Epoch 43/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1945 - accuracy: 0.4528 - val_loss: 1.2220 - val_accuracy: 0.4153
Epoch 44/100
3/3 [==============================] - 0s 23ms/step - loss: 1.2010 - accuracy: 0.4596 - val_loss: 1.2214 - val_accuracy: 0.4153
Epoch 45/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1847 - accuracy: 0.4514 - val_loss: 1.2209 - val_accuracy: 0.4153
Epoch 46/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1929 - accuracy: 0.4282 - val_loss: 1.2203 - val_accuracy: 0.4208
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1825 - accuracy: 0.4583 - val_loss: 1.2198 - val_accuracy: 0.4208
Epoch 48/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1955 - accuracy: 0.4487 - val_loss: 1.2192 - val_accuracy: 0.4208
Epoch 49/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1962 - accuracy: 0.4487 - val_loss: 1.2187 - val_accuracy: 0.4208
Epoch 50/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1931 - accuracy: 0.4583 - val_loss: 1.2182 - val_accuracy: 0.4262
Epoch 51/100
3/3 [==============================] - 0s 15ms/step - loss: 1.1781 - accuracy: 0.4624 - val_loss: 1.2176 - val_accuracy: 0.4262
Epoch 52/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1961 - accuracy: 0.4391 - val_loss: 1.2171 - val_accuracy: 0.4262
Epoch 53/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1822 - accuracy: 0.4555 - val_loss: 1.2165 - val_accuracy: 0.4372
Epoch 54/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1890 - accuracy: 0.4364 - val_loss: 1.2160 - val_accuracy: 0.4372
Epoch 55/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1711 - accuracy: 0.4610 - val_loss: 1.2154 - val_accuracy: 0.4372
Epoch 56/100
3/3 [==============================] - 0s 15ms/step - loss: 1.1808 - accuracy: 0.4637 - val_loss: 1.2149 - val_accuracy: 0.4372
Epoch 57/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1930 - accuracy: 0.4473 - val_loss: 1.2144 - val_accuracy: 0.4372
Epoch 58/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1921 - accuracy: 0.4610 - val_loss: 1.2138 - val_accuracy: 0.4372
Epoch 59/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1854 - accuracy: 0.4596 - val_loss: 1.2133 - val_accuracy: 0.4426
Epoch 60/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1819 - accuracy: 0.4583 - val_loss: 1.2127 - val_accuracy: 0.4426
Epoch 61/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1850 - accuracy: 0.4706 - val_loss: 1.2122 - val_accuracy: 0.4426
Epoch 62/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1787 - accuracy: 0.4596 - val_loss: 1.2116 - val_accuracy: 0.4426
Epoch 63/100
3/3 [==============================] - 0s 17ms/step - loss: 1.1847 - accuracy: 0.4706 - val_loss: 1.2111 - val_accuracy: 0.4426
Epoch 64/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1835 - accuracy: 0.4514 - val_loss: 1.2106 - val_accuracy: 0.4426
Epoch 65/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1807 - accuracy: 0.4651 - val_loss: 1.2100 - val_accuracy: 0.4426
Epoch 66/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1804 - accuracy: 0.4542 - val_loss: 1.2095 - val_accuracy: 0.4372
Epoch 67/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1785 - accuracy: 0.4747 - val_loss: 1.2089 - val_accuracy: 0.4372
Epoch 68/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1778 - accuracy: 0.4596 - val_loss: 1.2084 - val_accuracy: 0.4372
Epoch 69/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1825 - accuracy: 0.4610 - val_loss: 1.2079 - val_accuracy: 0.4426
Epoch 70/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1782 - accuracy: 0.4774 - val_loss: 1.2073 - val_accuracy: 0.4426
Epoch 71/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1810 - accuracy: 0.4514 - val_loss: 1.2068 - val_accuracy: 0.4426
Epoch 72/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1779 - accuracy: 0.4637 - val_loss: 1.2063 - val_accuracy: 0.4426
Epoch 73/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1773 - accuracy: 0.4637 - val_loss: 1.2057 - val_accuracy: 0.4426
Epoch 74/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1823 - accuracy: 0.4487 - val_loss: 1.2052 - val_accuracy: 0.4426
Epoch 75/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1772 - accuracy: 0.4679 - val_loss: 1.2047 - val_accuracy: 0.4426
Epoch 76/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1828 - accuracy: 0.4555 - val_loss: 1.2041 - val_accuracy: 0.4426
Epoch 77/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1602 - accuracy: 0.4679 - val_loss: 1.2036 - val_accuracy: 0.4481
Epoch 78/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1698 - accuracy: 0.4542 - val_loss: 1.2031 - val_accuracy: 0.4481
Epoch 79/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1822 - accuracy: 0.4583 - val_loss: 1.2025 - val_accuracy: 0.4481
Epoch 80/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1615 - accuracy: 0.4774 - val_loss: 1.2020 - val_accuracy: 0.4481
Epoch 81/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1773 - accuracy: 0.4624 - val_loss: 1.2015 - val_accuracy: 0.4481
Epoch 82/100
3/3 [==============================] - 0s 15ms/step - loss: 1.1720 - accuracy: 0.4596 - val_loss: 1.2009 - val_accuracy: 0.4426
Epoch 83/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1675 - accuracy: 0.4679 - val_loss: 1.2004 - val_accuracy: 0.4426
Epoch 84/100
3/3 [==============================] - 0s 26ms/step - loss: 1.1714 - accuracy: 0.4829 - val_loss: 1.1999 - val_accuracy: 0.4426
Epoch 85/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1749 - accuracy: 0.4802 - val_loss: 1.1994 - val_accuracy: 0.4426
Epoch 86/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1725 - accuracy: 0.4679 - val_loss: 1.1988 - val_accuracy: 0.4426
Epoch 87/100
3/3 [==============================] - 0s 15ms/step - loss: 1.1747 - accuracy: 0.4692 - val_loss: 1.1983 - val_accuracy: 0.4426
Epoch 88/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1800 - accuracy: 0.4761 - val_loss: 1.1978 - val_accuracy: 0.4426
Epoch 89/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1721 - accuracy: 0.4815 - val_loss: 1.1972 - val_accuracy: 0.4426
Epoch 90/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1655 - accuracy: 0.4761 - val_loss: 1.1967 - val_accuracy: 0.4426
Epoch 91/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1679 - accuracy: 0.4761 - val_loss: 1.1962 - val_accuracy: 0.4426
Epoch 92/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1669 - accuracy: 0.4870 - val_loss: 1.1957 - val_accuracy: 0.4481
Epoch 93/100
3/3 [==============================] - 0s 15ms/step - loss: 1.1622 - accuracy: 0.4911 - val_loss: 1.1951 - val_accuracy: 0.4481
Epoch 94/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1685 - accuracy: 0.4911 - val_loss: 1.1946 - val_accuracy: 0.4481
Epoch 95/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1582 - accuracy: 0.4802 - val_loss: 1.1941 - val_accuracy: 0.4481
Epoch 96/100
3/3 [==============================] - 0s 25ms/step - loss: 1.1674 - accuracy: 0.4843 - val_loss: 1.1936 - val_accuracy: 0.4481
Epoch 97/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1743 - accuracy: 0.4733 - val_loss: 1.1931 - val_accuracy: 0.4481
Epoch 98/100
3/3 [==============================] - 0s 24ms/step - loss: 1.1808 - accuracy: 0.4610 - val_loss: 1.1925 - val_accuracy: 0.4481
Epoch 99/100
3/3 [==============================] - 0s 27ms/step - loss: 1.1641 - accuracy: 0.4870 - val_loss: 1.1920 - val_accuracy: 0.4481
Epoch 100/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1651 - accuracy: 0.4815 - val_loss: 1.1915 - val_accuracy: 0.4481
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 1, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
3/3 [==============================] - 1s 120ms/step - loss: 1.4829 - accuracy: 0.1243 - val_loss: 1.5140 - val_accuracy: 0.0879
Epoch 2/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4911 - accuracy: 0.1434 - val_loss: 1.5137 - val_accuracy: 0.0879
Epoch 3/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4787 - accuracy: 0.1489 - val_loss: 1.5131 - val_accuracy: 0.0879
Epoch 4/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4711 - accuracy: 0.1571 - val_loss: 1.5125 - val_accuracy: 0.0879
Epoch 5/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4761 - accuracy: 0.1585 - val_loss: 1.5118 - val_accuracy: 0.0879
Epoch 6/100
3/3 [==============================] - 0s 13ms/step - loss: 1.5056 - accuracy: 0.1311 - val_loss: 1.5110 - val_accuracy: 0.0879
Epoch 7/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4721 - accuracy: 0.1680 - val_loss: 1.5102 - val_accuracy: 0.0879
Epoch 8/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4828 - accuracy: 0.1503 - val_loss: 1.5094 - val_accuracy: 0.0879
Epoch 9/100
3/3 [==============================] - 0s 29ms/step - loss: 1.4895 - accuracy: 0.1339 - val_loss: 1.5085 - val_accuracy: 0.0879
Epoch 10/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4740 - accuracy: 0.1366 - val_loss: 1.5077 - val_accuracy: 0.0879
Epoch 11/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4706 - accuracy: 0.1462 - val_loss: 1.5068 - val_accuracy: 0.0879
Epoch 12/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4942 - accuracy: 0.1339 - val_loss: 1.5059 - val_accuracy: 0.0879
Epoch 13/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4803 - accuracy: 0.1325 - val_loss: 1.5050 - val_accuracy: 0.0879
Epoch 14/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4715 - accuracy: 0.1544 - val_loss: 1.5041 - val_accuracy: 0.0879
Epoch 15/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4640 - accuracy: 0.1598 - val_loss: 1.5032 - val_accuracy: 0.0879
Epoch 16/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4584 - accuracy: 0.1503 - val_loss: 1.5023 - val_accuracy: 0.0934
Epoch 17/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4659 - accuracy: 0.1598 - val_loss: 1.5014 - val_accuracy: 0.0934
Epoch 18/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4807 - accuracy: 0.1434 - val_loss: 1.5004 - val_accuracy: 0.0934
Epoch 19/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4643 - accuracy: 0.1557 - val_loss: 1.4995 - val_accuracy: 0.0934
Epoch 20/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4668 - accuracy: 0.1475 - val_loss: 1.4986 - val_accuracy: 0.0934
Epoch 21/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4797 - accuracy: 0.1421 - val_loss: 1.4977 - val_accuracy: 0.0934
Epoch 22/100
3/3 [==============================] - 0s 28ms/step - loss: 1.4560 - accuracy: 0.1585 - val_loss: 1.4968 - val_accuracy: 0.0934
Epoch 23/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4708 - accuracy: 0.1612 - val_loss: 1.4959 - val_accuracy: 0.0934
Epoch 24/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4567 - accuracy: 0.1667 - val_loss: 1.4950 - val_accuracy: 0.0934
Epoch 25/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4740 - accuracy: 0.1530 - val_loss: 1.4941 - val_accuracy: 0.0934
Epoch 26/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4450 - accuracy: 0.1694 - val_loss: 1.4932 - val_accuracy: 0.0934
Epoch 27/100
3/3 [==============================] - 0s 39ms/step - loss: 1.4625 - accuracy: 0.1571 - val_loss: 1.4923 - val_accuracy: 0.0934
Epoch 28/100
3/3 [==============================] - 0s 26ms/step - loss: 1.4552 - accuracy: 0.1653 - val_loss: 1.4914 - val_accuracy: 0.0934
Epoch 29/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4484 - accuracy: 0.1680 - val_loss: 1.4905 - val_accuracy: 0.0934
Epoch 30/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4615 - accuracy: 0.1475 - val_loss: 1.4896 - val_accuracy: 0.0934
Epoch 31/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4399 - accuracy: 0.1598 - val_loss: 1.4887 - val_accuracy: 0.0934
Epoch 32/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4587 - accuracy: 0.1626 - val_loss: 1.4878 - val_accuracy: 0.0934
Epoch 33/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4606 - accuracy: 0.1653 - val_loss: 1.4869 - val_accuracy: 0.0934
Epoch 34/100
3/3 [==============================] - 0s 26ms/step - loss: 1.4478 - accuracy: 0.1667 - val_loss: 1.4860 - val_accuracy: 0.0934
Epoch 35/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4654 - accuracy: 0.1366 - val_loss: 1.4851 - val_accuracy: 0.0934
Epoch 36/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4561 - accuracy: 0.1557 - val_loss: 1.4842 - val_accuracy: 0.0934
Epoch 37/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4618 - accuracy: 0.1530 - val_loss: 1.4833 - val_accuracy: 0.0989
Epoch 38/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4513 - accuracy: 0.1667 - val_loss: 1.4825 - val_accuracy: 0.0989
Epoch 39/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4434 - accuracy: 0.1530 - val_loss: 1.4816 - val_accuracy: 0.0989
Epoch 40/100
3/3 [==============================] - 0s 26ms/step - loss: 1.4570 - accuracy: 0.1721 - val_loss: 1.4807 - val_accuracy: 0.0989
Epoch 41/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4390 - accuracy: 0.1844 - val_loss: 1.4798 - val_accuracy: 0.0989
Epoch 42/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4391 - accuracy: 0.1790 - val_loss: 1.4789 - val_accuracy: 0.0989
Epoch 43/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4407 - accuracy: 0.1612 - val_loss: 1.4780 - val_accuracy: 0.0989
Epoch 44/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4419 - accuracy: 0.1872 - val_loss: 1.4771 - val_accuracy: 0.0989
Epoch 45/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4583 - accuracy: 0.1544 - val_loss: 1.4763 - val_accuracy: 0.0989
Epoch 46/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4580 - accuracy: 0.1585 - val_loss: 1.4754 - val_accuracy: 0.0989
Epoch 47/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4507 - accuracy: 0.1598 - val_loss: 1.4745 - val_accuracy: 0.0989
Epoch 48/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4788 - accuracy: 0.1475 - val_loss: 1.4736 - val_accuracy: 0.0989
Epoch 49/100
3/3 [==============================] - 0s 26ms/step - loss: 1.4508 - accuracy: 0.1721 - val_loss: 1.4727 - val_accuracy: 0.0989
Epoch 50/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4531 - accuracy: 0.1749 - val_loss: 1.4718 - val_accuracy: 0.0989
Epoch 51/100
3/3 [==============================] - 0s 14ms/step - loss: 1.4520 - accuracy: 0.1639 - val_loss: 1.4709 - val_accuracy: 0.0989
Epoch 52/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4432 - accuracy: 0.1585 - val_loss: 1.4701 - val_accuracy: 0.0989
Epoch 53/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4396 - accuracy: 0.1790 - val_loss: 1.4692 - val_accuracy: 0.0989
Epoch 54/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4246 - accuracy: 0.1790 - val_loss: 1.4683 - val_accuracy: 0.0989
Epoch 55/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4587 - accuracy: 0.1462 - val_loss: 1.4674 - val_accuracy: 0.0989
Epoch 56/100
3/3 [==============================] - 0s 26ms/step - loss: 1.4538 - accuracy: 0.1612 - val_loss: 1.4665 - val_accuracy: 0.0989
Epoch 57/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4500 - accuracy: 0.1530 - val_loss: 1.4657 - val_accuracy: 0.0989
Epoch 58/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4414 - accuracy: 0.1831 - val_loss: 1.4648 - val_accuracy: 0.0989
Epoch 59/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4452 - accuracy: 0.1694 - val_loss: 1.4639 - val_accuracy: 0.0989
Epoch 60/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4278 - accuracy: 0.1817 - val_loss: 1.4630 - val_accuracy: 0.0989
Epoch 61/100
3/3 [==============================] - 0s 28ms/step - loss: 1.4317 - accuracy: 0.1762 - val_loss: 1.4622 - val_accuracy: 0.0989
Epoch 62/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4443 - accuracy: 0.1872 - val_loss: 1.4613 - val_accuracy: 0.0989
Epoch 63/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4241 - accuracy: 0.1790 - val_loss: 1.4604 - val_accuracy: 0.0989
Epoch 64/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4280 - accuracy: 0.1844 - val_loss: 1.4596 - val_accuracy: 0.0989
Epoch 65/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4384 - accuracy: 0.1585 - val_loss: 1.4587 - val_accuracy: 0.0989
Epoch 66/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4444 - accuracy: 0.1790 - val_loss: 1.4578 - val_accuracy: 0.0989
Epoch 67/100
3/3 [==============================] - 0s 27ms/step - loss: 1.4409 - accuracy: 0.1762 - val_loss: 1.4569 - val_accuracy: 0.0989
Epoch 68/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4146 - accuracy: 0.1872 - val_loss: 1.4561 - val_accuracy: 0.0989
Epoch 69/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4329 - accuracy: 0.1598 - val_loss: 1.4552 - val_accuracy: 0.0989
Epoch 70/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4253 - accuracy: 0.1831 - val_loss: 1.4544 - val_accuracy: 0.0989
Epoch 71/100
3/3 [==============================] - 0s 18ms/step - loss: 1.4190 - accuracy: 0.1844 - val_loss: 1.4535 - val_accuracy: 0.0989
Epoch 72/100
3/3 [==============================] - 0s 27ms/step - loss: 1.4212 - accuracy: 0.1803 - val_loss: 1.4526 - val_accuracy: 0.0989
Epoch 73/100
3/3 [==============================] - 0s 34ms/step - loss: 1.4321 - accuracy: 0.1735 - val_loss: 1.4518 - val_accuracy: 0.1044
Epoch 74/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4268 - accuracy: 0.1735 - val_loss: 1.4509 - val_accuracy: 0.1099
Epoch 75/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4237 - accuracy: 0.2036 - val_loss: 1.4501 - val_accuracy: 0.1099
Epoch 76/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4123 - accuracy: 0.1899 - val_loss: 1.4492 - val_accuracy: 0.1099
Epoch 77/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4196 - accuracy: 0.1967 - val_loss: 1.4483 - val_accuracy: 0.1099
Epoch 78/100
3/3 [==============================] - 0s 24ms/step - loss: 1.4205 - accuracy: 0.1940 - val_loss: 1.4475 - val_accuracy: 0.1099
Epoch 79/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4193 - accuracy: 0.1926 - val_loss: 1.4466 - val_accuracy: 0.1099
Epoch 80/100
3/3 [==============================] - 0s 26ms/step - loss: 1.4269 - accuracy: 0.1803 - val_loss: 1.4458 - val_accuracy: 0.1099
Epoch 81/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4232 - accuracy: 0.1612 - val_loss: 1.4449 - val_accuracy: 0.1099
Epoch 82/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4152 - accuracy: 0.2036 - val_loss: 1.4441 - val_accuracy: 0.1099
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4174 - accuracy: 0.1913 - val_loss: 1.4432 - val_accuracy: 0.1099
Epoch 84/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4213 - accuracy: 0.2049 - val_loss: 1.4424 - val_accuracy: 0.1099
Epoch 85/100
3/3 [==============================] - 0s 16ms/step - loss: 1.3916 - accuracy: 0.2117 - val_loss: 1.4415 - val_accuracy: 0.1099
Epoch 86/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4231 - accuracy: 0.1803 - val_loss: 1.4407 - val_accuracy: 0.1099
Epoch 87/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4122 - accuracy: 0.1899 - val_loss: 1.4398 - val_accuracy: 0.1099
Epoch 88/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4192 - accuracy: 0.1954 - val_loss: 1.4390 - val_accuracy: 0.1099
Epoch 89/100
3/3 [==============================] - 0s 25ms/step - loss: 1.4090 - accuracy: 0.1981 - val_loss: 1.4381 - val_accuracy: 0.1154
Epoch 90/100
3/3 [==============================] - 0s 15ms/step - loss: 1.4258 - accuracy: 0.1872 - val_loss: 1.4373 - val_accuracy: 0.1154
Epoch 91/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4098 - accuracy: 0.2036 - val_loss: 1.4365 - val_accuracy: 0.1154
Epoch 92/100
3/3 [==============================] - 0s 14ms/step - loss: 1.4195 - accuracy: 0.1954 - val_loss: 1.4356 - val_accuracy: 0.1154
Epoch 93/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4008 - accuracy: 0.1940 - val_loss: 1.4348 - val_accuracy: 0.1154
Epoch 94/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4121 - accuracy: 0.2117 - val_loss: 1.4339 - val_accuracy: 0.1154
Epoch 95/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4082 - accuracy: 0.1981 - val_loss: 1.4331 - val_accuracy: 0.1154
Epoch 96/100
3/3 [==============================] - 0s 16ms/step - loss: 1.3911 - accuracy: 0.2063 - val_loss: 1.4323 - val_accuracy: 0.1154
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 1.4189 - accuracy: 0.1694 - val_loss: 1.4314 - val_accuracy: 0.1154
Epoch 98/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3974 - accuracy: 0.2213 - val_loss: 1.4306 - val_accuracy: 0.1154
Epoch 99/100
3/3 [==============================] - 0s 16ms/step - loss: 1.4001 - accuracy: 0.1967 - val_loss: 1.4298 - val_accuracy: 0.1154
Epoch 100/100
3/3 [==============================] - 0s 16ms/step - loss: 1.3927 - accuracy: 0.2350 - val_loss: 1.4289 - val_accuracy: 0.1154
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Experiment number: 3
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 117ms/step - loss: 2.3679 - accuracy: 0.6621 - val_loss: 1.2652 - val_accuracy: 0.8142
Epoch 2/100
3/3 [==============================] - 0s 23ms/step - loss: 1.4528 - accuracy: 0.8591 - val_loss: 1.6765 - val_accuracy: 0.8142
Epoch 3/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3192 - accuracy: 0.8591 - val_loss: 1.0646 - val_accuracy: 0.8142
Epoch 4/100
3/3 [==============================] - 0s 20ms/step - loss: 0.9298 - accuracy: 0.8591 - val_loss: 0.9810 - val_accuracy: 0.8142
Epoch 5/100
3/3 [==============================] - 0s 22ms/step - loss: 0.9638 - accuracy: 0.8632 - val_loss: 0.9992 - val_accuracy: 0.8142
Epoch 6/100
3/3 [==============================] - 0s 27ms/step - loss: 0.9203 - accuracy: 0.8591 - val_loss: 0.9056 - val_accuracy: 0.8142
Epoch 7/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7923 - accuracy: 0.8673 - val_loss: 0.7766 - val_accuracy: 0.8197
Epoch 8/100
3/3 [==============================] - 0s 31ms/step - loss: 0.7315 - accuracy: 0.8687 - val_loss: 0.8031 - val_accuracy: 0.8142
Epoch 9/100
3/3 [==============================] - 0s 22ms/step - loss: 0.7524 - accuracy: 0.8632 - val_loss: 0.7770 - val_accuracy: 0.8415
Epoch 10/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6959 - accuracy: 0.8632 - val_loss: 0.6890 - val_accuracy: 0.8142
Epoch 11/100
3/3 [==============================] - 0s 24ms/step - loss: 0.6186 - accuracy: 0.8659 - val_loss: 0.6340 - val_accuracy: 0.8634
Epoch 12/100
3/3 [==============================] - 0s 29ms/step - loss: 0.6169 - accuracy: 0.8646 - val_loss: 0.6429 - val_accuracy: 0.8361
Epoch 13/100
3/3 [==============================] - 0s 22ms/step - loss: 0.6004 - accuracy: 0.8687 - val_loss: 0.6593 - val_accuracy: 0.8142
Epoch 14/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5924 - accuracy: 0.8550 - val_loss: 0.5825 - val_accuracy: 0.8197
Epoch 15/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5556 - accuracy: 0.8550 - val_loss: 0.5704 - val_accuracy: 0.8470
Epoch 16/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5472 - accuracy: 0.8700 - val_loss: 0.6288 - val_accuracy: 0.7978
Epoch 17/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5449 - accuracy: 0.8646 - val_loss: 0.5673 - val_accuracy: 0.8470
Epoch 18/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5049 - accuracy: 0.8700 - val_loss: 0.5465 - val_accuracy: 0.8361
Epoch 19/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5137 - accuracy: 0.8687 - val_loss: 0.5252 - val_accuracy: 0.8470
Epoch 20/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4950 - accuracy: 0.8646 - val_loss: 0.5375 - val_accuracy: 0.8142
Epoch 21/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4786 - accuracy: 0.8632 - val_loss: 0.4923 - val_accuracy: 0.8525
Epoch 22/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4792 - accuracy: 0.8673 - val_loss: 0.4914 - val_accuracy: 0.8634
Epoch 23/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4839 - accuracy: 0.8714 - val_loss: 0.5249 - val_accuracy: 0.8415
Epoch 24/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4701 - accuracy: 0.8700 - val_loss: 0.5051 - val_accuracy: 0.8415
Epoch 25/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4657 - accuracy: 0.8769 - val_loss: 0.5042 - val_accuracy: 0.8470
Epoch 26/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4577 - accuracy: 0.8700 - val_loss: 0.4986 - val_accuracy: 0.8525
Epoch 27/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4674 - accuracy: 0.8673 - val_loss: 0.4868 - val_accuracy: 0.8251
Epoch 28/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4507 - accuracy: 0.8646 - val_loss: 0.4838 - val_accuracy: 0.8306
Epoch 29/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4570 - accuracy: 0.8700 - val_loss: 0.4980 - val_accuracy: 0.8415
Epoch 30/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4541 - accuracy: 0.8755 - val_loss: 0.4940 - val_accuracy: 0.8525
Epoch 31/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4562 - accuracy: 0.8714 - val_loss: 0.4875 - val_accuracy: 0.8361
Epoch 32/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4713 - accuracy: 0.8646 - val_loss: 0.4736 - val_accuracy: 0.8634
Epoch 33/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4628 - accuracy: 0.8659 - val_loss: 0.5191 - val_accuracy: 0.8142
Epoch 34/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4639 - accuracy: 0.8605 - val_loss: 0.4863 - val_accuracy: 0.8470
Epoch 35/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4572 - accuracy: 0.8755 - val_loss: 0.4888 - val_accuracy: 0.8579
Epoch 36/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4865 - accuracy: 0.8577 - val_loss: 0.5070 - val_accuracy: 0.8415
Epoch 37/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4620 - accuracy: 0.8673 - val_loss: 0.4879 - val_accuracy: 0.8579
Epoch 38/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4642 - accuracy: 0.8646 - val_loss: 0.4819 - val_accuracy: 0.8361
Epoch 39/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4698 - accuracy: 0.8618 - val_loss: 0.4954 - val_accuracy: 0.8634
Epoch 40/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4778 - accuracy: 0.8714 - val_loss: 0.5064 - val_accuracy: 0.8306
Epoch 41/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4711 - accuracy: 0.8646 - val_loss: 0.5008 - val_accuracy: 0.8579
Epoch 42/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4757 - accuracy: 0.8605 - val_loss: 0.5032 - val_accuracy: 0.8415
Epoch 43/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4973 - accuracy: 0.8618 - val_loss: 0.5055 - val_accuracy: 0.8197
Epoch 44/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4673 - accuracy: 0.8673 - val_loss: 0.4913 - val_accuracy: 0.8743
Epoch 45/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4692 - accuracy: 0.8591 - val_loss: 0.5231 - val_accuracy: 0.8142
Epoch 46/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4684 - accuracy: 0.8605 - val_loss: 0.4911 - val_accuracy: 0.8634
Epoch 47/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4625 - accuracy: 0.8782 - val_loss: 0.5110 - val_accuracy: 0.8251
Epoch 48/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4834 - accuracy: 0.8646 - val_loss: 0.4832 - val_accuracy: 0.8361
Epoch 49/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4715 - accuracy: 0.8618 - val_loss: 0.4876 - val_accuracy: 0.8197
Epoch 50/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4672 - accuracy: 0.8700 - val_loss: 0.5151 - val_accuracy: 0.8361
Epoch 51/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4695 - accuracy: 0.8755 - val_loss: 0.5064 - val_accuracy: 0.8525
Epoch 52/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4721 - accuracy: 0.8700 - val_loss: 0.4926 - val_accuracy: 0.8251
Epoch 53/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4811 - accuracy: 0.8550 - val_loss: 0.4924 - val_accuracy: 0.8197
Epoch 54/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4656 - accuracy: 0.8714 - val_loss: 0.5092 - val_accuracy: 0.8197
Epoch 55/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4646 - accuracy: 0.8605 - val_loss: 0.4891 - val_accuracy: 0.8306
Epoch 56/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4654 - accuracy: 0.8659 - val_loss: 0.4983 - val_accuracy: 0.8142
Epoch 57/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4683 - accuracy: 0.8646 - val_loss: 0.5009 - val_accuracy: 0.8470
Epoch 58/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4601 - accuracy: 0.8632 - val_loss: 0.5155 - val_accuracy: 0.8197
Epoch 59/100
3/3 [==============================] - 0s 30ms/step - loss: 0.4494 - accuracy: 0.8591 - val_loss: 0.4947 - val_accuracy: 0.8142
Epoch 60/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4574 - accuracy: 0.8605 - val_loss: 0.4723 - val_accuracy: 0.8470
Epoch 61/100
3/3 [==============================] - 0s 28ms/step - loss: 0.4627 - accuracy: 0.8646 - val_loss: 0.4867 - val_accuracy: 0.8197
Epoch 62/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4536 - accuracy: 0.8646 - val_loss: 0.4770 - val_accuracy: 0.8579
Epoch 63/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4776 - accuracy: 0.8687 - val_loss: 0.4660 - val_accuracy: 0.8579
Epoch 64/100
3/3 [==============================] - 0s 28ms/step - loss: 0.4760 - accuracy: 0.8550 - val_loss: 0.5123 - val_accuracy: 0.8197
Epoch 65/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4748 - accuracy: 0.8536 - val_loss: 0.5350 - val_accuracy: 0.8415
Epoch 66/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4802 - accuracy: 0.8687 - val_loss: 0.5061 - val_accuracy: 0.8142
Epoch 67/100
3/3 [==============================] - 0s 26ms/step - loss: 0.4850 - accuracy: 0.8632 - val_loss: 0.4997 - val_accuracy: 0.8142
Epoch 68/100
3/3 [==============================] - 0s 13ms/step - loss: 0.4738 - accuracy: 0.8632 - val_loss: 0.4921 - val_accuracy: 0.8251
Epoch 69/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4601 - accuracy: 0.8673 - val_loss: 0.4902 - val_accuracy: 0.8142
Epoch 70/100
3/3 [==============================] - 0s 14ms/step - loss: 0.4689 - accuracy: 0.8646 - val_loss: 0.4836 - val_accuracy: 0.8142
Epoch 71/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4805 - accuracy: 0.8646 - val_loss: 0.4965 - val_accuracy: 0.8251
Epoch 72/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4813 - accuracy: 0.8605 - val_loss: 0.5473 - val_accuracy: 0.7705
Epoch 73/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4796 - accuracy: 0.8865 - val_loss: 0.5244 - val_accuracy: 0.8142
Epoch 74/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4747 - accuracy: 0.8618 - val_loss: 0.5141 - val_accuracy: 0.8142
Epoch 75/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4702 - accuracy: 0.8564 - val_loss: 0.4854 - val_accuracy: 0.8142
Epoch 76/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4692 - accuracy: 0.8591 - val_loss: 0.4866 - val_accuracy: 0.8197
Epoch 77/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4547 - accuracy: 0.8673 - val_loss: 0.4879 - val_accuracy: 0.8142
Epoch 78/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4714 - accuracy: 0.8618 - val_loss: 0.4805 - val_accuracy: 0.8142
Epoch 79/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4458 - accuracy: 0.8673 - val_loss: 0.4604 - val_accuracy: 0.8743
Epoch 80/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4489 - accuracy: 0.8687 - val_loss: 0.5017 - val_accuracy: 0.8197
Epoch 81/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4757 - accuracy: 0.8741 - val_loss: 0.4767 - val_accuracy: 0.8579
Epoch 82/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4660 - accuracy: 0.8714 - val_loss: 0.4847 - val_accuracy: 0.8361
Epoch 83/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4721 - accuracy: 0.8687 - val_loss: 0.4969 - val_accuracy: 0.8470
Epoch 84/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4764 - accuracy: 0.8564 - val_loss: 0.5000 - val_accuracy: 0.8361
Epoch 85/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4584 - accuracy: 0.8646 - val_loss: 0.5151 - val_accuracy: 0.8142
Epoch 86/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4650 - accuracy: 0.8618 - val_loss: 0.4726 - val_accuracy: 0.8689
Epoch 87/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4678 - accuracy: 0.8632 - val_loss: 0.4903 - val_accuracy: 0.8197
Epoch 88/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4737 - accuracy: 0.8659 - val_loss: 0.5283 - val_accuracy: 0.8142
Epoch 89/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4806 - accuracy: 0.8618 - val_loss: 0.4853 - val_accuracy: 0.8743
Epoch 90/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4644 - accuracy: 0.8755 - val_loss: 0.4764 - val_accuracy: 0.8306
Epoch 91/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4902 - accuracy: 0.8591 - val_loss: 0.4983 - val_accuracy: 0.8142
Epoch 92/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4628 - accuracy: 0.8577 - val_loss: 0.4816 - val_accuracy: 0.8415
Epoch 93/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4645 - accuracy: 0.8632 - val_loss: 0.5086 - val_accuracy: 0.8087
Epoch 94/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4625 - accuracy: 0.8618 - val_loss: 0.5107 - val_accuracy: 0.8142
Epoch 95/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4790 - accuracy: 0.8632 - val_loss: 0.4753 - val_accuracy: 0.8142
Epoch 96/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4676 - accuracy: 0.8605 - val_loss: 0.4928 - val_accuracy: 0.8142
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4638 - accuracy: 0.8591 - val_loss: 0.4985 - val_accuracy: 0.8142
Epoch 98/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4647 - accuracy: 0.8591 - val_loss: 0.4799 - val_accuracy: 0.8142
Epoch 99/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4677 - accuracy: 0.8605 - val_loss: 0.4846 - val_accuracy: 0.8142
Epoch 100/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4591 - accuracy: 0.8673 - val_loss: 0.4768 - val_accuracy: 0.8033
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 115ms/step - loss: 2.4047 - accuracy: 0.6033 - val_loss: 1.2022 - val_accuracy: 0.8415
Epoch 2/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4269 - accuracy: 0.8523 - val_loss: 1.4836 - val_accuracy: 0.8579
Epoch 3/100
3/3 [==============================] - 0s 21ms/step - loss: 1.3214 - accuracy: 0.8564 - val_loss: 1.0087 - val_accuracy: 0.8525
Epoch 4/100
3/3 [==============================] - 0s 16ms/step - loss: 0.9770 - accuracy: 0.8577 - val_loss: 0.9330 - val_accuracy: 0.8415
Epoch 5/100
3/3 [==============================] - 0s 27ms/step - loss: 0.9541 - accuracy: 0.8632 - val_loss: 0.9568 - val_accuracy: 0.8743
Epoch 6/100
3/3 [==============================] - 0s 24ms/step - loss: 0.9752 - accuracy: 0.8468 - val_loss: 0.8698 - val_accuracy: 0.8525
Epoch 7/100
3/3 [==============================] - 0s 26ms/step - loss: 0.8384 - accuracy: 0.8482 - val_loss: 0.7241 - val_accuracy: 0.8415
Epoch 8/100
3/3 [==============================] - 0s 23ms/step - loss: 0.7498 - accuracy: 0.8577 - val_loss: 0.7373 - val_accuracy: 0.8470
Epoch 9/100
3/3 [==============================] - 0s 23ms/step - loss: 0.7351 - accuracy: 0.8536 - val_loss: 0.7168 - val_accuracy: 0.8579
Epoch 10/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7151 - accuracy: 0.8564 - val_loss: 0.6576 - val_accuracy: 0.8798
Epoch 11/100
3/3 [==============================] - 0s 14ms/step - loss: 0.6434 - accuracy: 0.8632 - val_loss: 0.6163 - val_accuracy: 0.8579
Epoch 12/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6396 - accuracy: 0.8509 - val_loss: 0.5736 - val_accuracy: 0.8579
Epoch 13/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6097 - accuracy: 0.8618 - val_loss: 0.5672 - val_accuracy: 0.8962
Epoch 14/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5911 - accuracy: 0.8495 - val_loss: 0.5741 - val_accuracy: 0.8525
Epoch 15/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5911 - accuracy: 0.8523 - val_loss: 0.5458 - val_accuracy: 0.8743
Epoch 16/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5511 - accuracy: 0.8564 - val_loss: 0.5108 - val_accuracy: 0.8962
Epoch 17/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5366 - accuracy: 0.8550 - val_loss: 0.5168 - val_accuracy: 0.8525
Epoch 18/100
3/3 [==============================] - 0s 31ms/step - loss: 0.5241 - accuracy: 0.8618 - val_loss: 0.4827 - val_accuracy: 0.8798
Epoch 19/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5075 - accuracy: 0.8591 - val_loss: 0.4928 - val_accuracy: 0.8743
Epoch 20/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5228 - accuracy: 0.8536 - val_loss: 0.5105 - val_accuracy: 0.8579
Epoch 21/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4990 - accuracy: 0.8618 - val_loss: 0.4706 - val_accuracy: 0.8579
Epoch 22/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4764 - accuracy: 0.8659 - val_loss: 0.4646 - val_accuracy: 0.8798
Epoch 23/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4976 - accuracy: 0.8591 - val_loss: 0.4817 - val_accuracy: 0.8743
Epoch 24/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5038 - accuracy: 0.8427 - val_loss: 0.4568 - val_accuracy: 0.8579
Epoch 25/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4832 - accuracy: 0.8618 - val_loss: 0.4472 - val_accuracy: 0.8634
Epoch 26/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4681 - accuracy: 0.8605 - val_loss: 0.4520 - val_accuracy: 0.8634
Epoch 27/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4855 - accuracy: 0.8659 - val_loss: 0.4805 - val_accuracy: 0.8798
Epoch 28/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4830 - accuracy: 0.8632 - val_loss: 0.4576 - val_accuracy: 0.8852
Epoch 29/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4735 - accuracy: 0.8673 - val_loss: 0.4544 - val_accuracy: 0.8634
Epoch 30/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4795 - accuracy: 0.8468 - val_loss: 0.4503 - val_accuracy: 0.8962
Epoch 31/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4766 - accuracy: 0.8482 - val_loss: 0.4572 - val_accuracy: 0.8525
Epoch 32/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4734 - accuracy: 0.8591 - val_loss: 0.4260 - val_accuracy: 0.8634
Epoch 33/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4595 - accuracy: 0.8577 - val_loss: 0.4285 - val_accuracy: 0.8907
Epoch 34/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4731 - accuracy: 0.8454 - val_loss: 0.4263 - val_accuracy: 0.8798
Epoch 35/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4454 - accuracy: 0.8632 - val_loss: 0.4558 - val_accuracy: 0.8579
Epoch 36/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4674 - accuracy: 0.8523 - val_loss: 0.4662 - val_accuracy: 0.8634
Epoch 37/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4649 - accuracy: 0.8495 - val_loss: 0.4510 - val_accuracy: 0.8415
Epoch 38/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4550 - accuracy: 0.8523 - val_loss: 0.4425 - val_accuracy: 0.8415
Epoch 39/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4507 - accuracy: 0.8550 - val_loss: 0.4308 - val_accuracy: 0.9016
Epoch 40/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4486 - accuracy: 0.8509 - val_loss: 0.4253 - val_accuracy: 0.8852
Epoch 41/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4537 - accuracy: 0.8536 - val_loss: 0.4564 - val_accuracy: 0.8689
Epoch 42/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4500 - accuracy: 0.8550 - val_loss: 0.4357 - val_accuracy: 0.8579
Epoch 43/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4538 - accuracy: 0.8482 - val_loss: 0.4368 - val_accuracy: 0.8525
Epoch 44/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4497 - accuracy: 0.8605 - val_loss: 0.4796 - val_accuracy: 0.8579
Epoch 45/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4655 - accuracy: 0.8536 - val_loss: 0.4406 - val_accuracy: 0.8798
Epoch 46/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4620 - accuracy: 0.8605 - val_loss: 0.4495 - val_accuracy: 0.8415
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4484 - accuracy: 0.8577 - val_loss: 0.4378 - val_accuracy: 0.8798
Epoch 48/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4506 - accuracy: 0.8564 - val_loss: 0.4274 - val_accuracy: 0.8962
Epoch 49/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4564 - accuracy: 0.8632 - val_loss: 0.4500 - val_accuracy: 0.8743
Epoch 50/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4580 - accuracy: 0.8659 - val_loss: 0.4461 - val_accuracy: 0.8743
Epoch 51/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4446 - accuracy: 0.8591 - val_loss: 0.4452 - val_accuracy: 0.8743
Epoch 52/100
3/3 [==============================] - 0s 26ms/step - loss: 0.4738 - accuracy: 0.8482 - val_loss: 0.4626 - val_accuracy: 0.8798
Epoch 53/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4674 - accuracy: 0.8509 - val_loss: 0.4410 - val_accuracy: 0.8798
Epoch 54/100
3/3 [==============================] - 0s 26ms/step - loss: 0.4479 - accuracy: 0.8577 - val_loss: 0.4612 - val_accuracy: 0.8415
Epoch 55/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4591 - accuracy: 0.8523 - val_loss: 0.4587 - val_accuracy: 0.8689
Epoch 56/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4648 - accuracy: 0.8440 - val_loss: 0.4329 - val_accuracy: 0.8525
Epoch 57/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4582 - accuracy: 0.8591 - val_loss: 0.4511 - val_accuracy: 0.8743
Epoch 58/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4605 - accuracy: 0.8577 - val_loss: 0.4454 - val_accuracy: 0.8743
Epoch 59/100
3/3 [==============================] - 0s 31ms/step - loss: 0.4662 - accuracy: 0.8564 - val_loss: 0.4433 - val_accuracy: 0.8743
Epoch 60/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4722 - accuracy: 0.8605 - val_loss: 0.4548 - val_accuracy: 0.8525
Epoch 61/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4484 - accuracy: 0.8591 - val_loss: 0.4604 - val_accuracy: 0.8415
Epoch 62/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4697 - accuracy: 0.8550 - val_loss: 0.4832 - val_accuracy: 0.8907
Epoch 63/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4639 - accuracy: 0.8468 - val_loss: 0.4683 - val_accuracy: 0.8579
Epoch 64/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4485 - accuracy: 0.8577 - val_loss: 0.4533 - val_accuracy: 0.8579
Epoch 65/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4541 - accuracy: 0.8632 - val_loss: 0.4517 - val_accuracy: 0.8525
Epoch 66/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4646 - accuracy: 0.8536 - val_loss: 0.4345 - val_accuracy: 0.8743
Epoch 67/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4693 - accuracy: 0.8591 - val_loss: 0.4355 - val_accuracy: 0.8415
Epoch 68/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4692 - accuracy: 0.8523 - val_loss: 0.4442 - val_accuracy: 0.8525
Epoch 69/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4510 - accuracy: 0.8564 - val_loss: 0.4614 - val_accuracy: 0.9016
Epoch 70/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4781 - accuracy: 0.8509 - val_loss: 0.4861 - val_accuracy: 0.8579
Epoch 71/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4662 - accuracy: 0.8591 - val_loss: 0.4742 - val_accuracy: 0.8415
Epoch 72/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4640 - accuracy: 0.8550 - val_loss: 0.4460 - val_accuracy: 0.8579
Epoch 73/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4644 - accuracy: 0.8454 - val_loss: 0.4739 - val_accuracy: 0.8415
Epoch 74/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4709 - accuracy: 0.8509 - val_loss: 0.4570 - val_accuracy: 0.8525
Epoch 75/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4583 - accuracy: 0.8577 - val_loss: 0.4617 - val_accuracy: 0.8852
Epoch 76/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4763 - accuracy: 0.8605 - val_loss: 0.4688 - val_accuracy: 0.8470
Epoch 77/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4579 - accuracy: 0.8550 - val_loss: 0.4542 - val_accuracy: 0.8415
Epoch 78/100
3/3 [==============================] - 0s 30ms/step - loss: 0.4689 - accuracy: 0.8550 - val_loss: 0.4619 - val_accuracy: 0.8743
Epoch 79/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4567 - accuracy: 0.8536 - val_loss: 0.4598 - val_accuracy: 0.8579
Epoch 80/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4763 - accuracy: 0.8482 - val_loss: 0.4259 - val_accuracy: 0.8579
Epoch 81/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4514 - accuracy: 0.8618 - val_loss: 0.4561 - val_accuracy: 0.8798
Epoch 82/100
3/3 [==============================] - 0s 29ms/step - loss: 0.4626 - accuracy: 0.8564 - val_loss: 0.4496 - val_accuracy: 0.8962
Epoch 83/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4614 - accuracy: 0.8454 - val_loss: 0.4630 - val_accuracy: 0.8525
Epoch 84/100
3/3 [==============================] - 0s 29ms/step - loss: 0.4692 - accuracy: 0.8591 - val_loss: 0.4558 - val_accuracy: 0.8907
Epoch 85/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4692 - accuracy: 0.8618 - val_loss: 0.4709 - val_accuracy: 0.8743
Epoch 86/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4776 - accuracy: 0.8550 - val_loss: 0.4571 - val_accuracy: 0.8415
Epoch 87/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4615 - accuracy: 0.8495 - val_loss: 0.4682 - val_accuracy: 0.8415
Epoch 88/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4774 - accuracy: 0.8550 - val_loss: 0.4575 - val_accuracy: 0.8689
Epoch 89/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4685 - accuracy: 0.8577 - val_loss: 0.4459 - val_accuracy: 0.8689
Epoch 90/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4599 - accuracy: 0.8605 - val_loss: 0.4740 - val_accuracy: 0.8415
Epoch 91/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4626 - accuracy: 0.8577 - val_loss: 0.4559 - val_accuracy: 0.8689
Epoch 92/100
3/3 [==============================] - 0s 28ms/step - loss: 0.4640 - accuracy: 0.8577 - val_loss: 0.4625 - val_accuracy: 0.8634
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4677 - accuracy: 0.8700 - val_loss: 0.4627 - val_accuracy: 0.8415
Epoch 94/100
3/3 [==============================] - 0s 29ms/step - loss: 0.4791 - accuracy: 0.8605 - val_loss: 0.4633 - val_accuracy: 0.8852
Epoch 95/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4778 - accuracy: 0.8646 - val_loss: 0.4835 - val_accuracy: 0.8689
Epoch 96/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4816 - accuracy: 0.8550 - val_loss: 0.4585 - val_accuracy: 0.8798
Epoch 97/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4823 - accuracy: 0.8495 - val_loss: 0.4545 - val_accuracy: 0.8852
Epoch 98/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4724 - accuracy: 0.8564 - val_loss: 0.4766 - val_accuracy: 0.8415
Epoch 99/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5030 - accuracy: 0.8427 - val_loss: 0.4841 - val_accuracy: 0.8689
Epoch 100/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4913 - accuracy: 0.8577 - val_loss: 0.5120 - val_accuracy: 0.8415
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 117ms/step - loss: 2.4220 - accuracy: 0.6648 - val_loss: 1.1956 - val_accuracy: 0.8470
Epoch 2/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4000 - accuracy: 0.8509 - val_loss: 1.5215 - val_accuracy: 0.8470
Epoch 3/100
3/3 [==============================] - 0s 27ms/step - loss: 1.3457 - accuracy: 0.8536 - val_loss: 1.0840 - val_accuracy: 0.8415
Epoch 4/100
3/3 [==============================] - 0s 22ms/step - loss: 0.9877 - accuracy: 0.8618 - val_loss: 0.9441 - val_accuracy: 0.8470
Epoch 5/100
3/3 [==============================] - 0s 23ms/step - loss: 0.9536 - accuracy: 0.8605 - val_loss: 0.9547 - val_accuracy: 0.8689
Epoch 6/100
3/3 [==============================] - 0s 25ms/step - loss: 0.9410 - accuracy: 0.8564 - val_loss: 0.8901 - val_accuracy: 0.8525
Epoch 7/100
3/3 [==============================] - 0s 17ms/step - loss: 0.8575 - accuracy: 0.8509 - val_loss: 0.7323 - val_accuracy: 0.8689
Epoch 8/100
3/3 [==============================] - 0s 22ms/step - loss: 0.7368 - accuracy: 0.8550 - val_loss: 0.7445 - val_accuracy: 0.8470
Epoch 9/100
3/3 [==============================] - 0s 30ms/step - loss: 0.7682 - accuracy: 0.8550 - val_loss: 0.7325 - val_accuracy: 0.8525
Epoch 10/100
3/3 [==============================] - 0s 17ms/step - loss: 0.7359 - accuracy: 0.8509 - val_loss: 0.6798 - val_accuracy: 0.8634
Epoch 11/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6697 - accuracy: 0.8564 - val_loss: 0.6831 - val_accuracy: 0.8470
Epoch 12/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6491 - accuracy: 0.8536 - val_loss: 0.6362 - val_accuracy: 0.8634
Epoch 13/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6318 - accuracy: 0.8618 - val_loss: 0.6018 - val_accuracy: 0.8579
Epoch 14/100
3/3 [==============================] - 0s 24ms/step - loss: 0.6065 - accuracy: 0.8591 - val_loss: 0.5960 - val_accuracy: 0.8470
Epoch 15/100
3/3 [==============================] - 0s 15ms/step - loss: 0.5832 - accuracy: 0.8495 - val_loss: 0.5642 - val_accuracy: 0.8579
Epoch 16/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5515 - accuracy: 0.8659 - val_loss: 0.5263 - val_accuracy: 0.8634
Epoch 17/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5407 - accuracy: 0.8605 - val_loss: 0.5111 - val_accuracy: 0.8689
Epoch 18/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5188 - accuracy: 0.8659 - val_loss: 0.5122 - val_accuracy: 0.8798
Epoch 19/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5348 - accuracy: 0.8673 - val_loss: 0.5310 - val_accuracy: 0.8579
Epoch 20/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5260 - accuracy: 0.8536 - val_loss: 0.4892 - val_accuracy: 0.8579
Epoch 21/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5082 - accuracy: 0.8591 - val_loss: 0.4770 - val_accuracy: 0.8689
Epoch 22/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4899 - accuracy: 0.8755 - val_loss: 0.4848 - val_accuracy: 0.8689
Epoch 23/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4901 - accuracy: 0.8605 - val_loss: 0.4655 - val_accuracy: 0.8634
Epoch 24/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4858 - accuracy: 0.8550 - val_loss: 0.4881 - val_accuracy: 0.8579
Epoch 25/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4930 - accuracy: 0.8523 - val_loss: 0.4692 - val_accuracy: 0.8798
Epoch 26/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4908 - accuracy: 0.8536 - val_loss: 0.4822 - val_accuracy: 0.8579
Epoch 27/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4934 - accuracy: 0.8509 - val_loss: 0.4710 - val_accuracy: 0.8415
Epoch 28/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4767 - accuracy: 0.8605 - val_loss: 0.4635 - val_accuracy: 0.8579
Epoch 29/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4684 - accuracy: 0.8523 - val_loss: 0.4536 - val_accuracy: 0.8634
Epoch 30/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4571 - accuracy: 0.8646 - val_loss: 0.4686 - val_accuracy: 0.8415
Epoch 31/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4678 - accuracy: 0.8523 - val_loss: 0.4639 - val_accuracy: 0.8634
Epoch 32/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4706 - accuracy: 0.8591 - val_loss: 0.4337 - val_accuracy: 0.8525
Epoch 33/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4530 - accuracy: 0.8427 - val_loss: 0.4378 - val_accuracy: 0.8525
Epoch 34/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4617 - accuracy: 0.8495 - val_loss: 0.4590 - val_accuracy: 0.8634
Epoch 35/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4596 - accuracy: 0.8605 - val_loss: 0.4348 - val_accuracy: 0.8634
Epoch 36/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4584 - accuracy: 0.8632 - val_loss: 0.4443 - val_accuracy: 0.8579
Epoch 37/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4574 - accuracy: 0.8523 - val_loss: 0.4313 - val_accuracy: 0.8743
Epoch 38/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4522 - accuracy: 0.8536 - val_loss: 0.4324 - val_accuracy: 0.8525
Epoch 39/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4513 - accuracy: 0.8646 - val_loss: 0.4211 - val_accuracy: 0.8689
Epoch 40/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4500 - accuracy: 0.8591 - val_loss: 0.4260 - val_accuracy: 0.8634
Epoch 41/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4535 - accuracy: 0.8769 - val_loss: 0.4402 - val_accuracy: 0.8579
Epoch 42/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4411 - accuracy: 0.8646 - val_loss: 0.4430 - val_accuracy: 0.8579
Epoch 43/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4681 - accuracy: 0.8509 - val_loss: 0.4463 - val_accuracy: 0.8634
Epoch 44/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4467 - accuracy: 0.8618 - val_loss: 0.4336 - val_accuracy: 0.8525
Epoch 45/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4559 - accuracy: 0.8591 - val_loss: 0.4290 - val_accuracy: 0.8634
Epoch 46/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4633 - accuracy: 0.8700 - val_loss: 0.4440 - val_accuracy: 0.8634
Epoch 47/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4483 - accuracy: 0.8673 - val_loss: 0.4451 - val_accuracy: 0.8579
Epoch 48/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4677 - accuracy: 0.8673 - val_loss: 0.4334 - val_accuracy: 0.8689
Epoch 49/100
3/3 [==============================] - 0s 28ms/step - loss: 0.4652 - accuracy: 0.8591 - val_loss: 0.4424 - val_accuracy: 0.8525
Epoch 50/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4653 - accuracy: 0.8618 - val_loss: 0.4468 - val_accuracy: 0.8525
Epoch 51/100
3/3 [==============================] - 0s 26ms/step - loss: 0.4512 - accuracy: 0.8673 - val_loss: 0.4479 - val_accuracy: 0.8525
Epoch 52/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4674 - accuracy: 0.8523 - val_loss: 0.4368 - val_accuracy: 0.8579
Epoch 53/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4625 - accuracy: 0.8632 - val_loss: 0.4461 - val_accuracy: 0.8579
Epoch 54/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4680 - accuracy: 0.8659 - val_loss: 0.4725 - val_accuracy: 0.8470
Epoch 55/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4768 - accuracy: 0.8577 - val_loss: 0.4483 - val_accuracy: 0.8743
Epoch 56/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4638 - accuracy: 0.8605 - val_loss: 0.4530 - val_accuracy: 0.8470
Epoch 57/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4763 - accuracy: 0.8577 - val_loss: 0.4705 - val_accuracy: 0.8525
Epoch 58/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4698 - accuracy: 0.8714 - val_loss: 0.4489 - val_accuracy: 0.8798
Epoch 59/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4633 - accuracy: 0.8673 - val_loss: 0.4780 - val_accuracy: 0.8470
Epoch 60/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4883 - accuracy: 0.8523 - val_loss: 0.4556 - val_accuracy: 0.8689
Epoch 61/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4661 - accuracy: 0.8673 - val_loss: 0.4640 - val_accuracy: 0.8689
Epoch 62/100
3/3 [==============================] - 0s 26ms/step - loss: 0.4938 - accuracy: 0.8591 - val_loss: 0.4764 - val_accuracy: 0.8470
Epoch 63/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4753 - accuracy: 0.8509 - val_loss: 0.4594 - val_accuracy: 0.8634
Epoch 64/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4759 - accuracy: 0.8605 - val_loss: 0.4817 - val_accuracy: 0.8689
Epoch 65/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4806 - accuracy: 0.8728 - val_loss: 0.4680 - val_accuracy: 0.8579
Epoch 66/100
3/3 [==============================] - 0s 28ms/step - loss: 0.4785 - accuracy: 0.8673 - val_loss: 0.4421 - val_accuracy: 0.8743
Epoch 67/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4810 - accuracy: 0.8646 - val_loss: 0.4506 - val_accuracy: 0.8470
Epoch 68/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4807 - accuracy: 0.8495 - val_loss: 0.4262 - val_accuracy: 0.8634
Epoch 69/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4870 - accuracy: 0.8495 - val_loss: 0.4735 - val_accuracy: 0.8689
Epoch 70/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4956 - accuracy: 0.8468 - val_loss: 0.4636 - val_accuracy: 0.8689
Epoch 71/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4882 - accuracy: 0.8577 - val_loss: 0.4792 - val_accuracy: 0.8525
Epoch 72/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4824 - accuracy: 0.8605 - val_loss: 0.4335 - val_accuracy: 0.8689
Epoch 73/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4700 - accuracy: 0.8591 - val_loss: 0.4585 - val_accuracy: 0.8525
Epoch 74/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4800 - accuracy: 0.8605 - val_loss: 0.4485 - val_accuracy: 0.8743
Epoch 75/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4902 - accuracy: 0.8605 - val_loss: 0.4882 - val_accuracy: 0.8798
Epoch 76/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5164 - accuracy: 0.8536 - val_loss: 0.4987 - val_accuracy: 0.8306
Epoch 77/100
3/3 [==============================] - 0s 15ms/step - loss: 0.5010 - accuracy: 0.8577 - val_loss: 0.4670 - val_accuracy: 0.8470
Epoch 78/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4884 - accuracy: 0.8509 - val_loss: 0.4709 - val_accuracy: 0.8470
Epoch 79/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4947 - accuracy: 0.8591 - val_loss: 0.4697 - val_accuracy: 0.8689
Epoch 80/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4713 - accuracy: 0.8687 - val_loss: 0.4681 - val_accuracy: 0.8470
Epoch 81/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4769 - accuracy: 0.8536 - val_loss: 0.4641 - val_accuracy: 0.8470
Epoch 82/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4636 - accuracy: 0.8536 - val_loss: 0.4638 - val_accuracy: 0.8579
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4611 - accuracy: 0.8591 - val_loss: 0.4488 - val_accuracy: 0.8634
Epoch 84/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4592 - accuracy: 0.8646 - val_loss: 0.4214 - val_accuracy: 0.8634
Epoch 85/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4632 - accuracy: 0.8591 - val_loss: 0.4356 - val_accuracy: 0.8743
Epoch 86/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4680 - accuracy: 0.8659 - val_loss: 0.4435 - val_accuracy: 0.8634
Epoch 87/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4519 - accuracy: 0.8564 - val_loss: 0.4458 - val_accuracy: 0.8634
Epoch 88/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4589 - accuracy: 0.8659 - val_loss: 0.4211 - val_accuracy: 0.8743
Epoch 89/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4532 - accuracy: 0.8714 - val_loss: 0.4591 - val_accuracy: 0.8689
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4596 - accuracy: 0.8605 - val_loss: 0.4338 - val_accuracy: 0.8634
Epoch 91/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4645 - accuracy: 0.8605 - val_loss: 0.4295 - val_accuracy: 0.8634
Epoch 92/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4572 - accuracy: 0.8536 - val_loss: 0.4643 - val_accuracy: 0.8689
Epoch 93/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4708 - accuracy: 0.8564 - val_loss: 0.4588 - val_accuracy: 0.8743
Epoch 94/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4750 - accuracy: 0.8714 - val_loss: 0.4656 - val_accuracy: 0.8579
Epoch 95/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4775 - accuracy: 0.8673 - val_loss: 0.4413 - val_accuracy: 0.8743
Epoch 96/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4626 - accuracy: 0.8714 - val_loss: 0.4542 - val_accuracy: 0.8634
Epoch 97/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4570 - accuracy: 0.8673 - val_loss: 0.4333 - val_accuracy: 0.8743
Epoch 98/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4625 - accuracy: 0.8646 - val_loss: 0.4480 - val_accuracy: 0.8579
Epoch 99/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4708 - accuracy: 0.8632 - val_loss: 0.4491 - val_accuracy: 0.8634
Epoch 100/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4730 - accuracy: 0.8577 - val_loss: 0.4629 - val_accuracy: 0.8470
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 122ms/step - loss: 2.2976 - accuracy: 0.7086 - val_loss: 1.1846 - val_accuracy: 0.8852
Epoch 2/100
3/3 [==============================] - 0s 17ms/step - loss: 1.4121 - accuracy: 0.8523 - val_loss: 1.4593 - val_accuracy: 0.8525
Epoch 3/100
3/3 [==============================] - 0s 17ms/step - loss: 1.3294 - accuracy: 0.8495 - val_loss: 0.9655 - val_accuracy: 0.8907
Epoch 4/100
3/3 [==============================] - 0s 21ms/step - loss: 0.9107 - accuracy: 0.8550 - val_loss: 0.8967 - val_accuracy: 0.8579
Epoch 5/100
3/3 [==============================] - 0s 22ms/step - loss: 0.9312 - accuracy: 0.8564 - val_loss: 0.9418 - val_accuracy: 0.8907
Epoch 6/100
3/3 [==============================] - 0s 22ms/step - loss: 0.9448 - accuracy: 0.8427 - val_loss: 0.8355 - val_accuracy: 0.8852
Epoch 7/100
3/3 [==============================] - 0s 23ms/step - loss: 0.7820 - accuracy: 0.8482 - val_loss: 0.7390 - val_accuracy: 0.8306
Epoch 8/100
3/3 [==============================] - 0s 23ms/step - loss: 0.7054 - accuracy: 0.8509 - val_loss: 0.7093 - val_accuracy: 0.8689
Epoch 9/100
3/3 [==============================] - 0s 28ms/step - loss: 0.7249 - accuracy: 0.8728 - val_loss: 0.7705 - val_accuracy: 0.8579
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 0.6808 - accuracy: 0.8782 - val_loss: 0.6643 - val_accuracy: 0.8907
Epoch 11/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6376 - accuracy: 0.8632 - val_loss: 0.6662 - val_accuracy: 0.8361
Epoch 12/100
3/3 [==============================] - 0s 28ms/step - loss: 0.6259 - accuracy: 0.8659 - val_loss: 0.6288 - val_accuracy: 0.8579
Epoch 13/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5827 - accuracy: 0.8673 - val_loss: 0.5881 - val_accuracy: 0.8579
Epoch 14/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5711 - accuracy: 0.8646 - val_loss: 0.5720 - val_accuracy: 0.8579
Epoch 15/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5576 - accuracy: 0.8646 - val_loss: 0.5899 - val_accuracy: 0.8415
Epoch 16/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5577 - accuracy: 0.8454 - val_loss: 0.5635 - val_accuracy: 0.8361
Epoch 17/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5134 - accuracy: 0.8659 - val_loss: 0.5417 - val_accuracy: 0.8689
Epoch 18/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5156 - accuracy: 0.8509 - val_loss: 0.5286 - val_accuracy: 0.8525
Epoch 19/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5132 - accuracy: 0.8591 - val_loss: 0.5382 - val_accuracy: 0.8525
Epoch 20/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5229 - accuracy: 0.8536 - val_loss: 0.5276 - val_accuracy: 0.8470
Epoch 21/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5154 - accuracy: 0.8440 - val_loss: 0.5512 - val_accuracy: 0.8142
Epoch 22/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5003 - accuracy: 0.8523 - val_loss: 0.4972 - val_accuracy: 0.8798
Epoch 23/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4894 - accuracy: 0.8536 - val_loss: 0.4997 - val_accuracy: 0.8689
Epoch 24/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4779 - accuracy: 0.8714 - val_loss: 0.5104 - val_accuracy: 0.8579
Epoch 25/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4856 - accuracy: 0.8550 - val_loss: 0.4935 - val_accuracy: 0.8798
Epoch 26/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4602 - accuracy: 0.8659 - val_loss: 0.5026 - val_accuracy: 0.8361
Epoch 27/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4488 - accuracy: 0.8741 - val_loss: 0.4904 - val_accuracy: 0.8579
Epoch 28/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4528 - accuracy: 0.8700 - val_loss: 0.4811 - val_accuracy: 0.8689
Epoch 29/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4520 - accuracy: 0.8618 - val_loss: 0.5156 - val_accuracy: 0.8251
Epoch 30/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4485 - accuracy: 0.8632 - val_loss: 0.4835 - val_accuracy: 0.8634
Epoch 31/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4474 - accuracy: 0.8605 - val_loss: 0.5135 - val_accuracy: 0.8087
Epoch 32/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4461 - accuracy: 0.8632 - val_loss: 0.4569 - val_accuracy: 0.8743
Epoch 33/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4395 - accuracy: 0.8605 - val_loss: 0.4597 - val_accuracy: 0.8689
Epoch 34/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4550 - accuracy: 0.8646 - val_loss: 0.4865 - val_accuracy: 0.8361
Epoch 35/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4643 - accuracy: 0.8495 - val_loss: 0.4902 - val_accuracy: 0.8306
Epoch 36/100
3/3 [==============================] - 0s 29ms/step - loss: 0.4582 - accuracy: 0.8741 - val_loss: 0.5233 - val_accuracy: 0.8197
Epoch 37/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4604 - accuracy: 0.8577 - val_loss: 0.4935 - val_accuracy: 0.8743
Epoch 38/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4643 - accuracy: 0.8523 - val_loss: 0.5078 - val_accuracy: 0.8361
Epoch 39/100
3/3 [==============================] - 0s 28ms/step - loss: 0.4508 - accuracy: 0.8687 - val_loss: 0.4693 - val_accuracy: 0.8689
Epoch 40/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4614 - accuracy: 0.8591 - val_loss: 0.4711 - val_accuracy: 0.8852
Epoch 41/100
3/3 [==============================] - 0s 28ms/step - loss: 0.4589 - accuracy: 0.8714 - val_loss: 0.5060 - val_accuracy: 0.8306
Epoch 42/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4576 - accuracy: 0.8851 - val_loss: 0.4645 - val_accuracy: 0.8743
Epoch 43/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4652 - accuracy: 0.8509 - val_loss: 0.4968 - val_accuracy: 0.8197
Epoch 44/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4556 - accuracy: 0.8523 - val_loss: 0.5066 - val_accuracy: 0.8251
Epoch 45/100
3/3 [==============================] - 0s 30ms/step - loss: 0.4574 - accuracy: 0.8618 - val_loss: 0.4708 - val_accuracy: 0.8743
Epoch 46/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4662 - accuracy: 0.8536 - val_loss: 0.5309 - val_accuracy: 0.8087
Epoch 47/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4539 - accuracy: 0.8564 - val_loss: 0.5303 - val_accuracy: 0.8251
Epoch 48/100
3/3 [==============================] - 0s 29ms/step - loss: 0.4611 - accuracy: 0.8687 - val_loss: 0.4742 - val_accuracy: 0.8689
Epoch 49/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4569 - accuracy: 0.8700 - val_loss: 0.4727 - val_accuracy: 0.8525
Epoch 50/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4525 - accuracy: 0.8605 - val_loss: 0.4755 - val_accuracy: 0.8579
Epoch 51/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4657 - accuracy: 0.8564 - val_loss: 0.4832 - val_accuracy: 0.8470
Epoch 52/100
3/3 [==============================] - 0s 37ms/step - loss: 0.4462 - accuracy: 0.8700 - val_loss: 0.4984 - val_accuracy: 0.8251
Epoch 53/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4594 - accuracy: 0.8591 - val_loss: 0.4800 - val_accuracy: 0.8743
Epoch 54/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4502 - accuracy: 0.8550 - val_loss: 0.5051 - val_accuracy: 0.8251
Epoch 55/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4583 - accuracy: 0.8523 - val_loss: 0.4839 - val_accuracy: 0.8525
Epoch 56/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4754 - accuracy: 0.8673 - val_loss: 0.4962 - val_accuracy: 0.8634
Epoch 57/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4608 - accuracy: 0.8564 - val_loss: 0.5021 - val_accuracy: 0.8743
Epoch 58/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4748 - accuracy: 0.8673 - val_loss: 0.5261 - val_accuracy: 0.8361
Epoch 59/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4568 - accuracy: 0.8632 - val_loss: 0.5136 - val_accuracy: 0.8470
Epoch 60/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4695 - accuracy: 0.8673 - val_loss: 0.5321 - val_accuracy: 0.8634
Epoch 61/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4786 - accuracy: 0.8523 - val_loss: 0.5468 - val_accuracy: 0.8033
Epoch 62/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4738 - accuracy: 0.8468 - val_loss: 0.4888 - val_accuracy: 0.8743
Epoch 63/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4696 - accuracy: 0.8509 - val_loss: 0.5040 - val_accuracy: 0.8415
Epoch 64/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4639 - accuracy: 0.8632 - val_loss: 0.4978 - val_accuracy: 0.8306
Epoch 65/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4769 - accuracy: 0.8687 - val_loss: 0.4663 - val_accuracy: 0.9016
Epoch 66/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4814 - accuracy: 0.8495 - val_loss: 0.5014 - val_accuracy: 0.8361
Epoch 67/100
3/3 [==============================] - 0s 14ms/step - loss: 0.4646 - accuracy: 0.8550 - val_loss: 0.4775 - val_accuracy: 0.8634
Epoch 68/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4569 - accuracy: 0.8564 - val_loss: 0.4984 - val_accuracy: 0.8798
Epoch 69/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4834 - accuracy: 0.8618 - val_loss: 0.5293 - val_accuracy: 0.8415
Epoch 70/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4838 - accuracy: 0.8468 - val_loss: 0.4985 - val_accuracy: 0.8852
Epoch 71/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4616 - accuracy: 0.8523 - val_loss: 0.4902 - val_accuracy: 0.8798
Epoch 72/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4553 - accuracy: 0.8591 - val_loss: 0.4785 - val_accuracy: 0.8415
Epoch 73/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4564 - accuracy: 0.8618 - val_loss: 0.4631 - val_accuracy: 0.8852
Epoch 74/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4579 - accuracy: 0.8659 - val_loss: 0.4929 - val_accuracy: 0.8361
Epoch 75/100
3/3 [==============================] - 0s 14ms/step - loss: 0.4492 - accuracy: 0.8700 - val_loss: 0.4705 - val_accuracy: 0.8579
Epoch 76/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4645 - accuracy: 0.8564 - val_loss: 0.4625 - val_accuracy: 0.8852
Epoch 77/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4443 - accuracy: 0.8564 - val_loss: 0.4848 - val_accuracy: 0.8525
Epoch 78/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4483 - accuracy: 0.8673 - val_loss: 0.4968 - val_accuracy: 0.8415
Epoch 79/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4523 - accuracy: 0.8728 - val_loss: 0.4656 - val_accuracy: 0.8525
Epoch 80/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4626 - accuracy: 0.8536 - val_loss: 0.5135 - val_accuracy: 0.8470
Epoch 81/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4643 - accuracy: 0.8605 - val_loss: 0.5371 - val_accuracy: 0.8033
Epoch 82/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4876 - accuracy: 0.8440 - val_loss: 0.4916 - val_accuracy: 0.8907
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4618 - accuracy: 0.8523 - val_loss: 0.5421 - val_accuracy: 0.8087
Epoch 84/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4761 - accuracy: 0.8536 - val_loss: 0.5298 - val_accuracy: 0.8634
Epoch 85/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4867 - accuracy: 0.8605 - val_loss: 0.4900 - val_accuracy: 0.8852
Epoch 86/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4524 - accuracy: 0.8659 - val_loss: 0.4904 - val_accuracy: 0.8306
Epoch 87/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4728 - accuracy: 0.8564 - val_loss: 0.4755 - val_accuracy: 0.8579
Epoch 88/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4582 - accuracy: 0.8591 - val_loss: 0.4785 - val_accuracy: 0.8852
Epoch 89/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4648 - accuracy: 0.8618 - val_loss: 0.5227 - val_accuracy: 0.8197
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4682 - accuracy: 0.8618 - val_loss: 0.5069 - val_accuracy: 0.8852
Epoch 91/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4724 - accuracy: 0.8577 - val_loss: 0.5407 - val_accuracy: 0.8251
Epoch 92/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4500 - accuracy: 0.8687 - val_loss: 0.5018 - val_accuracy: 0.8634
Epoch 93/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4600 - accuracy: 0.8646 - val_loss: 0.4694 - val_accuracy: 0.8798
Epoch 94/100
3/3 [==============================] - 0s 29ms/step - loss: 0.4366 - accuracy: 0.8659 - val_loss: 0.4881 - val_accuracy: 0.8415
Epoch 95/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4635 - accuracy: 0.8673 - val_loss: 0.5030 - val_accuracy: 0.8361
Epoch 96/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4643 - accuracy: 0.8673 - val_loss: 0.5097 - val_accuracy: 0.8306
Epoch 97/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4717 - accuracy: 0.8659 - val_loss: 0.5001 - val_accuracy: 0.8579
Epoch 98/100
3/3 [==============================] - 0s 31ms/step - loss: 0.4651 - accuracy: 0.8523 - val_loss: 0.5216 - val_accuracy: 0.8525
Epoch 99/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4687 - accuracy: 0.8523 - val_loss: 0.5145 - val_accuracy: 0.8525
Epoch 100/100
3/3 [==============================] - 0s 15ms/step - loss: 0.4813 - accuracy: 0.8509 - val_loss: 0.5083 - val_accuracy: 0.8251
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 4, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None}
Batch size: 256
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
3/3 [==============================] - 1s 112ms/step - loss: 2.2266 - accuracy: 0.7445 - val_loss: 1.0965 - val_accuracy: 0.8626
Epoch 2/100
3/3 [==============================] - 0s 25ms/step - loss: 1.3381 - accuracy: 0.8470 - val_loss: 1.4391 - val_accuracy: 0.8681
Epoch 3/100
3/3 [==============================] - 0s 14ms/step - loss: 1.2854 - accuracy: 0.8566 - val_loss: 0.9345 - val_accuracy: 0.8626
Epoch 4/100
3/3 [==============================] - 0s 23ms/step - loss: 0.8942 - accuracy: 0.8579 - val_loss: 0.9102 - val_accuracy: 0.8571
Epoch 5/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9581 - accuracy: 0.8648 - val_loss: 0.9967 - val_accuracy: 0.8462
Epoch 6/100
3/3 [==============================] - 0s 16ms/step - loss: 0.9640 - accuracy: 0.8552 - val_loss: 0.8484 - val_accuracy: 0.8681
Epoch 7/100
3/3 [==============================] - 0s 23ms/step - loss: 0.8088 - accuracy: 0.8538 - val_loss: 0.6987 - val_accuracy: 0.8516
Epoch 8/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6894 - accuracy: 0.8648 - val_loss: 0.7166 - val_accuracy: 0.8571
Epoch 9/100
3/3 [==============================] - 0s 16ms/step - loss: 0.7264 - accuracy: 0.8634 - val_loss: 0.7038 - val_accuracy: 0.8571
Epoch 10/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6950 - accuracy: 0.8552 - val_loss: 0.6406 - val_accuracy: 0.8681
Epoch 11/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6278 - accuracy: 0.8607 - val_loss: 0.6136 - val_accuracy: 0.8516
Epoch 12/100
3/3 [==============================] - 0s 15ms/step - loss: 0.6243 - accuracy: 0.8607 - val_loss: 0.6021 - val_accuracy: 0.8462
Epoch 13/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5823 - accuracy: 0.8579 - val_loss: 0.5647 - val_accuracy: 0.8626
Epoch 14/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5652 - accuracy: 0.8607 - val_loss: 0.5612 - val_accuracy: 0.8736
Epoch 15/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5621 - accuracy: 0.8593 - val_loss: 0.5484 - val_accuracy: 0.8516
Epoch 16/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5291 - accuracy: 0.8757 - val_loss: 0.5452 - val_accuracy: 0.8626
Epoch 17/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5490 - accuracy: 0.8470 - val_loss: 0.5065 - val_accuracy: 0.8571
Epoch 18/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5233 - accuracy: 0.8552 - val_loss: 0.5225 - val_accuracy: 0.8626
Epoch 19/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5240 - accuracy: 0.8552 - val_loss: 0.5477 - val_accuracy: 0.8516
Epoch 20/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5231 - accuracy: 0.8484 - val_loss: 0.5084 - val_accuracy: 0.8352
Epoch 21/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5076 - accuracy: 0.8620 - val_loss: 0.5245 - val_accuracy: 0.8626
Epoch 22/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5159 - accuracy: 0.8484 - val_loss: 0.5000 - val_accuracy: 0.8571
Epoch 23/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4991 - accuracy: 0.8538 - val_loss: 0.4770 - val_accuracy: 0.8681
Epoch 24/100
3/3 [==============================] - 0s 37ms/step - loss: 0.4862 - accuracy: 0.8525 - val_loss: 0.5118 - val_accuracy: 0.8462
Epoch 25/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4975 - accuracy: 0.8620 - val_loss: 0.4954 - val_accuracy: 0.8462
Epoch 26/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4943 - accuracy: 0.8566 - val_loss: 0.5027 - val_accuracy: 0.8516
Epoch 27/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4811 - accuracy: 0.8552 - val_loss: 0.4701 - val_accuracy: 0.8681
Epoch 28/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4703 - accuracy: 0.8593 - val_loss: 0.4645 - val_accuracy: 0.8791
Epoch 29/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4757 - accuracy: 0.8607 - val_loss: 0.4595 - val_accuracy: 0.8626
Epoch 30/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4532 - accuracy: 0.8661 - val_loss: 0.4659 - val_accuracy: 0.8516
Epoch 31/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4663 - accuracy: 0.8593 - val_loss: 0.4853 - val_accuracy: 0.8681
Epoch 32/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4706 - accuracy: 0.8607 - val_loss: 0.4672 - val_accuracy: 0.8681
Epoch 33/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4751 - accuracy: 0.8497 - val_loss: 0.4753 - val_accuracy: 0.8516
Epoch 34/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4742 - accuracy: 0.8347 - val_loss: 0.4900 - val_accuracy: 0.8626
Epoch 35/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4520 - accuracy: 0.8511 - val_loss: 0.4583 - val_accuracy: 0.8571
Epoch 36/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4478 - accuracy: 0.8634 - val_loss: 0.4623 - val_accuracy: 0.8626
Epoch 37/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4529 - accuracy: 0.8716 - val_loss: 0.4508 - val_accuracy: 0.8626
Epoch 38/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4414 - accuracy: 0.8702 - val_loss: 0.4653 - val_accuracy: 0.8407
Epoch 39/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4494 - accuracy: 0.8620 - val_loss: 0.4652 - val_accuracy: 0.8626
Epoch 40/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4404 - accuracy: 0.8634 - val_loss: 0.4860 - val_accuracy: 0.8516
Epoch 41/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4488 - accuracy: 0.8648 - val_loss: 0.4501 - val_accuracy: 0.8736
Epoch 42/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4473 - accuracy: 0.8648 - val_loss: 0.4589 - val_accuracy: 0.8462
Epoch 43/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4408 - accuracy: 0.8689 - val_loss: 0.4676 - val_accuracy: 0.8626
Epoch 44/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4747 - accuracy: 0.8484 - val_loss: 0.4625 - val_accuracy: 0.8571
Epoch 45/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4837 - accuracy: 0.8566 - val_loss: 0.4662 - val_accuracy: 0.8516
Epoch 46/100
3/3 [==============================] - 0s 27ms/step - loss: 0.4935 - accuracy: 0.8415 - val_loss: 0.5470 - val_accuracy: 0.8626
Epoch 47/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4967 - accuracy: 0.8429 - val_loss: 0.4706 - val_accuracy: 0.8516
Epoch 48/100
3/3 [==============================] - 0s 16ms/step - loss: 0.4755 - accuracy: 0.8593 - val_loss: 0.4841 - val_accuracy: 0.8516
Epoch 49/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4803 - accuracy: 0.8689 - val_loss: 0.5034 - val_accuracy: 0.8571
Epoch 50/100
3/3 [==============================] - 0s 30ms/step - loss: 0.4793 - accuracy: 0.8497 - val_loss: 0.4701 - val_accuracy: 0.8571
Epoch 51/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4773 - accuracy: 0.8579 - val_loss: 0.4616 - val_accuracy: 0.8736
Epoch 52/100
3/3 [==============================] - 0s 24ms/step - loss: 0.4731 - accuracy: 0.8525 - val_loss: 0.4975 - val_accuracy: 0.8571
Epoch 53/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4723 - accuracy: 0.8511 - val_loss: 0.4755 - val_accuracy: 0.8681
Epoch 54/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4665 - accuracy: 0.8648 - val_loss: 0.4783 - val_accuracy: 0.8626
Epoch 55/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4657 - accuracy: 0.8497 - val_loss: 0.4802 - val_accuracy: 0.8681
Epoch 56/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4688 - accuracy: 0.8716 - val_loss: 0.4514 - val_accuracy: 0.8736
Epoch 57/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4666 - accuracy: 0.8743 - val_loss: 0.4787 - val_accuracy: 0.8571
Epoch 58/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4738 - accuracy: 0.8525 - val_loss: 0.4584 - val_accuracy: 0.8571
Epoch 59/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4840 - accuracy: 0.8579 - val_loss: 0.4889 - val_accuracy: 0.8626
Epoch 60/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4640 - accuracy: 0.8511 - val_loss: 0.4885 - val_accuracy: 0.8626
Epoch 61/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4601 - accuracy: 0.8552 - val_loss: 0.4687 - val_accuracy: 0.8516
Epoch 62/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4750 - accuracy: 0.8579 - val_loss: 0.4694 - val_accuracy: 0.8626
Epoch 63/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4781 - accuracy: 0.8306 - val_loss: 0.4684 - val_accuracy: 0.8571
Epoch 64/100
3/3 [==============================] - 0s 17ms/step - loss: 0.4586 - accuracy: 0.8620 - val_loss: 0.4918 - val_accuracy: 0.8626
Epoch 65/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4557 - accuracy: 0.8620 - val_loss: 0.4869 - val_accuracy: 0.8736
Epoch 66/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4675 - accuracy: 0.8607 - val_loss: 0.4747 - val_accuracy: 0.8626
Epoch 67/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4684 - accuracy: 0.8579 - val_loss: 0.4747 - val_accuracy: 0.8681
Epoch 68/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4610 - accuracy: 0.8716 - val_loss: 0.4838 - val_accuracy: 0.8516
Epoch 69/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4567 - accuracy: 0.8784 - val_loss: 0.4670 - val_accuracy: 0.8571
Epoch 70/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4698 - accuracy: 0.8675 - val_loss: 0.4624 - val_accuracy: 0.8681
Epoch 71/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4517 - accuracy: 0.8784 - val_loss: 0.4704 - val_accuracy: 0.8571
Epoch 72/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4695 - accuracy: 0.8702 - val_loss: 0.4784 - val_accuracy: 0.8571
Epoch 73/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4652 - accuracy: 0.8566 - val_loss: 0.4814 - val_accuracy: 0.8462
Epoch 74/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4713 - accuracy: 0.8511 - val_loss: 0.4621 - val_accuracy: 0.8791
Epoch 75/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4744 - accuracy: 0.8566 - val_loss: 0.5041 - val_accuracy: 0.8736
Epoch 76/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4681 - accuracy: 0.8702 - val_loss: 0.4771 - val_accuracy: 0.8681
Epoch 77/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4651 - accuracy: 0.8675 - val_loss: 0.4782 - val_accuracy: 0.8571
Epoch 78/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4654 - accuracy: 0.8552 - val_loss: 0.4736 - val_accuracy: 0.8462
Epoch 79/100
3/3 [==============================] - 0s 22ms/step - loss: 0.4689 - accuracy: 0.8716 - val_loss: 0.4871 - val_accuracy: 0.8626
Epoch 80/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4709 - accuracy: 0.8607 - val_loss: 0.4750 - val_accuracy: 0.8516
Epoch 81/100
3/3 [==============================] - 0s 25ms/step - loss: 0.4630 - accuracy: 0.8661 - val_loss: 0.4673 - val_accuracy: 0.8571
Epoch 82/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4544 - accuracy: 0.8689 - val_loss: 0.4937 - val_accuracy: 0.8681
Epoch 83/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4712 - accuracy: 0.8593 - val_loss: 0.4681 - val_accuracy: 0.8516
Epoch 84/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4708 - accuracy: 0.8620 - val_loss: 0.4842 - val_accuracy: 0.8571
Epoch 85/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5033 - accuracy: 0.8552 - val_loss: 0.4977 - val_accuracy: 0.8571
Epoch 86/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4871 - accuracy: 0.8429 - val_loss: 0.4853 - val_accuracy: 0.8462
Epoch 87/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4944 - accuracy: 0.8593 - val_loss: 0.4976 - val_accuracy: 0.8681
Epoch 88/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4952 - accuracy: 0.8443 - val_loss: 0.5169 - val_accuracy: 0.8626
Epoch 89/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4988 - accuracy: 0.8634 - val_loss: 0.4945 - val_accuracy: 0.8571
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4855 - accuracy: 0.8675 - val_loss: 0.5035 - val_accuracy: 0.8681
Epoch 91/100
3/3 [==============================] - 0s 23ms/step - loss: 0.4971 - accuracy: 0.8566 - val_loss: 0.4761 - val_accuracy: 0.8736
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 0.4763 - accuracy: 0.8607 - val_loss: 0.4880 - val_accuracy: 0.8681
Epoch 93/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4755 - accuracy: 0.8552 - val_loss: 0.4904 - val_accuracy: 0.8516
Epoch 94/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5011 - accuracy: 0.8552 - val_loss: 0.4790 - val_accuracy: 0.8626
Epoch 95/100
3/3 [==============================] - 0s 18ms/step - loss: 0.4753 - accuracy: 0.8675 - val_loss: 0.4832 - val_accuracy: 0.8626
Epoch 96/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4684 - accuracy: 0.8552 - val_loss: 0.4674 - val_accuracy: 0.8736
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4668 - accuracy: 0.8566 - val_loss: 0.4718 - val_accuracy: 0.8462
Epoch 98/100
3/3 [==============================] - 0s 21ms/step - loss: 0.4561 - accuracy: 0.8689 - val_loss: 0.4847 - val_accuracy: 0.8626
Epoch 99/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4624 - accuracy: 0.8579 - val_loss: 0.4609 - val_accuracy: 0.8681
Epoch 100/100
3/3 [==============================] - 0s 19ms/step - loss: 0.4516 - accuracy: 0.8634 - val_loss: 0.4728 - val_accuracy: 0.8626
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 4ms/step
Experiment number: 4
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 8, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 244ms/step - loss: 1.8214 - accuracy: 0.6799 - val_loss: 1.8201 - val_accuracy: 0.7322
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8313 - accuracy: 0.6703 - val_loss: 1.8192 - val_accuracy: 0.7322
Epoch 3/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8214 - accuracy: 0.6785 - val_loss: 1.8185 - val_accuracy: 0.7322
Epoch 4/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8184 - accuracy: 0.6936 - val_loss: 1.8179 - val_accuracy: 0.7322
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8103 - accuracy: 0.6717 - val_loss: 1.8173 - val_accuracy: 0.7377
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8154 - accuracy: 0.6936 - val_loss: 1.8168 - val_accuracy: 0.7377
Epoch 7/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8129 - accuracy: 0.6881 - val_loss: 1.8164 - val_accuracy: 0.7377
Epoch 8/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8170 - accuracy: 0.6731 - val_loss: 1.8159 - val_accuracy: 0.7432
Epoch 9/100
2/2 [==============================] - 0s 23ms/step - loss: 1.8091 - accuracy: 0.6908 - val_loss: 1.8155 - val_accuracy: 0.7432
Epoch 10/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8144 - accuracy: 0.6963 - val_loss: 1.8151 - val_accuracy: 0.7432
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8123 - accuracy: 0.6949 - val_loss: 1.8147 - val_accuracy: 0.7432
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8151 - accuracy: 0.6799 - val_loss: 1.8144 - val_accuracy: 0.7432
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8108 - accuracy: 0.7045 - val_loss: 1.8140 - val_accuracy: 0.7432
Epoch 14/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8204 - accuracy: 0.6785 - val_loss: 1.8137 - val_accuracy: 0.7486
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8019 - accuracy: 0.7045 - val_loss: 1.8134 - val_accuracy: 0.7486
Epoch 16/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8110 - accuracy: 0.6826 - val_loss: 1.8130 - val_accuracy: 0.7486
Epoch 17/100
2/2 [==============================] - 0s 30ms/step - loss: 1.8095 - accuracy: 0.7100 - val_loss: 1.8127 - val_accuracy: 0.7486
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8208 - accuracy: 0.6826 - val_loss: 1.8124 - val_accuracy: 0.7486
Epoch 19/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8090 - accuracy: 0.6895 - val_loss: 1.8121 - val_accuracy: 0.7486
Epoch 20/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8068 - accuracy: 0.6840 - val_loss: 1.8118 - val_accuracy: 0.7486
Epoch 21/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8037 - accuracy: 0.6922 - val_loss: 1.8116 - val_accuracy: 0.7486
Epoch 22/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8110 - accuracy: 0.6826 - val_loss: 1.8113 - val_accuracy: 0.7486
Epoch 23/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8163 - accuracy: 0.6758 - val_loss: 1.8110 - val_accuracy: 0.7486
Epoch 24/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8028 - accuracy: 0.6977 - val_loss: 1.8107 - val_accuracy: 0.7486
Epoch 25/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8078 - accuracy: 0.7031 - val_loss: 1.8105 - val_accuracy: 0.7486
Epoch 26/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8151 - accuracy: 0.6949 - val_loss: 1.8102 - val_accuracy: 0.7486
Epoch 27/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8110 - accuracy: 0.7045 - val_loss: 1.8100 - val_accuracy: 0.7486
Epoch 28/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8166 - accuracy: 0.6772 - val_loss: 1.8097 - val_accuracy: 0.7486
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8158 - accuracy: 0.6840 - val_loss: 1.8095 - val_accuracy: 0.7486
Epoch 30/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8091 - accuracy: 0.6840 - val_loss: 1.8092 - val_accuracy: 0.7486
Epoch 31/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8039 - accuracy: 0.7059 - val_loss: 1.8090 - val_accuracy: 0.7486
Epoch 32/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8148 - accuracy: 0.6922 - val_loss: 1.8087 - val_accuracy: 0.7486
Epoch 33/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8232 - accuracy: 0.6758 - val_loss: 1.8085 - val_accuracy: 0.7486
Epoch 34/100
2/2 [==============================] - 0s 30ms/step - loss: 1.8070 - accuracy: 0.6758 - val_loss: 1.8083 - val_accuracy: 0.7486
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8153 - accuracy: 0.6867 - val_loss: 1.8080 - val_accuracy: 0.7432
Epoch 36/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8069 - accuracy: 0.6881 - val_loss: 1.8078 - val_accuracy: 0.7432
Epoch 37/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8150 - accuracy: 0.6799 - val_loss: 1.8076 - val_accuracy: 0.7432
Epoch 38/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8081 - accuracy: 0.7045 - val_loss: 1.8073 - val_accuracy: 0.7432
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7982 - accuracy: 0.6758 - val_loss: 1.8071 - val_accuracy: 0.7432
Epoch 40/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8117 - accuracy: 0.6936 - val_loss: 1.8069 - val_accuracy: 0.7432
Epoch 41/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8124 - accuracy: 0.7004 - val_loss: 1.8067 - val_accuracy: 0.7432
Epoch 42/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8040 - accuracy: 0.6826 - val_loss: 1.8065 - val_accuracy: 0.7377
Epoch 43/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8022 - accuracy: 0.6936 - val_loss: 1.8063 - val_accuracy: 0.7377
Epoch 44/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8033 - accuracy: 0.6949 - val_loss: 1.8060 - val_accuracy: 0.7377
Epoch 45/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8015 - accuracy: 0.7059 - val_loss: 1.8058 - val_accuracy: 0.7377
Epoch 46/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8021 - accuracy: 0.6936 - val_loss: 1.8056 - val_accuracy: 0.7377
Epoch 47/100
2/2 [==============================] - 0s 29ms/step - loss: 1.7978 - accuracy: 0.6758 - val_loss: 1.8054 - val_accuracy: 0.7377
Epoch 48/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8053 - accuracy: 0.6772 - val_loss: 1.8052 - val_accuracy: 0.7322
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8041 - accuracy: 0.6908 - val_loss: 1.8050 - val_accuracy: 0.7322
Epoch 50/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8076 - accuracy: 0.6922 - val_loss: 1.8048 - val_accuracy: 0.7322
Epoch 51/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8063 - accuracy: 0.6922 - val_loss: 1.8046 - val_accuracy: 0.7322
Epoch 52/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7967 - accuracy: 0.7018 - val_loss: 1.8044 - val_accuracy: 0.7322
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8048 - accuracy: 0.6826 - val_loss: 1.8042 - val_accuracy: 0.7322
Epoch 54/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8083 - accuracy: 0.6881 - val_loss: 1.8040 - val_accuracy: 0.7322
Epoch 55/100
2/2 [==============================] - 0s 25ms/step - loss: 1.8006 - accuracy: 0.7031 - val_loss: 1.8038 - val_accuracy: 0.7322
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7971 - accuracy: 0.7004 - val_loss: 1.8036 - val_accuracy: 0.7322
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8021 - accuracy: 0.6963 - val_loss: 1.8034 - val_accuracy: 0.7322
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8031 - accuracy: 0.6881 - val_loss: 1.8032 - val_accuracy: 0.7322
Epoch 59/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7980 - accuracy: 0.6867 - val_loss: 1.8030 - val_accuracy: 0.7322
Epoch 60/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8017 - accuracy: 0.6813 - val_loss: 1.8028 - val_accuracy: 0.7322
Epoch 61/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7909 - accuracy: 0.6977 - val_loss: 1.8026 - val_accuracy: 0.7322
Epoch 62/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8025 - accuracy: 0.6881 - val_loss: 1.8024 - val_accuracy: 0.7322
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7896 - accuracy: 0.6854 - val_loss: 1.8022 - val_accuracy: 0.7322
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7970 - accuracy: 0.7100 - val_loss: 1.8020 - val_accuracy: 0.7322
Epoch 65/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7876 - accuracy: 0.6949 - val_loss: 1.8018 - val_accuracy: 0.7322
Epoch 66/100
2/2 [==============================] - 0s 51ms/step - loss: 1.8083 - accuracy: 0.6936 - val_loss: 1.8016 - val_accuracy: 0.7322
Epoch 67/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7961 - accuracy: 0.7004 - val_loss: 1.8014 - val_accuracy: 0.7322
Epoch 68/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7973 - accuracy: 0.6949 - val_loss: 1.8013 - val_accuracy: 0.7322
Epoch 69/100
2/2 [==============================] - 0s 44ms/step - loss: 1.8037 - accuracy: 0.6758 - val_loss: 1.8011 - val_accuracy: 0.7322
Epoch 70/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7968 - accuracy: 0.7114 - val_loss: 1.8009 - val_accuracy: 0.7322
Epoch 71/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8034 - accuracy: 0.6922 - val_loss: 1.8007 - val_accuracy: 0.7322
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 1.8213 - accuracy: 0.6826 - val_loss: 1.8005 - val_accuracy: 0.7322
Epoch 73/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8074 - accuracy: 0.6826 - val_loss: 1.8003 - val_accuracy: 0.7322
Epoch 74/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8034 - accuracy: 0.6895 - val_loss: 1.8001 - val_accuracy: 0.7322
Epoch 75/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7954 - accuracy: 0.7045 - val_loss: 1.7999 - val_accuracy: 0.7322
Epoch 76/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7982 - accuracy: 0.6922 - val_loss: 1.7998 - val_accuracy: 0.7322
Epoch 77/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7930 - accuracy: 0.6908 - val_loss: 1.7996 - val_accuracy: 0.7322
Epoch 78/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8100 - accuracy: 0.6881 - val_loss: 1.7994 - val_accuracy: 0.7322
Epoch 79/100
2/2 [==============================] - 0s 47ms/step - loss: 1.8012 - accuracy: 0.6990 - val_loss: 1.7992 - val_accuracy: 0.7322
Epoch 80/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7968 - accuracy: 0.6936 - val_loss: 1.7990 - val_accuracy: 0.7322
Epoch 81/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7977 - accuracy: 0.6990 - val_loss: 1.7988 - val_accuracy: 0.7322
Epoch 82/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8002 - accuracy: 0.6990 - val_loss: 1.7987 - val_accuracy: 0.7322
Epoch 83/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7877 - accuracy: 0.6854 - val_loss: 1.7985 - val_accuracy: 0.7322
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8064 - accuracy: 0.6990 - val_loss: 1.7983 - val_accuracy: 0.7322
Epoch 85/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8016 - accuracy: 0.6977 - val_loss: 1.7981 - val_accuracy: 0.7322
Epoch 86/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7959 - accuracy: 0.7045 - val_loss: 1.7979 - val_accuracy: 0.7322
Epoch 87/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7917 - accuracy: 0.6963 - val_loss: 1.7978 - val_accuracy: 0.7322
Epoch 88/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8085 - accuracy: 0.6731 - val_loss: 1.7976 - val_accuracy: 0.7322
Epoch 89/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7962 - accuracy: 0.7004 - val_loss: 1.7974 - val_accuracy: 0.7322
Epoch 90/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7893 - accuracy: 0.7073 - val_loss: 1.7972 - val_accuracy: 0.7322
Epoch 91/100
2/2 [==============================] - 0s 29ms/step - loss: 1.7886 - accuracy: 0.6990 - val_loss: 1.7971 - val_accuracy: 0.7322
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7934 - accuracy: 0.6854 - val_loss: 1.7969 - val_accuracy: 0.7322
Epoch 93/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7949 - accuracy: 0.6977 - val_loss: 1.7967 - val_accuracy: 0.7322
Epoch 94/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7917 - accuracy: 0.6922 - val_loss: 1.7965 - val_accuracy: 0.7322
Epoch 95/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7984 - accuracy: 0.6977 - val_loss: 1.7963 - val_accuracy: 0.7322
Epoch 96/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7997 - accuracy: 0.7045 - val_loss: 1.7962 - val_accuracy: 0.7322
Epoch 97/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7914 - accuracy: 0.7045 - val_loss: 1.7960 - val_accuracy: 0.7322
Epoch 98/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7932 - accuracy: 0.6895 - val_loss: 1.7958 - val_accuracy: 0.7322
Epoch 99/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7885 - accuracy: 0.6922 - val_loss: 1.7956 - val_accuracy: 0.7322
Epoch 100/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7967 - accuracy: 0.6854 - val_loss: 1.7955 - val_accuracy: 0.7322
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 8, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 295ms/step - loss: 1.9593 - accuracy: 0.4008 - val_loss: 1.9495 - val_accuracy: 0.3989
Epoch 2/100
2/2 [==============================] - 0s 51ms/step - loss: 1.9603 - accuracy: 0.4337 - val_loss: 1.9485 - val_accuracy: 0.3989
Epoch 3/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9358 - accuracy: 0.4008 - val_loss: 1.9478 - val_accuracy: 0.3989
Epoch 4/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9336 - accuracy: 0.4200 - val_loss: 1.9471 - val_accuracy: 0.3989
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9384 - accuracy: 0.4514 - val_loss: 1.9466 - val_accuracy: 0.3989
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9388 - accuracy: 0.4364 - val_loss: 1.9460 - val_accuracy: 0.3989
Epoch 7/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9596 - accuracy: 0.4350 - val_loss: 1.9456 - val_accuracy: 0.3989
Epoch 8/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9450 - accuracy: 0.4186 - val_loss: 1.9451 - val_accuracy: 0.3989
Epoch 9/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9435 - accuracy: 0.4295 - val_loss: 1.9447 - val_accuracy: 0.3989
Epoch 10/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9574 - accuracy: 0.4309 - val_loss: 1.9443 - val_accuracy: 0.3989
Epoch 11/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9212 - accuracy: 0.4405 - val_loss: 1.9439 - val_accuracy: 0.3989
Epoch 12/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9534 - accuracy: 0.4350 - val_loss: 1.9435 - val_accuracy: 0.3989
Epoch 13/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9333 - accuracy: 0.4610 - val_loss: 1.9431 - val_accuracy: 0.3989
Epoch 14/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9343 - accuracy: 0.4118 - val_loss: 1.9428 - val_accuracy: 0.3989
Epoch 15/100
2/2 [==============================] - 0s 28ms/step - loss: 1.9458 - accuracy: 0.4241 - val_loss: 1.9424 - val_accuracy: 0.4044
Epoch 16/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9268 - accuracy: 0.4282 - val_loss: 1.9421 - val_accuracy: 0.4044
Epoch 17/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9467 - accuracy: 0.4555 - val_loss: 1.9418 - val_accuracy: 0.4044
Epoch 18/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9307 - accuracy: 0.4337 - val_loss: 1.9415 - val_accuracy: 0.4044
Epoch 19/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9410 - accuracy: 0.4419 - val_loss: 1.9412 - val_accuracy: 0.4044
Epoch 20/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9354 - accuracy: 0.4378 - val_loss: 1.9409 - val_accuracy: 0.4044
Epoch 21/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9443 - accuracy: 0.4405 - val_loss: 1.9406 - val_accuracy: 0.4044
Epoch 22/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9380 - accuracy: 0.4200 - val_loss: 1.9403 - val_accuracy: 0.4044
Epoch 23/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9470 - accuracy: 0.4350 - val_loss: 1.9400 - val_accuracy: 0.4098
Epoch 24/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9283 - accuracy: 0.4282 - val_loss: 1.9397 - val_accuracy: 0.4098
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9207 - accuracy: 0.4596 - val_loss: 1.9395 - val_accuracy: 0.4098
Epoch 26/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9478 - accuracy: 0.4323 - val_loss: 1.9392 - val_accuracy: 0.4098
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9367 - accuracy: 0.4131 - val_loss: 1.9389 - val_accuracy: 0.4098
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9229 - accuracy: 0.4378 - val_loss: 1.9386 - val_accuracy: 0.4098
Epoch 29/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9305 - accuracy: 0.4364 - val_loss: 1.9384 - val_accuracy: 0.4098
Epoch 30/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9270 - accuracy: 0.4583 - val_loss: 1.9381 - val_accuracy: 0.4098
Epoch 31/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9362 - accuracy: 0.4378 - val_loss: 1.9379 - val_accuracy: 0.4098
Epoch 32/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9275 - accuracy: 0.4432 - val_loss: 1.9376 - val_accuracy: 0.4098
Epoch 33/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9355 - accuracy: 0.4405 - val_loss: 1.9374 - val_accuracy: 0.4153
Epoch 34/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9355 - accuracy: 0.4364 - val_loss: 1.9371 - val_accuracy: 0.4153
Epoch 35/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9591 - accuracy: 0.4090 - val_loss: 1.9369 - val_accuracy: 0.4153
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9032 - accuracy: 0.4528 - val_loss: 1.9367 - val_accuracy: 0.4153
Epoch 37/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9232 - accuracy: 0.4555 - val_loss: 1.9364 - val_accuracy: 0.4153
Epoch 38/100
2/2 [==============================] - 0s 49ms/step - loss: 1.9500 - accuracy: 0.4213 - val_loss: 1.9362 - val_accuracy: 0.4153
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9440 - accuracy: 0.4514 - val_loss: 1.9359 - val_accuracy: 0.4153
Epoch 40/100
2/2 [==============================] - 0s 29ms/step - loss: 1.9182 - accuracy: 0.4350 - val_loss: 1.9357 - val_accuracy: 0.4153
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9452 - accuracy: 0.4227 - val_loss: 1.9355 - val_accuracy: 0.4153
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9476 - accuracy: 0.4542 - val_loss: 1.9352 - val_accuracy: 0.4153
Epoch 43/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9214 - accuracy: 0.4446 - val_loss: 1.9350 - val_accuracy: 0.4153
Epoch 44/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9212 - accuracy: 0.4555 - val_loss: 1.9348 - val_accuracy: 0.4153
Epoch 45/100
2/2 [==============================] - 0s 29ms/step - loss: 1.9308 - accuracy: 0.4350 - val_loss: 1.9346 - val_accuracy: 0.4153
Epoch 46/100
2/2 [==============================] - 0s 33ms/step - loss: 1.9402 - accuracy: 0.4213 - val_loss: 1.9344 - val_accuracy: 0.4153
Epoch 47/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9225 - accuracy: 0.4432 - val_loss: 1.9341 - val_accuracy: 0.4153
Epoch 48/100
2/2 [==============================] - 0s 26ms/step - loss: 1.9355 - accuracy: 0.4268 - val_loss: 1.9339 - val_accuracy: 0.4153
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9271 - accuracy: 0.4378 - val_loss: 1.9337 - val_accuracy: 0.4153
Epoch 50/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9411 - accuracy: 0.4186 - val_loss: 1.9335 - val_accuracy: 0.4153
Epoch 51/100
2/2 [==============================] - 0s 27ms/step - loss: 1.9508 - accuracy: 0.4419 - val_loss: 1.9333 - val_accuracy: 0.4153
Epoch 52/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9337 - accuracy: 0.4514 - val_loss: 1.9331 - val_accuracy: 0.4153
Epoch 53/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9277 - accuracy: 0.4364 - val_loss: 1.9328 - val_accuracy: 0.4208
Epoch 54/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9441 - accuracy: 0.4350 - val_loss: 1.9326 - val_accuracy: 0.4208
Epoch 55/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9276 - accuracy: 0.4514 - val_loss: 1.9324 - val_accuracy: 0.4208
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9547 - accuracy: 0.4487 - val_loss: 1.9322 - val_accuracy: 0.4208
Epoch 57/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9203 - accuracy: 0.4542 - val_loss: 1.9320 - val_accuracy: 0.4208
Epoch 58/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9404 - accuracy: 0.4254 - val_loss: 1.9318 - val_accuracy: 0.4208
Epoch 59/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9057 - accuracy: 0.4596 - val_loss: 1.9316 - val_accuracy: 0.4208
Epoch 60/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9193 - accuracy: 0.4569 - val_loss: 1.9314 - val_accuracy: 0.4208
Epoch 61/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9499 - accuracy: 0.4227 - val_loss: 1.9312 - val_accuracy: 0.4208
Epoch 62/100
2/2 [==============================] - 0s 55ms/step - loss: 1.9393 - accuracy: 0.4501 - val_loss: 1.9310 - val_accuracy: 0.4208
Epoch 63/100
2/2 [==============================] - 0s 61ms/step - loss: 1.9080 - accuracy: 0.4747 - val_loss: 1.9308 - val_accuracy: 0.4262
Epoch 64/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9407 - accuracy: 0.4391 - val_loss: 1.9306 - val_accuracy: 0.4208
Epoch 65/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9096 - accuracy: 0.4583 - val_loss: 1.9304 - val_accuracy: 0.4208
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9156 - accuracy: 0.4624 - val_loss: 1.9302 - val_accuracy: 0.4208
Epoch 67/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9416 - accuracy: 0.4473 - val_loss: 1.9300 - val_accuracy: 0.4208
Epoch 68/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9270 - accuracy: 0.4610 - val_loss: 1.9298 - val_accuracy: 0.4208
Epoch 69/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9473 - accuracy: 0.4241 - val_loss: 1.9296 - val_accuracy: 0.4208
Epoch 70/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9194 - accuracy: 0.4514 - val_loss: 1.9294 - val_accuracy: 0.4208
Epoch 71/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9260 - accuracy: 0.4542 - val_loss: 1.9292 - val_accuracy: 0.4208
Epoch 72/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9323 - accuracy: 0.4391 - val_loss: 1.9290 - val_accuracy: 0.4262
Epoch 73/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9223 - accuracy: 0.4391 - val_loss: 1.9288 - val_accuracy: 0.4262
Epoch 74/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9275 - accuracy: 0.4337 - val_loss: 1.9286 - val_accuracy: 0.4262
Epoch 75/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9437 - accuracy: 0.4419 - val_loss: 1.9284 - val_accuracy: 0.4262
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9209 - accuracy: 0.4583 - val_loss: 1.9282 - val_accuracy: 0.4262
Epoch 77/100
2/2 [==============================] - 0s 28ms/step - loss: 1.9390 - accuracy: 0.4460 - val_loss: 1.9280 - val_accuracy: 0.4262
Epoch 78/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9313 - accuracy: 0.4528 - val_loss: 1.9278 - val_accuracy: 0.4262
Epoch 79/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9117 - accuracy: 0.4542 - val_loss: 1.9276 - val_accuracy: 0.4262
Epoch 80/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9152 - accuracy: 0.4596 - val_loss: 1.9274 - val_accuracy: 0.4262
Epoch 81/100
2/2 [==============================] - 0s 51ms/step - loss: 1.9247 - accuracy: 0.4720 - val_loss: 1.9273 - val_accuracy: 0.4262
Epoch 82/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9286 - accuracy: 0.4350 - val_loss: 1.9271 - val_accuracy: 0.4262
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9175 - accuracy: 0.4542 - val_loss: 1.9269 - val_accuracy: 0.4262
Epoch 84/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9113 - accuracy: 0.4720 - val_loss: 1.9267 - val_accuracy: 0.4262
Epoch 85/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9205 - accuracy: 0.4419 - val_loss: 1.9265 - val_accuracy: 0.4262
Epoch 86/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9199 - accuracy: 0.4309 - val_loss: 1.9263 - val_accuracy: 0.4262
Epoch 87/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9343 - accuracy: 0.4405 - val_loss: 1.9261 - val_accuracy: 0.4262
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9009 - accuracy: 0.4446 - val_loss: 1.9259 - val_accuracy: 0.4262
Epoch 89/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9345 - accuracy: 0.4542 - val_loss: 1.9257 - val_accuracy: 0.4262
Epoch 90/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9135 - accuracy: 0.4514 - val_loss: 1.9256 - val_accuracy: 0.4262
Epoch 91/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9516 - accuracy: 0.4391 - val_loss: 1.9254 - val_accuracy: 0.4262
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9413 - accuracy: 0.4446 - val_loss: 1.9252 - val_accuracy: 0.4262
Epoch 93/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9334 - accuracy: 0.4391 - val_loss: 1.9250 - val_accuracy: 0.4262
Epoch 94/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9207 - accuracy: 0.4391 - val_loss: 1.9248 - val_accuracy: 0.4262
Epoch 95/100
2/2 [==============================] - 0s 30ms/step - loss: 1.9406 - accuracy: 0.4405 - val_loss: 1.9246 - val_accuracy: 0.4317
Epoch 96/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9287 - accuracy: 0.4528 - val_loss: 1.9244 - val_accuracy: 0.4317
Epoch 97/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9064 - accuracy: 0.4679 - val_loss: 1.9243 - val_accuracy: 0.4317
Epoch 98/100
2/2 [==============================] - 0s 49ms/step - loss: 1.9400 - accuracy: 0.4309 - val_loss: 1.9241 - val_accuracy: 0.4317
Epoch 99/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9351 - accuracy: 0.4364 - val_loss: 1.9239 - val_accuracy: 0.4317
Epoch 100/100
2/2 [==============================] - 0s 45ms/step - loss: 1.9328 - accuracy: 0.4309 - val_loss: 1.9237 - val_accuracy: 0.4317
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 8, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 233ms/step - loss: 1.8516 - accuracy: 0.3967 - val_loss: 1.7853 - val_accuracy: 0.5464
Epoch 2/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8397 - accuracy: 0.4008 - val_loss: 1.7843 - val_accuracy: 0.5464
Epoch 3/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8328 - accuracy: 0.4090 - val_loss: 1.7836 - val_accuracy: 0.5464
Epoch 4/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8447 - accuracy: 0.4323 - val_loss: 1.7830 - val_accuracy: 0.5464
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8533 - accuracy: 0.4090 - val_loss: 1.7824 - val_accuracy: 0.5464
Epoch 6/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8462 - accuracy: 0.4104 - val_loss: 1.7819 - val_accuracy: 0.5464
Epoch 7/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8370 - accuracy: 0.4227 - val_loss: 1.7814 - val_accuracy: 0.5464
Epoch 8/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8320 - accuracy: 0.4241 - val_loss: 1.7810 - val_accuracy: 0.5464
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8380 - accuracy: 0.4131 - val_loss: 1.7805 - val_accuracy: 0.5464
Epoch 10/100
2/2 [==============================] - 0s 26ms/step - loss: 1.8320 - accuracy: 0.4090 - val_loss: 1.7801 - val_accuracy: 0.5464
Epoch 11/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8429 - accuracy: 0.4090 - val_loss: 1.7798 - val_accuracy: 0.5464
Epoch 12/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8296 - accuracy: 0.4378 - val_loss: 1.7794 - val_accuracy: 0.5464
Epoch 13/100
2/2 [==============================] - 0s 25ms/step - loss: 1.8412 - accuracy: 0.4159 - val_loss: 1.7790 - val_accuracy: 0.5464
Epoch 14/100
2/2 [==============================] - 0s 48ms/step - loss: 1.8419 - accuracy: 0.4049 - val_loss: 1.7787 - val_accuracy: 0.5464
Epoch 15/100
2/2 [==============================] - 0s 50ms/step - loss: 1.8391 - accuracy: 0.4282 - val_loss: 1.7783 - val_accuracy: 0.5464
Epoch 16/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8316 - accuracy: 0.4282 - val_loss: 1.7780 - val_accuracy: 0.5464
Epoch 17/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8388 - accuracy: 0.4118 - val_loss: 1.7777 - val_accuracy: 0.5464
Epoch 18/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8314 - accuracy: 0.4337 - val_loss: 1.7774 - val_accuracy: 0.5464
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8346 - accuracy: 0.4227 - val_loss: 1.7771 - val_accuracy: 0.5464
Epoch 20/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8314 - accuracy: 0.4131 - val_loss: 1.7768 - val_accuracy: 0.5464
Epoch 21/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8326 - accuracy: 0.4254 - val_loss: 1.7765 - val_accuracy: 0.5464
Epoch 22/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8258 - accuracy: 0.4309 - val_loss: 1.7762 - val_accuracy: 0.5464
Epoch 23/100
2/2 [==============================] - 0s 28ms/step - loss: 1.8393 - accuracy: 0.4104 - val_loss: 1.7759 - val_accuracy: 0.5464
Epoch 24/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8274 - accuracy: 0.4446 - val_loss: 1.7757 - val_accuracy: 0.5464
Epoch 25/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8466 - accuracy: 0.3858 - val_loss: 1.7754 - val_accuracy: 0.5464
Epoch 26/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8300 - accuracy: 0.4391 - val_loss: 1.7751 - val_accuracy: 0.5464
Epoch 27/100
2/2 [==============================] - 0s 26ms/step - loss: 1.8354 - accuracy: 0.4131 - val_loss: 1.7749 - val_accuracy: 0.5464
Epoch 28/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8416 - accuracy: 0.4022 - val_loss: 1.7746 - val_accuracy: 0.5464
Epoch 29/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8292 - accuracy: 0.4268 - val_loss: 1.7743 - val_accuracy: 0.5464
Epoch 30/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8400 - accuracy: 0.4159 - val_loss: 1.7741 - val_accuracy: 0.5464
Epoch 31/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8338 - accuracy: 0.4077 - val_loss: 1.7738 - val_accuracy: 0.5464
Epoch 32/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8384 - accuracy: 0.4063 - val_loss: 1.7736 - val_accuracy: 0.5464
Epoch 33/100
2/2 [==============================] - 0s 50ms/step - loss: 1.8345 - accuracy: 0.3967 - val_loss: 1.7734 - val_accuracy: 0.5464
Epoch 34/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8306 - accuracy: 0.4104 - val_loss: 1.7731 - val_accuracy: 0.5464
Epoch 35/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8210 - accuracy: 0.4227 - val_loss: 1.7729 - val_accuracy: 0.5464
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8255 - accuracy: 0.4213 - val_loss: 1.7726 - val_accuracy: 0.5464
Epoch 37/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8298 - accuracy: 0.4309 - val_loss: 1.7724 - val_accuracy: 0.5464
Epoch 38/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8228 - accuracy: 0.4391 - val_loss: 1.7722 - val_accuracy: 0.5464
Epoch 39/100
2/2 [==============================] - 0s 30ms/step - loss: 1.8210 - accuracy: 0.4186 - val_loss: 1.7719 - val_accuracy: 0.5464
Epoch 40/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8316 - accuracy: 0.4172 - val_loss: 1.7717 - val_accuracy: 0.5464
Epoch 41/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8452 - accuracy: 0.4090 - val_loss: 1.7715 - val_accuracy: 0.5464
Epoch 42/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8333 - accuracy: 0.4186 - val_loss: 1.7713 - val_accuracy: 0.5464
Epoch 43/100
2/2 [==============================] - 0s 29ms/step - loss: 1.8209 - accuracy: 0.4227 - val_loss: 1.7710 - val_accuracy: 0.5464
Epoch 44/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8305 - accuracy: 0.4104 - val_loss: 1.7708 - val_accuracy: 0.5464
Epoch 45/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8255 - accuracy: 0.4337 - val_loss: 1.7706 - val_accuracy: 0.5464
Epoch 46/100
2/2 [==============================] - 0s 31ms/step - loss: 1.8383 - accuracy: 0.4200 - val_loss: 1.7704 - val_accuracy: 0.5464
Epoch 47/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8290 - accuracy: 0.4295 - val_loss: 1.7702 - val_accuracy: 0.5464
Epoch 48/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8246 - accuracy: 0.4254 - val_loss: 1.7700 - val_accuracy: 0.5464
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8183 - accuracy: 0.4227 - val_loss: 1.7698 - val_accuracy: 0.5464
Epoch 50/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8241 - accuracy: 0.4323 - val_loss: 1.7696 - val_accuracy: 0.5464
Epoch 51/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8186 - accuracy: 0.4391 - val_loss: 1.7693 - val_accuracy: 0.5464
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8316 - accuracy: 0.4145 - val_loss: 1.7691 - val_accuracy: 0.5464
Epoch 53/100
2/2 [==============================] - 0s 46ms/step - loss: 1.8224 - accuracy: 0.4295 - val_loss: 1.7689 - val_accuracy: 0.5464
Epoch 54/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8244 - accuracy: 0.4419 - val_loss: 1.7687 - val_accuracy: 0.5464
Epoch 55/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8254 - accuracy: 0.4282 - val_loss: 1.7685 - val_accuracy: 0.5464
Epoch 56/100
2/2 [==============================] - 0s 49ms/step - loss: 1.8231 - accuracy: 0.4282 - val_loss: 1.7683 - val_accuracy: 0.5464
Epoch 57/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8216 - accuracy: 0.4118 - val_loss: 1.7681 - val_accuracy: 0.5464
Epoch 58/100
2/2 [==============================] - 0s 31ms/step - loss: 1.8321 - accuracy: 0.4159 - val_loss: 1.7679 - val_accuracy: 0.5464
Epoch 59/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8206 - accuracy: 0.4227 - val_loss: 1.7677 - val_accuracy: 0.5464
Epoch 60/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8232 - accuracy: 0.4309 - val_loss: 1.7675 - val_accuracy: 0.5464
Epoch 61/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8271 - accuracy: 0.4309 - val_loss: 1.7673 - val_accuracy: 0.5464
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8301 - accuracy: 0.4159 - val_loss: 1.7671 - val_accuracy: 0.5464
Epoch 63/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8135 - accuracy: 0.4378 - val_loss: 1.7669 - val_accuracy: 0.5464
Epoch 64/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8392 - accuracy: 0.4227 - val_loss: 1.7667 - val_accuracy: 0.5464
Epoch 65/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8247 - accuracy: 0.4309 - val_loss: 1.7665 - val_accuracy: 0.5464
Epoch 66/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8207 - accuracy: 0.4213 - val_loss: 1.7663 - val_accuracy: 0.5464
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8270 - accuracy: 0.4159 - val_loss: 1.7661 - val_accuracy: 0.5464
Epoch 68/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8235 - accuracy: 0.4419 - val_loss: 1.7659 - val_accuracy: 0.5464
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8249 - accuracy: 0.4295 - val_loss: 1.7657 - val_accuracy: 0.5464
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8285 - accuracy: 0.4022 - val_loss: 1.7655 - val_accuracy: 0.5464
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8301 - accuracy: 0.4295 - val_loss: 1.7653 - val_accuracy: 0.5464
Epoch 72/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8215 - accuracy: 0.4337 - val_loss: 1.7651 - val_accuracy: 0.5464
Epoch 73/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8254 - accuracy: 0.4295 - val_loss: 1.7649 - val_accuracy: 0.5464
Epoch 74/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8123 - accuracy: 0.4501 - val_loss: 1.7648 - val_accuracy: 0.5464
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8205 - accuracy: 0.4159 - val_loss: 1.7646 - val_accuracy: 0.5464
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8106 - accuracy: 0.4364 - val_loss: 1.7644 - val_accuracy: 0.5464
Epoch 77/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8217 - accuracy: 0.4295 - val_loss: 1.7642 - val_accuracy: 0.5464
Epoch 78/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8253 - accuracy: 0.4268 - val_loss: 1.7640 - val_accuracy: 0.5464
Epoch 79/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8254 - accuracy: 0.4186 - val_loss: 1.7638 - val_accuracy: 0.5464
Epoch 80/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8215 - accuracy: 0.4282 - val_loss: 1.7636 - val_accuracy: 0.5464
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8141 - accuracy: 0.4268 - val_loss: 1.7634 - val_accuracy: 0.5464
Epoch 82/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8271 - accuracy: 0.4323 - val_loss: 1.7633 - val_accuracy: 0.5464
Epoch 83/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8247 - accuracy: 0.4241 - val_loss: 1.7631 - val_accuracy: 0.5464
Epoch 84/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8218 - accuracy: 0.4213 - val_loss: 1.7629 - val_accuracy: 0.5464
Epoch 85/100
2/2 [==============================] - 0s 30ms/step - loss: 1.8124 - accuracy: 0.4514 - val_loss: 1.7627 - val_accuracy: 0.5464
Epoch 86/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8175 - accuracy: 0.4378 - val_loss: 1.7625 - val_accuracy: 0.5464
Epoch 87/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8120 - accuracy: 0.4487 - val_loss: 1.7623 - val_accuracy: 0.5464
Epoch 88/100
2/2 [==============================] - 0s 30ms/step - loss: 1.8101 - accuracy: 0.4419 - val_loss: 1.7622 - val_accuracy: 0.5464
Epoch 89/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8160 - accuracy: 0.4460 - val_loss: 1.7620 - val_accuracy: 0.5464
Epoch 90/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8128 - accuracy: 0.4118 - val_loss: 1.7618 - val_accuracy: 0.5464
Epoch 91/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8137 - accuracy: 0.4432 - val_loss: 1.7616 - val_accuracy: 0.5464
Epoch 92/100
2/2 [==============================] - 0s 25ms/step - loss: 1.8156 - accuracy: 0.4268 - val_loss: 1.7614 - val_accuracy: 0.5464
Epoch 93/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8073 - accuracy: 0.4501 - val_loss: 1.7612 - val_accuracy: 0.5464
Epoch 94/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8189 - accuracy: 0.4295 - val_loss: 1.7611 - val_accuracy: 0.5464
Epoch 95/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8188 - accuracy: 0.4159 - val_loss: 1.7609 - val_accuracy: 0.5464
Epoch 96/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8267 - accuracy: 0.4145 - val_loss: 1.7607 - val_accuracy: 0.5464
Epoch 97/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8180 - accuracy: 0.4282 - val_loss: 1.7605 - val_accuracy: 0.5464
Epoch 98/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8160 - accuracy: 0.4405 - val_loss: 1.7603 - val_accuracy: 0.5464
Epoch 99/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8178 - accuracy: 0.4405 - val_loss: 1.7602 - val_accuracy: 0.5464
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8104 - accuracy: 0.4378 - val_loss: 1.7600 - val_accuracy: 0.5464
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 8, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 233ms/step - loss: 2.3930 - accuracy: 0.3051 - val_loss: 2.4180 - val_accuracy: 0.2514
Epoch 2/100
2/2 [==============================] - 0s 42ms/step - loss: 2.3442 - accuracy: 0.3352 - val_loss: 2.4166 - val_accuracy: 0.2514
Epoch 3/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3867 - accuracy: 0.2873 - val_loss: 2.4156 - val_accuracy: 0.2514
Epoch 4/100
2/2 [==============================] - 0s 48ms/step - loss: 2.3818 - accuracy: 0.3352 - val_loss: 2.4146 - val_accuracy: 0.2514
Epoch 5/100
2/2 [==============================] - 0s 33ms/step - loss: 2.3523 - accuracy: 0.3201 - val_loss: 2.4138 - val_accuracy: 0.2514
Epoch 6/100
2/2 [==============================] - 0s 51ms/step - loss: 2.4099 - accuracy: 0.2900 - val_loss: 2.4130 - val_accuracy: 0.2514
Epoch 7/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3700 - accuracy: 0.3037 - val_loss: 2.4123 - val_accuracy: 0.2514
Epoch 8/100
2/2 [==============================] - 0s 40ms/step - loss: 2.3716 - accuracy: 0.3023 - val_loss: 2.4117 - val_accuracy: 0.2514
Epoch 9/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3728 - accuracy: 0.3174 - val_loss: 2.4110 - val_accuracy: 0.2514
Epoch 10/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3662 - accuracy: 0.3256 - val_loss: 2.4104 - val_accuracy: 0.2514
Epoch 11/100
2/2 [==============================] - 0s 47ms/step - loss: 2.4017 - accuracy: 0.3119 - val_loss: 2.4099 - val_accuracy: 0.2514
Epoch 12/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3649 - accuracy: 0.3078 - val_loss: 2.4093 - val_accuracy: 0.2514
Epoch 13/100
2/2 [==============================] - 0s 30ms/step - loss: 2.3639 - accuracy: 0.3010 - val_loss: 2.4088 - val_accuracy: 0.2514
Epoch 14/100
2/2 [==============================] - 0s 36ms/step - loss: 2.4106 - accuracy: 0.2996 - val_loss: 2.4083 - val_accuracy: 0.2514
Epoch 15/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3885 - accuracy: 0.2941 - val_loss: 2.4078 - val_accuracy: 0.2514
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 2.3725 - accuracy: 0.3174 - val_loss: 2.4073 - val_accuracy: 0.2514
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 2.3708 - accuracy: 0.3092 - val_loss: 2.4069 - val_accuracy: 0.2514
Epoch 18/100
2/2 [==============================] - 0s 40ms/step - loss: 2.3578 - accuracy: 0.3283 - val_loss: 2.4064 - val_accuracy: 0.2514
Epoch 19/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3593 - accuracy: 0.3242 - val_loss: 2.4060 - val_accuracy: 0.2514
Epoch 20/100
2/2 [==============================] - 0s 53ms/step - loss: 2.3578 - accuracy: 0.3201 - val_loss: 2.4055 - val_accuracy: 0.2514
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3850 - accuracy: 0.2969 - val_loss: 2.4051 - val_accuracy: 0.2514
Epoch 22/100
2/2 [==============================] - 0s 50ms/step - loss: 2.3594 - accuracy: 0.3297 - val_loss: 2.4047 - val_accuracy: 0.2514
Epoch 23/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3717 - accuracy: 0.3160 - val_loss: 2.4043 - val_accuracy: 0.2514
Epoch 24/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3531 - accuracy: 0.3119 - val_loss: 2.4039 - val_accuracy: 0.2514
Epoch 25/100
2/2 [==============================] - 0s 48ms/step - loss: 2.3695 - accuracy: 0.3269 - val_loss: 2.4035 - val_accuracy: 0.2514
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3606 - accuracy: 0.3201 - val_loss: 2.4031 - val_accuracy: 0.2514
Epoch 27/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3528 - accuracy: 0.3160 - val_loss: 2.4027 - val_accuracy: 0.2514
Epoch 28/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3740 - accuracy: 0.3311 - val_loss: 2.4023 - val_accuracy: 0.2514
Epoch 29/100
2/2 [==============================] - 0s 45ms/step - loss: 2.3696 - accuracy: 0.2969 - val_loss: 2.4020 - val_accuracy: 0.2514
Epoch 30/100
2/2 [==============================] - 0s 30ms/step - loss: 2.3841 - accuracy: 0.2955 - val_loss: 2.4016 - val_accuracy: 0.2514
Epoch 31/100
2/2 [==============================] - 0s 33ms/step - loss: 2.3632 - accuracy: 0.3119 - val_loss: 2.4012 - val_accuracy: 0.2514
Epoch 32/100
2/2 [==============================] - 0s 50ms/step - loss: 2.3811 - accuracy: 0.3064 - val_loss: 2.4009 - val_accuracy: 0.2514
Epoch 33/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3308 - accuracy: 0.3119 - val_loss: 2.4005 - val_accuracy: 0.2514
Epoch 34/100
2/2 [==============================] - 0s 32ms/step - loss: 2.3382 - accuracy: 0.3297 - val_loss: 2.4002 - val_accuracy: 0.2514
Epoch 35/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3638 - accuracy: 0.3133 - val_loss: 2.3998 - val_accuracy: 0.2514
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3685 - accuracy: 0.3023 - val_loss: 2.3995 - val_accuracy: 0.2514
Epoch 37/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3637 - accuracy: 0.2873 - val_loss: 2.3991 - val_accuracy: 0.2514
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3349 - accuracy: 0.3215 - val_loss: 2.3988 - val_accuracy: 0.2514
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3224 - accuracy: 0.3311 - val_loss: 2.3984 - val_accuracy: 0.2514
Epoch 40/100
2/2 [==============================] - 0s 33ms/step - loss: 2.3448 - accuracy: 0.3146 - val_loss: 2.3981 - val_accuracy: 0.2514
Epoch 41/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3504 - accuracy: 0.3297 - val_loss: 2.3978 - val_accuracy: 0.2514
Epoch 42/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3534 - accuracy: 0.3133 - val_loss: 2.3975 - val_accuracy: 0.2514
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3319 - accuracy: 0.3297 - val_loss: 2.3972 - val_accuracy: 0.2514
Epoch 44/100
2/2 [==============================] - 0s 42ms/step - loss: 2.3565 - accuracy: 0.3256 - val_loss: 2.3968 - val_accuracy: 0.2514
Epoch 45/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3804 - accuracy: 0.3146 - val_loss: 2.3965 - val_accuracy: 0.2514
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3764 - accuracy: 0.3338 - val_loss: 2.3962 - val_accuracy: 0.2514
Epoch 47/100
2/2 [==============================] - 0s 44ms/step - loss: 2.3478 - accuracy: 0.3064 - val_loss: 2.3959 - val_accuracy: 0.2514
Epoch 48/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3458 - accuracy: 0.3105 - val_loss: 2.3956 - val_accuracy: 0.2514
Epoch 49/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3719 - accuracy: 0.3201 - val_loss: 2.3953 - val_accuracy: 0.2514
Epoch 50/100
2/2 [==============================] - 0s 32ms/step - loss: 2.3637 - accuracy: 0.3092 - val_loss: 2.3950 - val_accuracy: 0.2514
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3706 - accuracy: 0.3174 - val_loss: 2.3947 - val_accuracy: 0.2514
Epoch 52/100
2/2 [==============================] - 0s 40ms/step - loss: 2.3306 - accuracy: 0.3201 - val_loss: 2.3944 - val_accuracy: 0.2514
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3411 - accuracy: 0.3133 - val_loss: 2.3941 - val_accuracy: 0.2514
Epoch 54/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3725 - accuracy: 0.3187 - val_loss: 2.3937 - val_accuracy: 0.2514
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3798 - accuracy: 0.2969 - val_loss: 2.3934 - val_accuracy: 0.2514
Epoch 56/100
2/2 [==============================] - 0s 48ms/step - loss: 2.3581 - accuracy: 0.3352 - val_loss: 2.3931 - val_accuracy: 0.2514
Epoch 57/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3298 - accuracy: 0.3393 - val_loss: 2.3929 - val_accuracy: 0.2514
Epoch 58/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3589 - accuracy: 0.3051 - val_loss: 2.3926 - val_accuracy: 0.2514
Epoch 59/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3449 - accuracy: 0.3297 - val_loss: 2.3923 - val_accuracy: 0.2514
Epoch 60/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3594 - accuracy: 0.3269 - val_loss: 2.3920 - val_accuracy: 0.2514
Epoch 61/100
2/2 [==============================] - 0s 33ms/step - loss: 2.3571 - accuracy: 0.3133 - val_loss: 2.3917 - val_accuracy: 0.2514
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3726 - accuracy: 0.3201 - val_loss: 2.3914 - val_accuracy: 0.2514
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3024 - accuracy: 0.3352 - val_loss: 2.3911 - val_accuracy: 0.2514
Epoch 64/100
2/2 [==============================] - 0s 52ms/step - loss: 2.3395 - accuracy: 0.3201 - val_loss: 2.3908 - val_accuracy: 0.2514
Epoch 65/100
2/2 [==============================] - 0s 50ms/step - loss: 2.3141 - accuracy: 0.3352 - val_loss: 2.3905 - val_accuracy: 0.2514
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3799 - accuracy: 0.2955 - val_loss: 2.3902 - val_accuracy: 0.2514
Epoch 67/100
2/2 [==============================] - 0s 48ms/step - loss: 2.3750 - accuracy: 0.3283 - val_loss: 2.3900 - val_accuracy: 0.2514
Epoch 68/100
2/2 [==============================] - 0s 60ms/step - loss: 2.3308 - accuracy: 0.3187 - val_loss: 2.3897 - val_accuracy: 0.2514
Epoch 69/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3376 - accuracy: 0.3324 - val_loss: 2.3894 - val_accuracy: 0.2514
Epoch 70/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3715 - accuracy: 0.3119 - val_loss: 2.3891 - val_accuracy: 0.2514
Epoch 71/100
2/2 [==============================] - 0s 50ms/step - loss: 2.3662 - accuracy: 0.3119 - val_loss: 2.3888 - val_accuracy: 0.2514
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3619 - accuracy: 0.3078 - val_loss: 2.3885 - val_accuracy: 0.2514
Epoch 73/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3619 - accuracy: 0.3119 - val_loss: 2.3882 - val_accuracy: 0.2514
Epoch 74/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3467 - accuracy: 0.3119 - val_loss: 2.3879 - val_accuracy: 0.2514
Epoch 75/100
2/2 [==============================] - 0s 48ms/step - loss: 2.3246 - accuracy: 0.3352 - val_loss: 2.3877 - val_accuracy: 0.2514
Epoch 76/100
2/2 [==============================] - 0s 44ms/step - loss: 2.3516 - accuracy: 0.3092 - val_loss: 2.3874 - val_accuracy: 0.2514
Epoch 77/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3378 - accuracy: 0.3160 - val_loss: 2.3871 - val_accuracy: 0.2514
Epoch 78/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3273 - accuracy: 0.3269 - val_loss: 2.3868 - val_accuracy: 0.2514
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3541 - accuracy: 0.3283 - val_loss: 2.3866 - val_accuracy: 0.2514
Epoch 80/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3468 - accuracy: 0.3051 - val_loss: 2.3863 - val_accuracy: 0.2514
Epoch 81/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3398 - accuracy: 0.3228 - val_loss: 2.3860 - val_accuracy: 0.2514
Epoch 82/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3609 - accuracy: 0.3352 - val_loss: 2.3857 - val_accuracy: 0.2514
Epoch 83/100
2/2 [==============================] - 0s 33ms/step - loss: 2.3590 - accuracy: 0.3078 - val_loss: 2.3855 - val_accuracy: 0.2514
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3300 - accuracy: 0.3092 - val_loss: 2.3852 - val_accuracy: 0.2514
Epoch 85/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3393 - accuracy: 0.3174 - val_loss: 2.3849 - val_accuracy: 0.2514
Epoch 86/100
2/2 [==============================] - 0s 45ms/step - loss: 2.3556 - accuracy: 0.3324 - val_loss: 2.3846 - val_accuracy: 0.2514
Epoch 87/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3248 - accuracy: 0.3269 - val_loss: 2.3844 - val_accuracy: 0.2514
Epoch 88/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3264 - accuracy: 0.3297 - val_loss: 2.3841 - val_accuracy: 0.2514
Epoch 89/100
2/2 [==============================] - 0s 43ms/step - loss: 2.3581 - accuracy: 0.3215 - val_loss: 2.3838 - val_accuracy: 0.2514
Epoch 90/100
2/2 [==============================] - 0s 42ms/step - loss: 2.3423 - accuracy: 0.3283 - val_loss: 2.3836 - val_accuracy: 0.2514
Epoch 91/100
2/2 [==============================] - 0s 41ms/step - loss: 2.3690 - accuracy: 0.2969 - val_loss: 2.3833 - val_accuracy: 0.2514
Epoch 92/100
2/2 [==============================] - 0s 28ms/step - loss: 2.3410 - accuracy: 0.3215 - val_loss: 2.3830 - val_accuracy: 0.2514
Epoch 93/100
2/2 [==============================] - 0s 42ms/step - loss: 2.3394 - accuracy: 0.3215 - val_loss: 2.3828 - val_accuracy: 0.2514
Epoch 94/100
2/2 [==============================] - 0s 50ms/step - loss: 2.3426 - accuracy: 0.3406 - val_loss: 2.3825 - val_accuracy: 0.2514
Epoch 95/100
2/2 [==============================] - 0s 49ms/step - loss: 2.3607 - accuracy: 0.3119 - val_loss: 2.3822 - val_accuracy: 0.2568
Epoch 96/100
2/2 [==============================] - 0s 48ms/step - loss: 2.3759 - accuracy: 0.3338 - val_loss: 2.3820 - val_accuracy: 0.2568
Epoch 97/100
2/2 [==============================] - 0s 28ms/step - loss: 2.3414 - accuracy: 0.3201 - val_loss: 2.3817 - val_accuracy: 0.2568
Epoch 98/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3260 - accuracy: 0.3187 - val_loss: 2.3814 - val_accuracy: 0.2568
Epoch 99/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3667 - accuracy: 0.3078 - val_loss: 2.3812 - val_accuracy: 0.2678
Epoch 100/100
2/2 [==============================] - 0s 50ms/step - loss: 2.3326 - accuracy: 0.3297 - val_loss: 2.3809 - val_accuracy: 0.2678
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 8, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
2/2 [==============================] - 1s 223ms/step - loss: 2.0052 - accuracy: 0.4604 - val_loss: 1.9642 - val_accuracy: 0.5055
Epoch 2/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9965 - accuracy: 0.4658 - val_loss: 1.9632 - val_accuracy: 0.5055
Epoch 3/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9845 - accuracy: 0.4740 - val_loss: 1.9624 - val_accuracy: 0.5055
Epoch 4/100
2/2 [==============================] - 0s 30ms/step - loss: 1.9959 - accuracy: 0.4809 - val_loss: 1.9617 - val_accuracy: 0.5055
Epoch 5/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0098 - accuracy: 0.4686 - val_loss: 1.9611 - val_accuracy: 0.5055
Epoch 6/100
2/2 [==============================] - 0s 33ms/step - loss: 1.9952 - accuracy: 0.4754 - val_loss: 1.9605 - val_accuracy: 0.5055
Epoch 7/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0033 - accuracy: 0.4617 - val_loss: 1.9600 - val_accuracy: 0.5055
Epoch 8/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9969 - accuracy: 0.4686 - val_loss: 1.9595 - val_accuracy: 0.5055
Epoch 9/100
2/2 [==============================] - 0s 44ms/step - loss: 2.0132 - accuracy: 0.4645 - val_loss: 1.9590 - val_accuracy: 0.5055
Epoch 10/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9864 - accuracy: 0.4672 - val_loss: 1.9586 - val_accuracy: 0.5055
Epoch 11/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9985 - accuracy: 0.4754 - val_loss: 1.9581 - val_accuracy: 0.5055
Epoch 12/100
2/2 [==============================] - 0s 51ms/step - loss: 1.9884 - accuracy: 0.4740 - val_loss: 1.9577 - val_accuracy: 0.5055
Epoch 13/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9790 - accuracy: 0.4877 - val_loss: 1.9573 - val_accuracy: 0.5055
Epoch 14/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9838 - accuracy: 0.4836 - val_loss: 1.9570 - val_accuracy: 0.5110
Epoch 15/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0021 - accuracy: 0.4590 - val_loss: 1.9566 - val_accuracy: 0.5110
Epoch 16/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9803 - accuracy: 0.4891 - val_loss: 1.9562 - val_accuracy: 0.5110
Epoch 17/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9960 - accuracy: 0.4740 - val_loss: 1.9559 - val_accuracy: 0.5110
Epoch 18/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9803 - accuracy: 0.4809 - val_loss: 1.9556 - val_accuracy: 0.5110
Epoch 19/100
2/2 [==============================] - 0s 46ms/step - loss: 1.9852 - accuracy: 0.4686 - val_loss: 1.9552 - val_accuracy: 0.5110
Epoch 20/100
2/2 [==============================] - 0s 33ms/step - loss: 1.9864 - accuracy: 0.4795 - val_loss: 1.9549 - val_accuracy: 0.5110
Epoch 21/100
2/2 [==============================] - 0s 32ms/step - loss: 1.9902 - accuracy: 0.4836 - val_loss: 1.9546 - val_accuracy: 0.5110
Epoch 22/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9920 - accuracy: 0.4699 - val_loss: 1.9543 - val_accuracy: 0.5110
Epoch 23/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0032 - accuracy: 0.4631 - val_loss: 1.9539 - val_accuracy: 0.5110
Epoch 24/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9784 - accuracy: 0.4604 - val_loss: 1.9536 - val_accuracy: 0.5110
Epoch 25/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9949 - accuracy: 0.4672 - val_loss: 1.9533 - val_accuracy: 0.5110
Epoch 26/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9819 - accuracy: 0.4658 - val_loss: 1.9531 - val_accuracy: 0.5110
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9906 - accuracy: 0.4590 - val_loss: 1.9528 - val_accuracy: 0.5165
Epoch 28/100
2/2 [==============================] - 0s 32ms/step - loss: 1.9727 - accuracy: 0.5014 - val_loss: 1.9525 - val_accuracy: 0.5165
Epoch 29/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9936 - accuracy: 0.4727 - val_loss: 1.9522 - val_accuracy: 0.5165
Epoch 30/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9847 - accuracy: 0.4713 - val_loss: 1.9519 - val_accuracy: 0.5165
Epoch 31/100
2/2 [==============================] - 0s 29ms/step - loss: 1.9831 - accuracy: 0.4672 - val_loss: 1.9517 - val_accuracy: 0.5165
Epoch 32/100
2/2 [==============================] - 0s 33ms/step - loss: 1.9818 - accuracy: 0.4781 - val_loss: 1.9514 - val_accuracy: 0.5165
Epoch 33/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9910 - accuracy: 0.4699 - val_loss: 1.9511 - val_accuracy: 0.5165
Epoch 34/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9806 - accuracy: 0.4809 - val_loss: 1.9508 - val_accuracy: 0.5165
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9773 - accuracy: 0.4727 - val_loss: 1.9506 - val_accuracy: 0.5165
Epoch 36/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9880 - accuracy: 0.4959 - val_loss: 1.9503 - val_accuracy: 0.5165
Epoch 37/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9896 - accuracy: 0.5027 - val_loss: 1.9501 - val_accuracy: 0.5165
Epoch 38/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9721 - accuracy: 0.4850 - val_loss: 1.9498 - val_accuracy: 0.5165
Epoch 39/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9701 - accuracy: 0.4932 - val_loss: 1.9496 - val_accuracy: 0.5165
Epoch 40/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9681 - accuracy: 0.4904 - val_loss: 1.9493 - val_accuracy: 0.5165
Epoch 41/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9865 - accuracy: 0.4768 - val_loss: 1.9491 - val_accuracy: 0.5165
Epoch 42/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9890 - accuracy: 0.4795 - val_loss: 1.9488 - val_accuracy: 0.5165
Epoch 43/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9682 - accuracy: 0.4781 - val_loss: 1.9486 - val_accuracy: 0.5165
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9807 - accuracy: 0.4863 - val_loss: 1.9483 - val_accuracy: 0.5165
Epoch 45/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9877 - accuracy: 0.4904 - val_loss: 1.9481 - val_accuracy: 0.5165
Epoch 46/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9810 - accuracy: 0.4645 - val_loss: 1.9479 - val_accuracy: 0.5165
Epoch 47/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9892 - accuracy: 0.4904 - val_loss: 1.9476 - val_accuracy: 0.5165
Epoch 48/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9955 - accuracy: 0.4863 - val_loss: 1.9474 - val_accuracy: 0.5165
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9859 - accuracy: 0.4836 - val_loss: 1.9471 - val_accuracy: 0.5165
Epoch 50/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9889 - accuracy: 0.4863 - val_loss: 1.9469 - val_accuracy: 0.5165
Epoch 51/100
2/2 [==============================] - 0s 29ms/step - loss: 1.9751 - accuracy: 0.4795 - val_loss: 1.9467 - val_accuracy: 0.5165
Epoch 52/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9965 - accuracy: 0.4699 - val_loss: 1.9464 - val_accuracy: 0.5165
Epoch 53/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9991 - accuracy: 0.4836 - val_loss: 1.9462 - val_accuracy: 0.5165
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9822 - accuracy: 0.4932 - val_loss: 1.9460 - val_accuracy: 0.5165
Epoch 55/100
2/2 [==============================] - 0s 45ms/step - loss: 1.9716 - accuracy: 0.4959 - val_loss: 1.9458 - val_accuracy: 0.5165
Epoch 56/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9725 - accuracy: 0.4795 - val_loss: 1.9455 - val_accuracy: 0.5165
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9765 - accuracy: 0.4795 - val_loss: 1.9453 - val_accuracy: 0.5165
Epoch 58/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9838 - accuracy: 0.4809 - val_loss: 1.9451 - val_accuracy: 0.5165
Epoch 59/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9949 - accuracy: 0.4891 - val_loss: 1.9449 - val_accuracy: 0.5165
Epoch 60/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9921 - accuracy: 0.4699 - val_loss: 1.9446 - val_accuracy: 0.5165
Epoch 61/100
2/2 [==============================] - 0s 52ms/step - loss: 1.9709 - accuracy: 0.4918 - val_loss: 1.9444 - val_accuracy: 0.5165
Epoch 62/100
2/2 [==============================] - 0s 53ms/step - loss: 1.9767 - accuracy: 0.4959 - val_loss: 1.9442 - val_accuracy: 0.5165
Epoch 63/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9804 - accuracy: 0.5014 - val_loss: 1.9440 - val_accuracy: 0.5165
Epoch 64/100
2/2 [==============================] - 0s 51ms/step - loss: 1.9738 - accuracy: 0.4973 - val_loss: 1.9438 - val_accuracy: 0.5165
Epoch 65/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9837 - accuracy: 0.4768 - val_loss: 1.9435 - val_accuracy: 0.5165
Epoch 66/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9676 - accuracy: 0.4959 - val_loss: 1.9433 - val_accuracy: 0.5165
Epoch 67/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9778 - accuracy: 0.4863 - val_loss: 1.9431 - val_accuracy: 0.5165
Epoch 68/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9846 - accuracy: 0.4809 - val_loss: 1.9429 - val_accuracy: 0.5165
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9900 - accuracy: 0.4918 - val_loss: 1.9427 - val_accuracy: 0.5165
Epoch 70/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9851 - accuracy: 0.4809 - val_loss: 1.9425 - val_accuracy: 0.5165
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9817 - accuracy: 0.4809 - val_loss: 1.9423 - val_accuracy: 0.5165
Epoch 72/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9745 - accuracy: 0.4850 - val_loss: 1.9420 - val_accuracy: 0.5165
Epoch 73/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9791 - accuracy: 0.4986 - val_loss: 1.9418 - val_accuracy: 0.5165
Epoch 74/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9440 - accuracy: 0.5000 - val_loss: 1.9416 - val_accuracy: 0.5165
Epoch 75/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9748 - accuracy: 0.4877 - val_loss: 1.9414 - val_accuracy: 0.5165
Epoch 76/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9825 - accuracy: 0.4590 - val_loss: 1.9412 - val_accuracy: 0.5165
Epoch 77/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9886 - accuracy: 0.4918 - val_loss: 1.9410 - val_accuracy: 0.5165
Epoch 78/100
2/2 [==============================] - 0s 46ms/step - loss: 1.9892 - accuracy: 0.4686 - val_loss: 1.9408 - val_accuracy: 0.5165
Epoch 79/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9631 - accuracy: 0.4727 - val_loss: 1.9406 - val_accuracy: 0.5165
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9754 - accuracy: 0.4850 - val_loss: 1.9404 - val_accuracy: 0.5165
Epoch 81/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9618 - accuracy: 0.5000 - val_loss: 1.9402 - val_accuracy: 0.5165
Epoch 82/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9790 - accuracy: 0.4836 - val_loss: 1.9400 - val_accuracy: 0.5165
Epoch 83/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9866 - accuracy: 0.4918 - val_loss: 1.9398 - val_accuracy: 0.5165
Epoch 84/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9738 - accuracy: 0.4836 - val_loss: 1.9395 - val_accuracy: 0.5165
Epoch 85/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9701 - accuracy: 0.4904 - val_loss: 1.9393 - val_accuracy: 0.5165
Epoch 86/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9676 - accuracy: 0.4986 - val_loss: 1.9391 - val_accuracy: 0.5165
Epoch 87/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9724 - accuracy: 0.4781 - val_loss: 1.9389 - val_accuracy: 0.5165
Epoch 88/100
2/2 [==============================] - 0s 49ms/step - loss: 1.9706 - accuracy: 0.4973 - val_loss: 1.9387 - val_accuracy: 0.5165
Epoch 89/100
2/2 [==============================] - 0s 29ms/step - loss: 1.9793 - accuracy: 0.4918 - val_loss: 1.9385 - val_accuracy: 0.5165
Epoch 90/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9785 - accuracy: 0.4699 - val_loss: 1.9383 - val_accuracy: 0.5165
Epoch 91/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9820 - accuracy: 0.4699 - val_loss: 1.9381 - val_accuracy: 0.5165
Epoch 92/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9651 - accuracy: 0.5014 - val_loss: 1.9379 - val_accuracy: 0.5165
Epoch 93/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9601 - accuracy: 0.4863 - val_loss: 1.9377 - val_accuracy: 0.5165
Epoch 94/100
2/2 [==============================] - 0s 46ms/step - loss: 1.9634 - accuracy: 0.5014 - val_loss: 1.9375 - val_accuracy: 0.5165
Epoch 95/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9917 - accuracy: 0.4891 - val_loss: 1.9373 - val_accuracy: 0.5165
Epoch 96/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9745 - accuracy: 0.4945 - val_loss: 1.9371 - val_accuracy: 0.5165
Epoch 97/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9722 - accuracy: 0.4795 - val_loss: 1.9369 - val_accuracy: 0.5165
Epoch 98/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9909 - accuracy: 0.4822 - val_loss: 1.9367 - val_accuracy: 0.5165
Epoch 99/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9787 - accuracy: 0.4904 - val_loss: 1.9365 - val_accuracy: 0.5165
Epoch 100/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9721 - accuracy: 0.4795 - val_loss: 1.9363 - val_accuracy: 0.5165
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Experiment number: 5
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 118ms/step - loss: 2.2716 - accuracy: 0.3789 - val_loss: 2.2285 - val_accuracy: 0.4262
Epoch 2/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2841 - accuracy: 0.3803 - val_loss: 2.2276 - val_accuracy: 0.4262
Epoch 3/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2751 - accuracy: 0.3926 - val_loss: 2.2268 - val_accuracy: 0.4262
Epoch 4/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2880 - accuracy: 0.3871 - val_loss: 2.2261 - val_accuracy: 0.4262
Epoch 5/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2704 - accuracy: 0.4036 - val_loss: 2.2253 - val_accuracy: 0.4262
Epoch 6/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2765 - accuracy: 0.3885 - val_loss: 2.2246 - val_accuracy: 0.4262
Epoch 7/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2718 - accuracy: 0.3885 - val_loss: 2.2239 - val_accuracy: 0.4317
Epoch 8/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2572 - accuracy: 0.4295 - val_loss: 2.2232 - val_accuracy: 0.4372
Epoch 9/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2687 - accuracy: 0.4227 - val_loss: 2.2225 - val_accuracy: 0.4426
Epoch 10/100
3/3 [==============================] - 0s 26ms/step - loss: 2.2666 - accuracy: 0.3981 - val_loss: 2.2218 - val_accuracy: 0.4426
Epoch 11/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2650 - accuracy: 0.3858 - val_loss: 2.2211 - val_accuracy: 0.4426
Epoch 12/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2632 - accuracy: 0.3912 - val_loss: 2.2204 - val_accuracy: 0.4481
Epoch 13/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2665 - accuracy: 0.3858 - val_loss: 2.2197 - val_accuracy: 0.4481
Epoch 14/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2683 - accuracy: 0.3967 - val_loss: 2.2190 - val_accuracy: 0.4481
Epoch 15/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2526 - accuracy: 0.4309 - val_loss: 2.2183 - val_accuracy: 0.4481
Epoch 16/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2646 - accuracy: 0.4186 - val_loss: 2.2176 - val_accuracy: 0.4481
Epoch 17/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2562 - accuracy: 0.3967 - val_loss: 2.2169 - val_accuracy: 0.4481
Epoch 18/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2549 - accuracy: 0.4145 - val_loss: 2.2162 - val_accuracy: 0.4481
Epoch 19/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2602 - accuracy: 0.3912 - val_loss: 2.2155 - val_accuracy: 0.4481
Epoch 20/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2592 - accuracy: 0.3926 - val_loss: 2.2148 - val_accuracy: 0.4481
Epoch 21/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2388 - accuracy: 0.4364 - val_loss: 2.2141 - val_accuracy: 0.4481
Epoch 22/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2698 - accuracy: 0.3871 - val_loss: 2.2134 - val_accuracy: 0.4481
Epoch 23/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2680 - accuracy: 0.4268 - val_loss: 2.2127 - val_accuracy: 0.4481
Epoch 24/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2638 - accuracy: 0.3858 - val_loss: 2.2120 - val_accuracy: 0.4481
Epoch 25/100
3/3 [==============================] - 0s 16ms/step - loss: 2.2586 - accuracy: 0.4008 - val_loss: 2.2113 - val_accuracy: 0.4590
Epoch 26/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2497 - accuracy: 0.4186 - val_loss: 2.2106 - val_accuracy: 0.4590
Epoch 27/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2514 - accuracy: 0.3912 - val_loss: 2.2099 - val_accuracy: 0.4590
Epoch 28/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2701 - accuracy: 0.4049 - val_loss: 2.2092 - val_accuracy: 0.4590
Epoch 29/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2477 - accuracy: 0.4145 - val_loss: 2.2085 - val_accuracy: 0.4590
Epoch 30/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2577 - accuracy: 0.4036 - val_loss: 2.2078 - val_accuracy: 0.4590
Epoch 31/100
3/3 [==============================] - 0s 13ms/step - loss: 2.2505 - accuracy: 0.4090 - val_loss: 2.2071 - val_accuracy: 0.4590
Epoch 32/100
3/3 [==============================] - 0s 15ms/step - loss: 2.2311 - accuracy: 0.4241 - val_loss: 2.2064 - val_accuracy: 0.4590
Epoch 33/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2456 - accuracy: 0.4213 - val_loss: 2.2057 - val_accuracy: 0.4590
Epoch 34/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2367 - accuracy: 0.4159 - val_loss: 2.2050 - val_accuracy: 0.4590
Epoch 35/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2458 - accuracy: 0.4186 - val_loss: 2.2043 - val_accuracy: 0.4590
Epoch 36/100
3/3 [==============================] - 0s 26ms/step - loss: 2.2340 - accuracy: 0.4186 - val_loss: 2.2037 - val_accuracy: 0.4590
Epoch 37/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2550 - accuracy: 0.4186 - val_loss: 2.2030 - val_accuracy: 0.4590
Epoch 38/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2461 - accuracy: 0.3953 - val_loss: 2.2023 - val_accuracy: 0.4590
Epoch 39/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2378 - accuracy: 0.4118 - val_loss: 2.2016 - val_accuracy: 0.4590
Epoch 40/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2431 - accuracy: 0.4172 - val_loss: 2.2009 - val_accuracy: 0.4590
Epoch 41/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2453 - accuracy: 0.4213 - val_loss: 2.2002 - val_accuracy: 0.4590
Epoch 42/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2448 - accuracy: 0.4118 - val_loss: 2.1995 - val_accuracy: 0.4590
Epoch 43/100
3/3 [==============================] - 0s 31ms/step - loss: 2.2338 - accuracy: 0.4282 - val_loss: 2.1988 - val_accuracy: 0.4590
Epoch 44/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2381 - accuracy: 0.4145 - val_loss: 2.1981 - val_accuracy: 0.4590
Epoch 45/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2346 - accuracy: 0.4213 - val_loss: 2.1974 - val_accuracy: 0.4590
Epoch 46/100
3/3 [==============================] - 0s 16ms/step - loss: 2.2395 - accuracy: 0.4295 - val_loss: 2.1967 - val_accuracy: 0.4590
Epoch 47/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2518 - accuracy: 0.4022 - val_loss: 2.1960 - val_accuracy: 0.4590
Epoch 48/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2264 - accuracy: 0.4227 - val_loss: 2.1953 - val_accuracy: 0.4590
Epoch 49/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2445 - accuracy: 0.4391 - val_loss: 2.1946 - val_accuracy: 0.4536
Epoch 50/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2280 - accuracy: 0.4501 - val_loss: 2.1940 - val_accuracy: 0.4536
Epoch 51/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2216 - accuracy: 0.4460 - val_loss: 2.1933 - val_accuracy: 0.4536
Epoch 52/100
3/3 [==============================] - 0s 13ms/step - loss: 2.2337 - accuracy: 0.4473 - val_loss: 2.1926 - val_accuracy: 0.4536
Epoch 53/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2212 - accuracy: 0.4159 - val_loss: 2.1919 - val_accuracy: 0.4536
Epoch 54/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2193 - accuracy: 0.4186 - val_loss: 2.1912 - val_accuracy: 0.4536
Epoch 55/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2227 - accuracy: 0.4446 - val_loss: 2.1905 - val_accuracy: 0.4536
Epoch 56/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2287 - accuracy: 0.4268 - val_loss: 2.1898 - val_accuracy: 0.4536
Epoch 57/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2322 - accuracy: 0.4446 - val_loss: 2.1891 - val_accuracy: 0.4536
Epoch 58/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2336 - accuracy: 0.4295 - val_loss: 2.1884 - val_accuracy: 0.4590
Epoch 59/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2232 - accuracy: 0.4391 - val_loss: 2.1878 - val_accuracy: 0.4590
Epoch 60/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2153 - accuracy: 0.4583 - val_loss: 2.1871 - val_accuracy: 0.4590
Epoch 61/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2261 - accuracy: 0.4487 - val_loss: 2.1864 - val_accuracy: 0.4590
Epoch 62/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2502 - accuracy: 0.4036 - val_loss: 2.1857 - val_accuracy: 0.4590
Epoch 63/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2299 - accuracy: 0.4172 - val_loss: 2.1850 - val_accuracy: 0.4590
Epoch 64/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2397 - accuracy: 0.4118 - val_loss: 2.1843 - val_accuracy: 0.4590
Epoch 65/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2416 - accuracy: 0.4323 - val_loss: 2.1836 - val_accuracy: 0.4590
Epoch 66/100
3/3 [==============================] - 0s 26ms/step - loss: 2.2089 - accuracy: 0.4473 - val_loss: 2.1830 - val_accuracy: 0.4590
Epoch 67/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2240 - accuracy: 0.4378 - val_loss: 2.1823 - val_accuracy: 0.4590
Epoch 68/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2276 - accuracy: 0.4295 - val_loss: 2.1816 - val_accuracy: 0.4590
Epoch 69/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2337 - accuracy: 0.4063 - val_loss: 2.1809 - val_accuracy: 0.4590
Epoch 70/100
3/3 [==============================] - 0s 16ms/step - loss: 2.2111 - accuracy: 0.4596 - val_loss: 2.1802 - val_accuracy: 0.4590
Epoch 71/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2119 - accuracy: 0.4295 - val_loss: 2.1796 - val_accuracy: 0.4590
Epoch 72/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2221 - accuracy: 0.4569 - val_loss: 2.1789 - val_accuracy: 0.4645
Epoch 73/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2261 - accuracy: 0.4460 - val_loss: 2.1782 - val_accuracy: 0.4699
Epoch 74/100
3/3 [==============================] - 0s 15ms/step - loss: 2.2106 - accuracy: 0.4391 - val_loss: 2.1775 - val_accuracy: 0.4699
Epoch 75/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2145 - accuracy: 0.4624 - val_loss: 2.1768 - val_accuracy: 0.4754
Epoch 76/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2132 - accuracy: 0.4596 - val_loss: 2.1762 - val_accuracy: 0.4809
Epoch 77/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2150 - accuracy: 0.4528 - val_loss: 2.1755 - val_accuracy: 0.4809
Epoch 78/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2122 - accuracy: 0.4419 - val_loss: 2.1748 - val_accuracy: 0.4809
Epoch 79/100
3/3 [==============================] - 0s 26ms/step - loss: 2.2178 - accuracy: 0.4378 - val_loss: 2.1741 - val_accuracy: 0.4809
Epoch 80/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2186 - accuracy: 0.4624 - val_loss: 2.1734 - val_accuracy: 0.4809
Epoch 81/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2258 - accuracy: 0.4542 - val_loss: 2.1727 - val_accuracy: 0.4809
Epoch 82/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2206 - accuracy: 0.4227 - val_loss: 2.1721 - val_accuracy: 0.4809
Epoch 83/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1936 - accuracy: 0.4364 - val_loss: 2.1714 - val_accuracy: 0.4809
Epoch 84/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1862 - accuracy: 0.5048 - val_loss: 2.1707 - val_accuracy: 0.4809
Epoch 85/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2052 - accuracy: 0.4350 - val_loss: 2.1700 - val_accuracy: 0.4863
Epoch 86/100
3/3 [==============================] - 0s 14ms/step - loss: 2.2099 - accuracy: 0.4446 - val_loss: 2.1694 - val_accuracy: 0.4863
Epoch 87/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2146 - accuracy: 0.4323 - val_loss: 2.1687 - val_accuracy: 0.4863
Epoch 88/100
3/3 [==============================] - 0s 14ms/step - loss: 2.2009 - accuracy: 0.4528 - val_loss: 2.1680 - val_accuracy: 0.4863
Epoch 89/100
3/3 [==============================] - 0s 15ms/step - loss: 2.2180 - accuracy: 0.4172 - val_loss: 2.1673 - val_accuracy: 0.4918
Epoch 90/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2003 - accuracy: 0.4569 - val_loss: 2.1666 - val_accuracy: 0.4918
Epoch 91/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2118 - accuracy: 0.4432 - val_loss: 2.1660 - val_accuracy: 0.4918
Epoch 92/100
3/3 [==============================] - 0s 31ms/step - loss: 2.2106 - accuracy: 0.4309 - val_loss: 2.1653 - val_accuracy: 0.4918
Epoch 93/100
3/3 [==============================] - 0s 28ms/step - loss: 2.2129 - accuracy: 0.4514 - val_loss: 2.1646 - val_accuracy: 0.4918
Epoch 94/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2022 - accuracy: 0.4692 - val_loss: 2.1639 - val_accuracy: 0.4918
Epoch 95/100
3/3 [==============================] - 0s 26ms/step - loss: 2.1827 - accuracy: 0.4911 - val_loss: 2.1633 - val_accuracy: 0.4918
Epoch 96/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2286 - accuracy: 0.4104 - val_loss: 2.1626 - val_accuracy: 0.4918
Epoch 97/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1972 - accuracy: 0.4761 - val_loss: 2.1619 - val_accuracy: 0.4918
Epoch 98/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1829 - accuracy: 0.4911 - val_loss: 2.1612 - val_accuracy: 0.4918
Epoch 99/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2013 - accuracy: 0.4528 - val_loss: 2.1606 - val_accuracy: 0.4918
Epoch 100/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2002 - accuracy: 0.4391 - val_loss: 2.1599 - val_accuracy: 0.4918
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 138ms/step - loss: 2.4053 - accuracy: 0.2271 - val_loss: 2.3936 - val_accuracy: 0.1858
Epoch 2/100
3/3 [==============================] - 0s 29ms/step - loss: 2.4077 - accuracy: 0.2408 - val_loss: 2.3925 - val_accuracy: 0.1858
Epoch 3/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4235 - accuracy: 0.2285 - val_loss: 2.3915 - val_accuracy: 0.1858
Epoch 4/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4164 - accuracy: 0.2353 - val_loss: 2.3905 - val_accuracy: 0.1858
Epoch 5/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4314 - accuracy: 0.2271 - val_loss: 2.3896 - val_accuracy: 0.1858
Epoch 6/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4234 - accuracy: 0.2271 - val_loss: 2.3887 - val_accuracy: 0.1858
Epoch 7/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4091 - accuracy: 0.2558 - val_loss: 2.3878 - val_accuracy: 0.1858
Epoch 8/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4169 - accuracy: 0.2339 - val_loss: 2.3869 - val_accuracy: 0.1858
Epoch 9/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4353 - accuracy: 0.2066 - val_loss: 2.3860 - val_accuracy: 0.1913
Epoch 10/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4288 - accuracy: 0.2244 - val_loss: 2.3851 - val_accuracy: 0.1913
Epoch 11/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4148 - accuracy: 0.2353 - val_loss: 2.3842 - val_accuracy: 0.1913
Epoch 12/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4062 - accuracy: 0.2285 - val_loss: 2.3833 - val_accuracy: 0.1913
Epoch 13/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4109 - accuracy: 0.2572 - val_loss: 2.3824 - val_accuracy: 0.1913
Epoch 14/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4003 - accuracy: 0.2462 - val_loss: 2.3815 - val_accuracy: 0.1913
Epoch 15/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3994 - accuracy: 0.2572 - val_loss: 2.3806 - val_accuracy: 0.1913
Epoch 16/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3843 - accuracy: 0.2613 - val_loss: 2.3797 - val_accuracy: 0.1913
Epoch 17/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3826 - accuracy: 0.2476 - val_loss: 2.3788 - val_accuracy: 0.1913
Epoch 18/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3907 - accuracy: 0.2490 - val_loss: 2.3779 - val_accuracy: 0.1967
Epoch 19/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4006 - accuracy: 0.2462 - val_loss: 2.3770 - val_accuracy: 0.1967
Epoch 20/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4121 - accuracy: 0.2572 - val_loss: 2.3761 - val_accuracy: 0.1967
Epoch 21/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4049 - accuracy: 0.2408 - val_loss: 2.3752 - val_accuracy: 0.1967
Epoch 22/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4130 - accuracy: 0.2189 - val_loss: 2.3744 - val_accuracy: 0.1967
Epoch 23/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3617 - accuracy: 0.2490 - val_loss: 2.3735 - val_accuracy: 0.1967
Epoch 24/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3982 - accuracy: 0.2613 - val_loss: 2.3726 - val_accuracy: 0.1967
Epoch 25/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3778 - accuracy: 0.2750 - val_loss: 2.3717 - val_accuracy: 0.1967
Epoch 26/100
3/3 [==============================] - 0s 27ms/step - loss: 2.4109 - accuracy: 0.2517 - val_loss: 2.3708 - val_accuracy: 0.1967
Epoch 27/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3934 - accuracy: 0.2613 - val_loss: 2.3699 - val_accuracy: 0.1967
Epoch 28/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4008 - accuracy: 0.2640 - val_loss: 2.3690 - val_accuracy: 0.1967
Epoch 29/100
3/3 [==============================] - 0s 27ms/step - loss: 2.3925 - accuracy: 0.2599 - val_loss: 2.3681 - val_accuracy: 0.1967
Epoch 30/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4059 - accuracy: 0.2285 - val_loss: 2.3672 - val_accuracy: 0.1967
Epoch 31/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3688 - accuracy: 0.2503 - val_loss: 2.3664 - val_accuracy: 0.1967
Epoch 32/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3855 - accuracy: 0.2627 - val_loss: 2.3655 - val_accuracy: 0.1967
Epoch 33/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3788 - accuracy: 0.2613 - val_loss: 2.3646 - val_accuracy: 0.1967
Epoch 34/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3707 - accuracy: 0.2832 - val_loss: 2.3637 - val_accuracy: 0.1967
Epoch 35/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3926 - accuracy: 0.2709 - val_loss: 2.3628 - val_accuracy: 0.1967
Epoch 36/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4009 - accuracy: 0.2230 - val_loss: 2.3619 - val_accuracy: 0.2022
Epoch 37/100
3/3 [==============================] - 0s 15ms/step - loss: 2.3804 - accuracy: 0.2695 - val_loss: 2.3610 - val_accuracy: 0.2022
Epoch 38/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3981 - accuracy: 0.2654 - val_loss: 2.3601 - val_accuracy: 0.2022
Epoch 39/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3700 - accuracy: 0.2572 - val_loss: 2.3593 - val_accuracy: 0.2022
Epoch 40/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3740 - accuracy: 0.2722 - val_loss: 2.3584 - val_accuracy: 0.2022
Epoch 41/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3857 - accuracy: 0.2668 - val_loss: 2.3575 - val_accuracy: 0.2022
Epoch 42/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3821 - accuracy: 0.2517 - val_loss: 2.3566 - val_accuracy: 0.2022
Epoch 43/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3642 - accuracy: 0.2777 - val_loss: 2.3557 - val_accuracy: 0.2022
Epoch 44/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3607 - accuracy: 0.2640 - val_loss: 2.3548 - val_accuracy: 0.2022
Epoch 45/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3800 - accuracy: 0.2517 - val_loss: 2.3539 - val_accuracy: 0.2022
Epoch 46/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3683 - accuracy: 0.2695 - val_loss: 2.3531 - val_accuracy: 0.2022
Epoch 47/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3695 - accuracy: 0.2695 - val_loss: 2.3522 - val_accuracy: 0.2022
Epoch 48/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3761 - accuracy: 0.2531 - val_loss: 2.3513 - val_accuracy: 0.2022
Epoch 49/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3818 - accuracy: 0.2681 - val_loss: 2.3504 - val_accuracy: 0.2022
Epoch 50/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3928 - accuracy: 0.2585 - val_loss: 2.3495 - val_accuracy: 0.2022
Epoch 51/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3915 - accuracy: 0.2722 - val_loss: 2.3486 - val_accuracy: 0.2022
Epoch 52/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3662 - accuracy: 0.2654 - val_loss: 2.3478 - val_accuracy: 0.2022
Epoch 53/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3680 - accuracy: 0.2709 - val_loss: 2.3469 - val_accuracy: 0.2022
Epoch 54/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3610 - accuracy: 0.2449 - val_loss: 2.3460 - val_accuracy: 0.2022
Epoch 55/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3763 - accuracy: 0.2585 - val_loss: 2.3451 - val_accuracy: 0.2022
Epoch 56/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3854 - accuracy: 0.2627 - val_loss: 2.3443 - val_accuracy: 0.2022
Epoch 57/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3537 - accuracy: 0.2736 - val_loss: 2.3434 - val_accuracy: 0.2022
Epoch 58/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3718 - accuracy: 0.2750 - val_loss: 2.3425 - val_accuracy: 0.2022
Epoch 59/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3558 - accuracy: 0.2709 - val_loss: 2.3416 - val_accuracy: 0.2022
Epoch 60/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3777 - accuracy: 0.2627 - val_loss: 2.3408 - val_accuracy: 0.2077
Epoch 61/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3401 - accuracy: 0.2804 - val_loss: 2.3399 - val_accuracy: 0.2077
Epoch 62/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3821 - accuracy: 0.2750 - val_loss: 2.3390 - val_accuracy: 0.2131
Epoch 63/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3685 - accuracy: 0.3037 - val_loss: 2.3381 - val_accuracy: 0.2131
Epoch 64/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3728 - accuracy: 0.2763 - val_loss: 2.3372 - val_accuracy: 0.2131
Epoch 65/100
3/3 [==============================] - 0s 15ms/step - loss: 2.3601 - accuracy: 0.2709 - val_loss: 2.3364 - val_accuracy: 0.2131
Epoch 66/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3590 - accuracy: 0.2859 - val_loss: 2.3355 - val_accuracy: 0.2131
Epoch 67/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3728 - accuracy: 0.2818 - val_loss: 2.3346 - val_accuracy: 0.2131
Epoch 68/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3588 - accuracy: 0.2818 - val_loss: 2.3338 - val_accuracy: 0.2131
Epoch 69/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3483 - accuracy: 0.3037 - val_loss: 2.3329 - val_accuracy: 0.2131
Epoch 70/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3684 - accuracy: 0.2654 - val_loss: 2.3320 - val_accuracy: 0.2131
Epoch 71/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3516 - accuracy: 0.3064 - val_loss: 2.3312 - val_accuracy: 0.2131
Epoch 72/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3565 - accuracy: 0.2490 - val_loss: 2.3303 - val_accuracy: 0.2131
Epoch 73/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3299 - accuracy: 0.2859 - val_loss: 2.3294 - val_accuracy: 0.2131
Epoch 74/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3442 - accuracy: 0.2640 - val_loss: 2.3285 - val_accuracy: 0.2131
Epoch 75/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3336 - accuracy: 0.2927 - val_loss: 2.3277 - val_accuracy: 0.2131
Epoch 76/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3652 - accuracy: 0.2722 - val_loss: 2.3268 - val_accuracy: 0.2131
Epoch 77/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3505 - accuracy: 0.2818 - val_loss: 2.3259 - val_accuracy: 0.2131
Epoch 78/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3577 - accuracy: 0.2777 - val_loss: 2.3251 - val_accuracy: 0.2131
Epoch 79/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3412 - accuracy: 0.2791 - val_loss: 2.3242 - val_accuracy: 0.2186
Epoch 80/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3310 - accuracy: 0.2804 - val_loss: 2.3233 - val_accuracy: 0.2186
Epoch 81/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3363 - accuracy: 0.3023 - val_loss: 2.3225 - val_accuracy: 0.2186
Epoch 82/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3509 - accuracy: 0.2955 - val_loss: 2.3216 - val_accuracy: 0.2240
Epoch 83/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3591 - accuracy: 0.2763 - val_loss: 2.3208 - val_accuracy: 0.2240
Epoch 84/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3476 - accuracy: 0.2927 - val_loss: 2.3199 - val_accuracy: 0.2240
Epoch 85/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3153 - accuracy: 0.2914 - val_loss: 2.3190 - val_accuracy: 0.2240
Epoch 86/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3471 - accuracy: 0.2996 - val_loss: 2.3182 - val_accuracy: 0.2240
Epoch 87/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3479 - accuracy: 0.2791 - val_loss: 2.3173 - val_accuracy: 0.2240
Epoch 88/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3312 - accuracy: 0.2996 - val_loss: 2.3164 - val_accuracy: 0.2240
Epoch 89/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3437 - accuracy: 0.3037 - val_loss: 2.3156 - val_accuracy: 0.2240
Epoch 90/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3694 - accuracy: 0.2613 - val_loss: 2.3147 - val_accuracy: 0.2295
Epoch 91/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3359 - accuracy: 0.3105 - val_loss: 2.3139 - val_accuracy: 0.2404
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3288 - accuracy: 0.3023 - val_loss: 2.3130 - val_accuracy: 0.2404
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3730 - accuracy: 0.2763 - val_loss: 2.3121 - val_accuracy: 0.2459
Epoch 94/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3401 - accuracy: 0.3228 - val_loss: 2.3113 - val_accuracy: 0.2459
Epoch 95/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3420 - accuracy: 0.3037 - val_loss: 2.3104 - val_accuracy: 0.2514
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3326 - accuracy: 0.2750 - val_loss: 2.3096 - val_accuracy: 0.2514
Epoch 97/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3315 - accuracy: 0.2832 - val_loss: 2.3087 - val_accuracy: 0.2514
Epoch 98/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3281 - accuracy: 0.2804 - val_loss: 2.3079 - val_accuracy: 0.2514
Epoch 99/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3193 - accuracy: 0.3311 - val_loss: 2.3070 - val_accuracy: 0.2459
Epoch 100/100
3/3 [==============================] - 0s 15ms/step - loss: 2.3367 - accuracy: 0.2886 - val_loss: 2.3061 - val_accuracy: 0.2514
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 118ms/step - loss: 2.1540 - accuracy: 0.5609 - val_loss: 2.1438 - val_accuracy: 0.5956
Epoch 2/100
3/3 [==============================] - 0s 25ms/step - loss: 2.1562 - accuracy: 0.5650 - val_loss: 2.1430 - val_accuracy: 0.5956
Epoch 3/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1487 - accuracy: 0.5746 - val_loss: 2.1422 - val_accuracy: 0.5956
Epoch 4/100
3/3 [==============================] - 0s 23ms/step - loss: 2.1480 - accuracy: 0.5663 - val_loss: 2.1416 - val_accuracy: 0.5956
Epoch 5/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1688 - accuracy: 0.5335 - val_loss: 2.1409 - val_accuracy: 0.5956
Epoch 6/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1404 - accuracy: 0.5595 - val_loss: 2.1402 - val_accuracy: 0.6011
Epoch 7/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1523 - accuracy: 0.5581 - val_loss: 2.1396 - val_accuracy: 0.6011
Epoch 8/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1492 - accuracy: 0.5705 - val_loss: 2.1389 - val_accuracy: 0.6011
Epoch 9/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1398 - accuracy: 0.5636 - val_loss: 2.1382 - val_accuracy: 0.6011
Epoch 10/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1499 - accuracy: 0.5773 - val_loss: 2.1376 - val_accuracy: 0.6011
Epoch 11/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1401 - accuracy: 0.5663 - val_loss: 2.1369 - val_accuracy: 0.6011
Epoch 12/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1463 - accuracy: 0.5568 - val_loss: 2.1363 - val_accuracy: 0.6066
Epoch 13/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1529 - accuracy: 0.5677 - val_loss: 2.1356 - val_accuracy: 0.6066
Epoch 14/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1504 - accuracy: 0.5486 - val_loss: 2.1350 - val_accuracy: 0.6066
Epoch 15/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1353 - accuracy: 0.5787 - val_loss: 2.1343 - val_accuracy: 0.6066
Epoch 16/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1461 - accuracy: 0.5855 - val_loss: 2.1337 - val_accuracy: 0.6066
Epoch 17/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1320 - accuracy: 0.5841 - val_loss: 2.1330 - val_accuracy: 0.6120
Epoch 18/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1407 - accuracy: 0.5691 - val_loss: 2.1324 - val_accuracy: 0.6120
Epoch 19/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1512 - accuracy: 0.5677 - val_loss: 2.1317 - val_accuracy: 0.6120
Epoch 20/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1531 - accuracy: 0.5499 - val_loss: 2.1310 - val_accuracy: 0.6120
Epoch 21/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1198 - accuracy: 0.5992 - val_loss: 2.1304 - val_accuracy: 0.6120
Epoch 22/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1314 - accuracy: 0.5882 - val_loss: 2.1297 - val_accuracy: 0.6120
Epoch 23/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1505 - accuracy: 0.5417 - val_loss: 2.1291 - val_accuracy: 0.6120
Epoch 24/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1407 - accuracy: 0.5527 - val_loss: 2.1284 - val_accuracy: 0.6175
Epoch 25/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1336 - accuracy: 0.5773 - val_loss: 2.1278 - val_accuracy: 0.6175
Epoch 26/100
3/3 [==============================] - 0s 23ms/step - loss: 2.1536 - accuracy: 0.5650 - val_loss: 2.1271 - val_accuracy: 0.6175
Epoch 27/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1457 - accuracy: 0.5814 - val_loss: 2.1265 - val_accuracy: 0.6175
Epoch 28/100
3/3 [==============================] - 0s 23ms/step - loss: 2.1614 - accuracy: 0.5513 - val_loss: 2.1258 - val_accuracy: 0.6175
Epoch 29/100
3/3 [==============================] - 0s 23ms/step - loss: 2.1539 - accuracy: 0.5677 - val_loss: 2.1252 - val_accuracy: 0.6175
Epoch 30/100
3/3 [==============================] - 0s 23ms/step - loss: 2.1324 - accuracy: 0.5581 - val_loss: 2.1245 - val_accuracy: 0.6175
Epoch 31/100
3/3 [==============================] - 0s 25ms/step - loss: 2.1243 - accuracy: 0.5732 - val_loss: 2.1239 - val_accuracy: 0.6175
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1241 - accuracy: 0.5951 - val_loss: 2.1232 - val_accuracy: 0.6230
Epoch 33/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1314 - accuracy: 0.5732 - val_loss: 2.1226 - val_accuracy: 0.6230
Epoch 34/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1259 - accuracy: 0.5841 - val_loss: 2.1219 - val_accuracy: 0.6230
Epoch 35/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1256 - accuracy: 0.5773 - val_loss: 2.1213 - val_accuracy: 0.6339
Epoch 36/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1383 - accuracy: 0.5746 - val_loss: 2.1206 - val_accuracy: 0.6339
Epoch 37/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1223 - accuracy: 0.5718 - val_loss: 2.1200 - val_accuracy: 0.6339
Epoch 38/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1392 - accuracy: 0.5677 - val_loss: 2.1193 - val_accuracy: 0.6339
Epoch 39/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1220 - accuracy: 0.5691 - val_loss: 2.1187 - val_accuracy: 0.6339
Epoch 40/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1389 - accuracy: 0.5554 - val_loss: 2.1180 - val_accuracy: 0.6393
Epoch 41/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1212 - accuracy: 0.5910 - val_loss: 2.1174 - val_accuracy: 0.6393
Epoch 42/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1377 - accuracy: 0.5841 - val_loss: 2.1167 - val_accuracy: 0.6393
Epoch 43/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1292 - accuracy: 0.5800 - val_loss: 2.1161 - val_accuracy: 0.6393
Epoch 44/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1301 - accuracy: 0.5896 - val_loss: 2.1155 - val_accuracy: 0.6393
Epoch 45/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1317 - accuracy: 0.5691 - val_loss: 2.1148 - val_accuracy: 0.6393
Epoch 46/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1334 - accuracy: 0.5746 - val_loss: 2.1142 - val_accuracy: 0.6448
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1249 - accuracy: 0.5882 - val_loss: 2.1135 - val_accuracy: 0.6448
Epoch 48/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1180 - accuracy: 0.5937 - val_loss: 2.1129 - val_accuracy: 0.6448
Epoch 49/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1129 - accuracy: 0.5937 - val_loss: 2.1122 - val_accuracy: 0.6448
Epoch 50/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1272 - accuracy: 0.5718 - val_loss: 2.1116 - val_accuracy: 0.6448
Epoch 51/100
3/3 [==============================] - 0s 16ms/step - loss: 2.1360 - accuracy: 0.5663 - val_loss: 2.1109 - val_accuracy: 0.6448
Epoch 52/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1287 - accuracy: 0.5677 - val_loss: 2.1103 - val_accuracy: 0.6503
Epoch 53/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1344 - accuracy: 0.5595 - val_loss: 2.1097 - val_accuracy: 0.6503
Epoch 54/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1073 - accuracy: 0.6019 - val_loss: 2.1090 - val_accuracy: 0.6503
Epoch 55/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1215 - accuracy: 0.5869 - val_loss: 2.1084 - val_accuracy: 0.6503
Epoch 56/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1144 - accuracy: 0.6047 - val_loss: 2.1077 - val_accuracy: 0.6503
Epoch 57/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1069 - accuracy: 0.6088 - val_loss: 2.1071 - val_accuracy: 0.6503
Epoch 58/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1174 - accuracy: 0.5910 - val_loss: 2.1065 - val_accuracy: 0.6503
Epoch 59/100
3/3 [==============================] - 0s 16ms/step - loss: 2.1131 - accuracy: 0.6101 - val_loss: 2.1058 - val_accuracy: 0.6503
Epoch 60/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1187 - accuracy: 0.5882 - val_loss: 2.1052 - val_accuracy: 0.6503
Epoch 61/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1089 - accuracy: 0.6005 - val_loss: 2.1045 - val_accuracy: 0.6503
Epoch 62/100
3/3 [==============================] - 0s 23ms/step - loss: 2.1032 - accuracy: 0.6019 - val_loss: 2.1039 - val_accuracy: 0.6503
Epoch 63/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1075 - accuracy: 0.5937 - val_loss: 2.1033 - val_accuracy: 0.6557
Epoch 64/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1166 - accuracy: 0.5937 - val_loss: 2.1026 - val_accuracy: 0.6557
Epoch 65/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1079 - accuracy: 0.5910 - val_loss: 2.1020 - val_accuracy: 0.6612
Epoch 66/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1100 - accuracy: 0.5828 - val_loss: 2.1013 - val_accuracy: 0.6612
Epoch 67/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1011 - accuracy: 0.6129 - val_loss: 2.1007 - val_accuracy: 0.6612
Epoch 68/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0956 - accuracy: 0.5896 - val_loss: 2.1001 - val_accuracy: 0.6612
Epoch 69/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1055 - accuracy: 0.5923 - val_loss: 2.0994 - val_accuracy: 0.6612
Epoch 70/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1058 - accuracy: 0.5828 - val_loss: 2.0988 - val_accuracy: 0.6612
Epoch 71/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1032 - accuracy: 0.5951 - val_loss: 2.0982 - val_accuracy: 0.6612
Epoch 72/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1089 - accuracy: 0.5978 - val_loss: 2.0975 - val_accuracy: 0.6612
Epoch 73/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1051 - accuracy: 0.6033 - val_loss: 2.0969 - val_accuracy: 0.6612
Epoch 74/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1117 - accuracy: 0.6060 - val_loss: 2.0963 - val_accuracy: 0.6667
Epoch 75/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1028 - accuracy: 0.6224 - val_loss: 2.0956 - val_accuracy: 0.6667
Epoch 76/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1246 - accuracy: 0.5923 - val_loss: 2.0950 - val_accuracy: 0.6721
Epoch 77/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1023 - accuracy: 0.5951 - val_loss: 2.0944 - val_accuracy: 0.6721
Epoch 78/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1064 - accuracy: 0.5992 - val_loss: 2.0937 - val_accuracy: 0.6721
Epoch 79/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1035 - accuracy: 0.5910 - val_loss: 2.0931 - val_accuracy: 0.6721
Epoch 80/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0975 - accuracy: 0.6005 - val_loss: 2.0924 - val_accuracy: 0.6776
Epoch 81/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0969 - accuracy: 0.6033 - val_loss: 2.0918 - val_accuracy: 0.6831
Epoch 82/100
3/3 [==============================] - 0s 27ms/step - loss: 2.0881 - accuracy: 0.6047 - val_loss: 2.0912 - val_accuracy: 0.6831
Epoch 83/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1211 - accuracy: 0.5759 - val_loss: 2.0905 - val_accuracy: 0.6831
Epoch 84/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0825 - accuracy: 0.6347 - val_loss: 2.0899 - val_accuracy: 0.6885
Epoch 85/100
3/3 [==============================] - 0s 18ms/step - loss: 2.0971 - accuracy: 0.6060 - val_loss: 2.0893 - val_accuracy: 0.6885
Epoch 86/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0861 - accuracy: 0.6101 - val_loss: 2.0886 - val_accuracy: 0.6885
Epoch 87/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1040 - accuracy: 0.6047 - val_loss: 2.0880 - val_accuracy: 0.6885
Epoch 88/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0809 - accuracy: 0.6101 - val_loss: 2.0874 - val_accuracy: 0.6940
Epoch 89/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0707 - accuracy: 0.6334 - val_loss: 2.0868 - val_accuracy: 0.6940
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0855 - accuracy: 0.6129 - val_loss: 2.0861 - val_accuracy: 0.6995
Epoch 91/100
3/3 [==============================] - 0s 24ms/step - loss: 2.0898 - accuracy: 0.6005 - val_loss: 2.0855 - val_accuracy: 0.6995
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0976 - accuracy: 0.5978 - val_loss: 2.0848 - val_accuracy: 0.7049
Epoch 93/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0960 - accuracy: 0.5951 - val_loss: 2.0842 - val_accuracy: 0.7049
Epoch 94/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0755 - accuracy: 0.6183 - val_loss: 2.0836 - val_accuracy: 0.7049
Epoch 95/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1058 - accuracy: 0.6033 - val_loss: 2.0830 - val_accuracy: 0.7049
Epoch 96/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1009 - accuracy: 0.6019 - val_loss: 2.0823 - val_accuracy: 0.7104
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0839 - accuracy: 0.6197 - val_loss: 2.0817 - val_accuracy: 0.7104
Epoch 98/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0893 - accuracy: 0.6306 - val_loss: 2.0811 - val_accuracy: 0.7104
Epoch 99/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0792 - accuracy: 0.6320 - val_loss: 2.0805 - val_accuracy: 0.7104
Epoch 100/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0971 - accuracy: 0.6142 - val_loss: 2.0798 - val_accuracy: 0.7104
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 118ms/step - loss: 2.5087 - accuracy: 0.2230 - val_loss: 2.4912 - val_accuracy: 0.2404
Epoch 2/100
3/3 [==============================] - 0s 22ms/step - loss: 2.5144 - accuracy: 0.2312 - val_loss: 2.4900 - val_accuracy: 0.2404
Epoch 3/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4928 - accuracy: 0.2312 - val_loss: 2.4890 - val_accuracy: 0.2404
Epoch 4/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5168 - accuracy: 0.2285 - val_loss: 2.4880 - val_accuracy: 0.2404
Epoch 5/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5161 - accuracy: 0.2216 - val_loss: 2.4871 - val_accuracy: 0.2404
Epoch 6/100
3/3 [==============================] - 0s 28ms/step - loss: 2.5044 - accuracy: 0.2312 - val_loss: 2.4861 - val_accuracy: 0.2404
Epoch 7/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5204 - accuracy: 0.2449 - val_loss: 2.4852 - val_accuracy: 0.2404
Epoch 8/100
3/3 [==============================] - 0s 27ms/step - loss: 2.5266 - accuracy: 0.2435 - val_loss: 2.4842 - val_accuracy: 0.2404
Epoch 9/100
3/3 [==============================] - 0s 22ms/step - loss: 2.5092 - accuracy: 0.2271 - val_loss: 2.4833 - val_accuracy: 0.2404
Epoch 10/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4969 - accuracy: 0.2161 - val_loss: 2.4824 - val_accuracy: 0.2404
Epoch 11/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5023 - accuracy: 0.2558 - val_loss: 2.4814 - val_accuracy: 0.2459
Epoch 12/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4982 - accuracy: 0.2544 - val_loss: 2.4805 - val_accuracy: 0.2459
Epoch 13/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5081 - accuracy: 0.2161 - val_loss: 2.4796 - val_accuracy: 0.2514
Epoch 14/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4843 - accuracy: 0.2367 - val_loss: 2.4786 - val_accuracy: 0.2514
Epoch 15/100
3/3 [==============================] - 0s 22ms/step - loss: 2.5024 - accuracy: 0.2408 - val_loss: 2.4777 - val_accuracy: 0.2514
Epoch 16/100
3/3 [==============================] - 0s 24ms/step - loss: 2.5127 - accuracy: 0.2408 - val_loss: 2.4768 - val_accuracy: 0.2514
Epoch 17/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5089 - accuracy: 0.2476 - val_loss: 2.4758 - val_accuracy: 0.2514
Epoch 18/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4988 - accuracy: 0.2367 - val_loss: 2.4749 - val_accuracy: 0.2514
Epoch 19/100
3/3 [==============================] - 0s 22ms/step - loss: 2.5012 - accuracy: 0.2558 - val_loss: 2.4740 - val_accuracy: 0.2514
Epoch 20/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5027 - accuracy: 0.2298 - val_loss: 2.4730 - val_accuracy: 0.2678
Epoch 21/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4954 - accuracy: 0.2380 - val_loss: 2.4721 - val_accuracy: 0.2678
Epoch 22/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4843 - accuracy: 0.2613 - val_loss: 2.4712 - val_accuracy: 0.2678
Epoch 23/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5087 - accuracy: 0.2490 - val_loss: 2.4702 - val_accuracy: 0.2678
Epoch 24/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5074 - accuracy: 0.2312 - val_loss: 2.4693 - val_accuracy: 0.2678
Epoch 25/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4827 - accuracy: 0.2558 - val_loss: 2.4684 - val_accuracy: 0.2678
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5067 - accuracy: 0.2271 - val_loss: 2.4675 - val_accuracy: 0.2732
Epoch 27/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4876 - accuracy: 0.2490 - val_loss: 2.4665 - val_accuracy: 0.2732
Epoch 28/100
3/3 [==============================] - 0s 26ms/step - loss: 2.5025 - accuracy: 0.2627 - val_loss: 2.4656 - val_accuracy: 0.2732
Epoch 29/100
3/3 [==============================] - 0s 26ms/step - loss: 2.4810 - accuracy: 0.2544 - val_loss: 2.4647 - val_accuracy: 0.2732
Epoch 30/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4851 - accuracy: 0.2202 - val_loss: 2.4638 - val_accuracy: 0.2732
Epoch 31/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4978 - accuracy: 0.2408 - val_loss: 2.4628 - val_accuracy: 0.2732
Epoch 32/100
3/3 [==============================] - 0s 15ms/step - loss: 2.4972 - accuracy: 0.2367 - val_loss: 2.4619 - val_accuracy: 0.2732
Epoch 33/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4782 - accuracy: 0.2572 - val_loss: 2.4610 - val_accuracy: 0.2732
Epoch 34/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4736 - accuracy: 0.2462 - val_loss: 2.4601 - val_accuracy: 0.2787
Epoch 35/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4794 - accuracy: 0.2408 - val_loss: 2.4592 - val_accuracy: 0.2787
Epoch 36/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4898 - accuracy: 0.2449 - val_loss: 2.4582 - val_accuracy: 0.2787
Epoch 37/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4924 - accuracy: 0.2544 - val_loss: 2.4573 - val_accuracy: 0.2787
Epoch 38/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4721 - accuracy: 0.2544 - val_loss: 2.4564 - val_accuracy: 0.2842
Epoch 39/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4682 - accuracy: 0.2558 - val_loss: 2.4555 - val_accuracy: 0.2842
Epoch 40/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4723 - accuracy: 0.2367 - val_loss: 2.4546 - val_accuracy: 0.2842
Epoch 41/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4828 - accuracy: 0.2449 - val_loss: 2.4536 - val_accuracy: 0.2842
Epoch 42/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4881 - accuracy: 0.2435 - val_loss: 2.4527 - val_accuracy: 0.2842
Epoch 43/100
3/3 [==============================] - 0s 22ms/step - loss: 2.4857 - accuracy: 0.2408 - val_loss: 2.4518 - val_accuracy: 0.2842
Epoch 44/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4780 - accuracy: 0.2531 - val_loss: 2.4509 - val_accuracy: 0.2842
Epoch 45/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4915 - accuracy: 0.2462 - val_loss: 2.4500 - val_accuracy: 0.2842
Epoch 46/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4621 - accuracy: 0.2517 - val_loss: 2.4491 - val_accuracy: 0.2896
Epoch 47/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4831 - accuracy: 0.2627 - val_loss: 2.4481 - val_accuracy: 0.2896
Epoch 48/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4688 - accuracy: 0.2503 - val_loss: 2.4472 - val_accuracy: 0.2896
Epoch 49/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4717 - accuracy: 0.2476 - val_loss: 2.4463 - val_accuracy: 0.2896
Epoch 50/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4766 - accuracy: 0.2585 - val_loss: 2.4454 - val_accuracy: 0.2896
Epoch 51/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4705 - accuracy: 0.2558 - val_loss: 2.4445 - val_accuracy: 0.2896
Epoch 52/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4903 - accuracy: 0.2640 - val_loss: 2.4436 - val_accuracy: 0.2896
Epoch 53/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4810 - accuracy: 0.2722 - val_loss: 2.4427 - val_accuracy: 0.2896
Epoch 54/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4684 - accuracy: 0.2517 - val_loss: 2.4417 - val_accuracy: 0.2896
Epoch 55/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4913 - accuracy: 0.2572 - val_loss: 2.4408 - val_accuracy: 0.2896
Epoch 56/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4828 - accuracy: 0.2503 - val_loss: 2.4399 - val_accuracy: 0.2896
Epoch 57/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4580 - accuracy: 0.2544 - val_loss: 2.4390 - val_accuracy: 0.2896
Epoch 58/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4441 - accuracy: 0.2695 - val_loss: 2.4381 - val_accuracy: 0.2951
Epoch 59/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4513 - accuracy: 0.2613 - val_loss: 2.4372 - val_accuracy: 0.2951
Epoch 60/100
3/3 [==============================] - 0s 29ms/step - loss: 2.4635 - accuracy: 0.2722 - val_loss: 2.4363 - val_accuracy: 0.3005
Epoch 61/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4661 - accuracy: 0.2627 - val_loss: 2.4354 - val_accuracy: 0.3005
Epoch 62/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4631 - accuracy: 0.2435 - val_loss: 2.4345 - val_accuracy: 0.3005
Epoch 63/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4725 - accuracy: 0.2585 - val_loss: 2.4336 - val_accuracy: 0.3005
Epoch 64/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4625 - accuracy: 0.2709 - val_loss: 2.4326 - val_accuracy: 0.3005
Epoch 65/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4730 - accuracy: 0.2750 - val_loss: 2.4317 - val_accuracy: 0.3005
Epoch 66/100
3/3 [==============================] - 0s 22ms/step - loss: 2.4606 - accuracy: 0.2695 - val_loss: 2.4308 - val_accuracy: 0.3005
Epoch 67/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4395 - accuracy: 0.2709 - val_loss: 2.4299 - val_accuracy: 0.3005
Epoch 68/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4517 - accuracy: 0.2640 - val_loss: 2.4290 - val_accuracy: 0.3005
Epoch 69/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4684 - accuracy: 0.2544 - val_loss: 2.4281 - val_accuracy: 0.3005
Epoch 70/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4633 - accuracy: 0.2531 - val_loss: 2.4272 - val_accuracy: 0.3005
Epoch 71/100
3/3 [==============================] - 0s 34ms/step - loss: 2.4482 - accuracy: 0.2585 - val_loss: 2.4263 - val_accuracy: 0.3005
Epoch 72/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4484 - accuracy: 0.2736 - val_loss: 2.4254 - val_accuracy: 0.3005
Epoch 73/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4502 - accuracy: 0.2654 - val_loss: 2.4245 - val_accuracy: 0.3005
Epoch 74/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4553 - accuracy: 0.2791 - val_loss: 2.4236 - val_accuracy: 0.3005
Epoch 75/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4370 - accuracy: 0.2791 - val_loss: 2.4227 - val_accuracy: 0.3005
Epoch 76/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4676 - accuracy: 0.2627 - val_loss: 2.4218 - val_accuracy: 0.3005
Epoch 77/100
3/3 [==============================] - 0s 22ms/step - loss: 2.4534 - accuracy: 0.2640 - val_loss: 2.4209 - val_accuracy: 0.3005
Epoch 78/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4319 - accuracy: 0.2777 - val_loss: 2.4200 - val_accuracy: 0.3005
Epoch 79/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4466 - accuracy: 0.2681 - val_loss: 2.4191 - val_accuracy: 0.3005
Epoch 80/100
3/3 [==============================] - 0s 22ms/step - loss: 2.4629 - accuracy: 0.2531 - val_loss: 2.4181 - val_accuracy: 0.3005
Epoch 81/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4500 - accuracy: 0.2462 - val_loss: 2.4172 - val_accuracy: 0.3005
Epoch 82/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4247 - accuracy: 0.2804 - val_loss: 2.4164 - val_accuracy: 0.3005
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4411 - accuracy: 0.2955 - val_loss: 2.4155 - val_accuracy: 0.3005
Epoch 84/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4552 - accuracy: 0.2777 - val_loss: 2.4146 - val_accuracy: 0.3005
Epoch 85/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4355 - accuracy: 0.2886 - val_loss: 2.4137 - val_accuracy: 0.3005
Epoch 86/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4500 - accuracy: 0.2927 - val_loss: 2.4128 - val_accuracy: 0.3005
Epoch 87/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4498 - accuracy: 0.2668 - val_loss: 2.4119 - val_accuracy: 0.3005
Epoch 88/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4431 - accuracy: 0.2804 - val_loss: 2.4110 - val_accuracy: 0.3005
Epoch 89/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4439 - accuracy: 0.2886 - val_loss: 2.4101 - val_accuracy: 0.3005
Epoch 90/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4276 - accuracy: 0.2709 - val_loss: 2.4092 - val_accuracy: 0.3060
Epoch 91/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4184 - accuracy: 0.2927 - val_loss: 2.4083 - val_accuracy: 0.3060
Epoch 92/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4341 - accuracy: 0.2640 - val_loss: 2.4074 - val_accuracy: 0.3060
Epoch 93/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4348 - accuracy: 0.2873 - val_loss: 2.4065 - val_accuracy: 0.3060
Epoch 94/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4413 - accuracy: 0.2517 - val_loss: 2.4056 - val_accuracy: 0.3060
Epoch 95/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4299 - accuracy: 0.2914 - val_loss: 2.4047 - val_accuracy: 0.3060
Epoch 96/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4359 - accuracy: 0.2709 - val_loss: 2.4038 - val_accuracy: 0.3060
Epoch 97/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4097 - accuracy: 0.2804 - val_loss: 2.4029 - val_accuracy: 0.3060
Epoch 98/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4362 - accuracy: 0.2969 - val_loss: 2.4020 - val_accuracy: 0.3060
Epoch 99/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4181 - accuracy: 0.2818 - val_loss: 2.4011 - val_accuracy: 0.3060
Epoch 100/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4641 - accuracy: 0.2627 - val_loss: 2.4002 - val_accuracy: 0.3060
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 5, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8}
Batch size: 256
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
3/3 [==============================] - 1s 107ms/step - loss: 2.3497 - accuracy: 0.3224 - val_loss: 2.3352 - val_accuracy: 0.1923
Epoch 2/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3732 - accuracy: 0.2855 - val_loss: 2.3341 - val_accuracy: 0.1923
Epoch 3/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3654 - accuracy: 0.3087 - val_loss: 2.3331 - val_accuracy: 0.1923
Epoch 4/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3941 - accuracy: 0.2691 - val_loss: 2.3322 - val_accuracy: 0.1978
Epoch 5/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3632 - accuracy: 0.3101 - val_loss: 2.3313 - val_accuracy: 0.1978
Epoch 6/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3704 - accuracy: 0.3033 - val_loss: 2.3305 - val_accuracy: 0.1978
Epoch 7/100
3/3 [==============================] - 0s 27ms/step - loss: 2.3680 - accuracy: 0.3169 - val_loss: 2.3296 - val_accuracy: 0.2033
Epoch 8/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3514 - accuracy: 0.3033 - val_loss: 2.3288 - val_accuracy: 0.2033
Epoch 9/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3687 - accuracy: 0.2910 - val_loss: 2.3279 - val_accuracy: 0.2033
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3659 - accuracy: 0.2978 - val_loss: 2.3270 - val_accuracy: 0.2033
Epoch 11/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3581 - accuracy: 0.2842 - val_loss: 2.3262 - val_accuracy: 0.2143
Epoch 12/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3564 - accuracy: 0.2951 - val_loss: 2.3253 - val_accuracy: 0.2198
Epoch 13/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3727 - accuracy: 0.2896 - val_loss: 2.3244 - val_accuracy: 0.2198
Epoch 14/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3745 - accuracy: 0.2787 - val_loss: 2.3236 - val_accuracy: 0.2198
Epoch 15/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3464 - accuracy: 0.3074 - val_loss: 2.3227 - val_accuracy: 0.2198
Epoch 16/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3564 - accuracy: 0.3156 - val_loss: 2.3219 - val_accuracy: 0.2198
Epoch 17/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3641 - accuracy: 0.2964 - val_loss: 2.3210 - val_accuracy: 0.2198
Epoch 18/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3440 - accuracy: 0.3197 - val_loss: 2.3201 - val_accuracy: 0.2253
Epoch 19/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3669 - accuracy: 0.2814 - val_loss: 2.3193 - val_accuracy: 0.2308
Epoch 20/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3687 - accuracy: 0.2883 - val_loss: 2.3184 - val_accuracy: 0.2473
Epoch 21/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3628 - accuracy: 0.3060 - val_loss: 2.3176 - val_accuracy: 0.2473
Epoch 22/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3561 - accuracy: 0.3210 - val_loss: 2.3167 - val_accuracy: 0.2473
Epoch 23/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3477 - accuracy: 0.3251 - val_loss: 2.3158 - val_accuracy: 0.2473
Epoch 24/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3590 - accuracy: 0.3033 - val_loss: 2.3150 - val_accuracy: 0.2473
Epoch 25/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3624 - accuracy: 0.3169 - val_loss: 2.3141 - val_accuracy: 0.2473
Epoch 26/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3532 - accuracy: 0.3074 - val_loss: 2.3133 - val_accuracy: 0.2473
Epoch 27/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3644 - accuracy: 0.2964 - val_loss: 2.3124 - val_accuracy: 0.2473
Epoch 28/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3398 - accuracy: 0.3306 - val_loss: 2.3116 - val_accuracy: 0.2473
Epoch 29/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3464 - accuracy: 0.3169 - val_loss: 2.3107 - val_accuracy: 0.2473
Epoch 30/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3441 - accuracy: 0.3251 - val_loss: 2.3099 - val_accuracy: 0.2582
Epoch 31/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3479 - accuracy: 0.3210 - val_loss: 2.3090 - val_accuracy: 0.2582
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3369 - accuracy: 0.2978 - val_loss: 2.3082 - val_accuracy: 0.2582
Epoch 33/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3673 - accuracy: 0.2937 - val_loss: 2.3073 - val_accuracy: 0.2582
Epoch 34/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3496 - accuracy: 0.3292 - val_loss: 2.3065 - val_accuracy: 0.2637
Epoch 35/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3519 - accuracy: 0.3101 - val_loss: 2.3056 - val_accuracy: 0.2692
Epoch 36/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3243 - accuracy: 0.3374 - val_loss: 2.3048 - val_accuracy: 0.2692
Epoch 37/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3380 - accuracy: 0.2951 - val_loss: 2.3039 - val_accuracy: 0.2692
Epoch 38/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3229 - accuracy: 0.3579 - val_loss: 2.3031 - val_accuracy: 0.2692
Epoch 39/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3470 - accuracy: 0.3279 - val_loss: 2.3022 - val_accuracy: 0.2692
Epoch 40/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3387 - accuracy: 0.3169 - val_loss: 2.3014 - val_accuracy: 0.2692
Epoch 41/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3303 - accuracy: 0.3456 - val_loss: 2.3005 - val_accuracy: 0.2692
Epoch 42/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3232 - accuracy: 0.3210 - val_loss: 2.2997 - val_accuracy: 0.2692
Epoch 43/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3251 - accuracy: 0.3251 - val_loss: 2.2988 - val_accuracy: 0.2692
Epoch 44/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3380 - accuracy: 0.3265 - val_loss: 2.2980 - val_accuracy: 0.2692
Epoch 45/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3286 - accuracy: 0.3456 - val_loss: 2.2971 - val_accuracy: 0.2692
Epoch 46/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3330 - accuracy: 0.3402 - val_loss: 2.2963 - val_accuracy: 0.2692
Epoch 47/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3287 - accuracy: 0.3511 - val_loss: 2.2954 - val_accuracy: 0.2747
Epoch 48/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3381 - accuracy: 0.3511 - val_loss: 2.2946 - val_accuracy: 0.2747
Epoch 49/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3400 - accuracy: 0.3402 - val_loss: 2.2937 - val_accuracy: 0.2802
Epoch 50/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3269 - accuracy: 0.3347 - val_loss: 2.2929 - val_accuracy: 0.2802
Epoch 51/100
3/3 [==============================] - 0s 27ms/step - loss: 2.3167 - accuracy: 0.3197 - val_loss: 2.2921 - val_accuracy: 0.2802
Epoch 52/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3229 - accuracy: 0.3306 - val_loss: 2.2912 - val_accuracy: 0.2857
Epoch 53/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3256 - accuracy: 0.3470 - val_loss: 2.2904 - val_accuracy: 0.2857
Epoch 54/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3354 - accuracy: 0.3183 - val_loss: 2.2895 - val_accuracy: 0.2857
Epoch 55/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3222 - accuracy: 0.3265 - val_loss: 2.2887 - val_accuracy: 0.2857
Epoch 56/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3212 - accuracy: 0.3415 - val_loss: 2.2878 - val_accuracy: 0.2857
Epoch 57/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3247 - accuracy: 0.3388 - val_loss: 2.2870 - val_accuracy: 0.2857
Epoch 58/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3406 - accuracy: 0.3183 - val_loss: 2.2861 - val_accuracy: 0.2857
Epoch 59/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3239 - accuracy: 0.3525 - val_loss: 2.2853 - val_accuracy: 0.2857
Epoch 60/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3433 - accuracy: 0.3197 - val_loss: 2.2845 - val_accuracy: 0.2912
Epoch 61/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3082 - accuracy: 0.3593 - val_loss: 2.2836 - val_accuracy: 0.2967
Epoch 62/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3033 - accuracy: 0.3743 - val_loss: 2.2828 - val_accuracy: 0.2967
Epoch 63/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3114 - accuracy: 0.3538 - val_loss: 2.2820 - val_accuracy: 0.2967
Epoch 64/100
3/3 [==============================] - 0s 13ms/step - loss: 2.3101 - accuracy: 0.3402 - val_loss: 2.2811 - val_accuracy: 0.2967
Epoch 65/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3101 - accuracy: 0.3347 - val_loss: 2.2803 - val_accuracy: 0.2967
Epoch 66/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3182 - accuracy: 0.3388 - val_loss: 2.2794 - val_accuracy: 0.2967
Epoch 67/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3141 - accuracy: 0.3634 - val_loss: 2.2786 - val_accuracy: 0.2967
Epoch 68/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3111 - accuracy: 0.3579 - val_loss: 2.2778 - val_accuracy: 0.2967
Epoch 69/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3225 - accuracy: 0.3415 - val_loss: 2.2769 - val_accuracy: 0.2967
Epoch 70/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3274 - accuracy: 0.3265 - val_loss: 2.2761 - val_accuracy: 0.3022
Epoch 71/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3174 - accuracy: 0.3757 - val_loss: 2.2753 - val_accuracy: 0.3022
Epoch 72/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3189 - accuracy: 0.3210 - val_loss: 2.2744 - val_accuracy: 0.3022
Epoch 73/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2994 - accuracy: 0.3743 - val_loss: 2.2736 - val_accuracy: 0.3077
Epoch 74/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3067 - accuracy: 0.3456 - val_loss: 2.2728 - val_accuracy: 0.3077
Epoch 75/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3253 - accuracy: 0.3648 - val_loss: 2.2720 - val_accuracy: 0.3077
Epoch 76/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3207 - accuracy: 0.3292 - val_loss: 2.2711 - val_accuracy: 0.3077
Epoch 77/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3168 - accuracy: 0.3497 - val_loss: 2.2703 - val_accuracy: 0.3077
Epoch 78/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2971 - accuracy: 0.3702 - val_loss: 2.2695 - val_accuracy: 0.3132
Epoch 79/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2880 - accuracy: 0.3770 - val_loss: 2.2686 - val_accuracy: 0.3132
Epoch 80/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2954 - accuracy: 0.3689 - val_loss: 2.2678 - val_accuracy: 0.3132
Epoch 81/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2991 - accuracy: 0.3593 - val_loss: 2.2670 - val_accuracy: 0.3187
Epoch 82/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3071 - accuracy: 0.3374 - val_loss: 2.2661 - val_accuracy: 0.3187
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3034 - accuracy: 0.3716 - val_loss: 2.2653 - val_accuracy: 0.3187
Epoch 84/100
3/3 [==============================] - 0s 16ms/step - loss: 2.2905 - accuracy: 0.3921 - val_loss: 2.2645 - val_accuracy: 0.3242
Epoch 85/100
3/3 [==============================] - 0s 16ms/step - loss: 2.2926 - accuracy: 0.3593 - val_loss: 2.2637 - val_accuracy: 0.3242
Epoch 86/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2864 - accuracy: 0.3593 - val_loss: 2.2628 - val_accuracy: 0.3297
Epoch 87/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2934 - accuracy: 0.3593 - val_loss: 2.2620 - val_accuracy: 0.3352
Epoch 88/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2934 - accuracy: 0.3730 - val_loss: 2.2612 - val_accuracy: 0.3352
Epoch 89/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2970 - accuracy: 0.3607 - val_loss: 2.2603 - val_accuracy: 0.3352
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3068 - accuracy: 0.3607 - val_loss: 2.2595 - val_accuracy: 0.3352
Epoch 91/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2842 - accuracy: 0.3798 - val_loss: 2.2587 - val_accuracy: 0.3352
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2960 - accuracy: 0.3484 - val_loss: 2.2579 - val_accuracy: 0.3352
Epoch 93/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2868 - accuracy: 0.3934 - val_loss: 2.2570 - val_accuracy: 0.3352
Epoch 94/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2875 - accuracy: 0.3962 - val_loss: 2.2562 - val_accuracy: 0.3352
Epoch 95/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2993 - accuracy: 0.3593 - val_loss: 2.2554 - val_accuracy: 0.3352
Epoch 96/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2871 - accuracy: 0.3852 - val_loss: 2.2546 - val_accuracy: 0.3352
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2870 - accuracy: 0.3661 - val_loss: 2.2537 - val_accuracy: 0.3352
Epoch 98/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2902 - accuracy: 0.3607 - val_loss: 2.2529 - val_accuracy: 0.3352
Epoch 99/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2882 - accuracy: 0.3989 - val_loss: 2.2521 - val_accuracy: 0.3352
Epoch 100/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2843 - accuracy: 0.3811 - val_loss: 2.2513 - val_accuracy: 0.3352
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 395us/step
Experiment number: 6
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 128
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
6/6 [==============================] - 1s 46ms/step - loss: 11.5538 - accuracy: 0.1710 - val_loss: 11.5224 - val_accuracy: 0.1475
Epoch 2/100
6/6 [==============================] - 0s 12ms/step - loss: 11.5380 - accuracy: 0.1874 - val_loss: 11.5167 - val_accuracy: 0.1475
Epoch 3/100
6/6 [==============================] - 0s 10ms/step - loss: 11.5453 - accuracy: 0.1696 - val_loss: 11.5075 - val_accuracy: 0.1475
Epoch 4/100
6/6 [==============================] - 0s 9ms/step - loss: 11.5173 - accuracy: 0.1792 - val_loss: 11.4948 - val_accuracy: 0.1585
Epoch 5/100
6/6 [==============================] - 0s 10ms/step - loss: 11.5117 - accuracy: 0.1888 - val_loss: 11.4786 - val_accuracy: 0.1585
Epoch 6/100
6/6 [==============================] - 0s 11ms/step - loss: 11.5026 - accuracy: 0.1984 - val_loss: 11.4590 - val_accuracy: 0.1694
Epoch 7/100
6/6 [==============================] - 0s 9ms/step - loss: 11.4732 - accuracy: 0.1874 - val_loss: 11.4359 - val_accuracy: 0.1694
Epoch 8/100
6/6 [==============================] - 0s 10ms/step - loss: 11.4506 - accuracy: 0.2093 - val_loss: 11.4095 - val_accuracy: 0.1913
Epoch 9/100
6/6 [==============================] - 0s 18ms/step - loss: 11.4191 - accuracy: 0.1860 - val_loss: 11.3797 - val_accuracy: 0.1967
Epoch 10/100
6/6 [==============================] - 0s 10ms/step - loss: 11.3786 - accuracy: 0.2285 - val_loss: 11.3468 - val_accuracy: 0.1967
Epoch 11/100
6/6 [==============================] - 0s 9ms/step - loss: 11.3391 - accuracy: 0.2367 - val_loss: 11.3107 - val_accuracy: 0.2131
Epoch 12/100
6/6 [==============================] - 0s 8ms/step - loss: 11.3269 - accuracy: 0.2011 - val_loss: 11.2715 - val_accuracy: 0.2240
Epoch 13/100
6/6 [==============================] - 0s 9ms/step - loss: 11.2742 - accuracy: 0.2271 - val_loss: 11.2292 - val_accuracy: 0.2404
Epoch 14/100
6/6 [==============================] - 0s 9ms/step - loss: 11.2271 - accuracy: 0.2531 - val_loss: 11.1839 - val_accuracy: 0.2514
Epoch 15/100
6/6 [==============================] - 0s 10ms/step - loss: 11.1762 - accuracy: 0.2599 - val_loss: 11.1356 - val_accuracy: 0.2732
Epoch 16/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1430 - accuracy: 0.2777 - val_loss: 11.0846 - val_accuracy: 0.2787
Epoch 17/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1034 - accuracy: 0.2832 - val_loss: 11.0309 - val_accuracy: 0.2951
Epoch 18/100
6/6 [==============================] - 0s 10ms/step - loss: 11.0249 - accuracy: 0.2804 - val_loss: 10.9745 - val_accuracy: 0.3224
Epoch 19/100
6/6 [==============================] - 0s 9ms/step - loss: 10.9530 - accuracy: 0.3338 - val_loss: 10.9159 - val_accuracy: 0.3497
Epoch 20/100
6/6 [==============================] - 0s 9ms/step - loss: 10.9185 - accuracy: 0.3406 - val_loss: 10.8548 - val_accuracy: 0.3607
Epoch 21/100
6/6 [==============================] - 0s 10ms/step - loss: 10.8581 - accuracy: 0.3625 - val_loss: 10.7911 - val_accuracy: 0.3661
Epoch 22/100
6/6 [==============================] - 0s 9ms/step - loss: 10.7792 - accuracy: 0.3995 - val_loss: 10.7254 - val_accuracy: 0.3825
Epoch 23/100
6/6 [==============================] - 0s 9ms/step - loss: 10.7264 - accuracy: 0.3940 - val_loss: 10.6575 - val_accuracy: 0.4044
Epoch 24/100
6/6 [==============================] - 0s 9ms/step - loss: 10.6421 - accuracy: 0.4022 - val_loss: 10.5873 - val_accuracy: 0.4317
Epoch 25/100
6/6 [==============================] - 0s 9ms/step - loss: 10.5755 - accuracy: 0.4378 - val_loss: 10.5150 - val_accuracy: 0.4536
Epoch 26/100
6/6 [==============================] - 0s 9ms/step - loss: 10.4928 - accuracy: 0.4514 - val_loss: 10.4405 - val_accuracy: 0.4809
Epoch 27/100
6/6 [==============================] - 0s 10ms/step - loss: 10.4218 - accuracy: 0.4952 - val_loss: 10.3643 - val_accuracy: 0.5301
Epoch 28/100
6/6 [==============================] - 0s 9ms/step - loss: 10.3426 - accuracy: 0.5130 - val_loss: 10.2864 - val_accuracy: 0.5410
Epoch 29/100
6/6 [==============================] - 0s 10ms/step - loss: 10.2691 - accuracy: 0.5116 - val_loss: 10.2072 - val_accuracy: 0.5683
Epoch 30/100
6/6 [==============================] - 0s 10ms/step - loss: 10.1778 - accuracy: 0.5540 - val_loss: 10.1264 - val_accuracy: 0.6011
Epoch 31/100
6/6 [==============================] - 0s 9ms/step - loss: 10.1043 - accuracy: 0.5773 - val_loss: 10.0438 - val_accuracy: 0.6175
Epoch 32/100
6/6 [==============================] - 0s 9ms/step - loss: 10.0313 - accuracy: 0.5746 - val_loss: 9.9591 - val_accuracy: 0.6284
Epoch 33/100
6/6 [==============================] - 0s 10ms/step - loss: 9.9303 - accuracy: 0.6170 - val_loss: 9.8733 - val_accuracy: 0.6393
Epoch 34/100
6/6 [==============================] - 0s 9ms/step - loss: 9.8519 - accuracy: 0.6306 - val_loss: 9.7863 - val_accuracy: 0.6557
Epoch 35/100
6/6 [==============================] - 0s 10ms/step - loss: 9.7478 - accuracy: 0.6676 - val_loss: 9.6977 - val_accuracy: 0.6557
Epoch 36/100
6/6 [==============================] - 0s 9ms/step - loss: 9.6624 - accuracy: 0.6662 - val_loss: 9.6080 - val_accuracy: 0.6721
Epoch 37/100
6/6 [==============================] - 0s 10ms/step - loss: 9.5649 - accuracy: 0.7031 - val_loss: 9.5176 - val_accuracy: 0.6885
Epoch 38/100
6/6 [==============================] - 0s 11ms/step - loss: 9.4853 - accuracy: 0.6867 - val_loss: 9.4258 - val_accuracy: 0.7049
Epoch 39/100
6/6 [==============================] - 0s 11ms/step - loss: 9.3820 - accuracy: 0.7305 - val_loss: 9.3329 - val_accuracy: 0.7213
Epoch 40/100
6/6 [==============================] - 0s 10ms/step - loss: 9.3056 - accuracy: 0.7278 - val_loss: 9.2393 - val_accuracy: 0.7322
Epoch 41/100
6/6 [==============================] - 0s 10ms/step - loss: 9.2040 - accuracy: 0.7373 - val_loss: 9.1447 - val_accuracy: 0.7541
Epoch 42/100
6/6 [==============================] - 0s 9ms/step - loss: 9.1035 - accuracy: 0.7647 - val_loss: 9.0493 - val_accuracy: 0.7650
Epoch 43/100
6/6 [==============================] - 0s 9ms/step - loss: 9.0056 - accuracy: 0.7784 - val_loss: 8.9532 - val_accuracy: 0.7650
Epoch 44/100
6/6 [==============================] - 0s 10ms/step - loss: 8.8997 - accuracy: 0.7770 - val_loss: 8.8568 - val_accuracy: 0.7760
Epoch 45/100
6/6 [==============================] - 0s 10ms/step - loss: 8.8140 - accuracy: 0.7921 - val_loss: 8.7600 - val_accuracy: 0.7760
Epoch 46/100
6/6 [==============================] - 0s 9ms/step - loss: 8.7112 - accuracy: 0.8030 - val_loss: 8.6627 - val_accuracy: 0.7705
Epoch 47/100
6/6 [==============================] - 0s 9ms/step - loss: 8.6132 - accuracy: 0.8044 - val_loss: 8.5648 - val_accuracy: 0.7760
Epoch 48/100
6/6 [==============================] - 0s 9ms/step - loss: 8.5064 - accuracy: 0.8222 - val_loss: 8.4671 - val_accuracy: 0.7760
Epoch 49/100
6/6 [==============================] - 0s 9ms/step - loss: 8.4193 - accuracy: 0.8208 - val_loss: 8.3689 - val_accuracy: 0.7760
Epoch 50/100
6/6 [==============================] - 0s 12ms/step - loss: 8.3110 - accuracy: 0.8331 - val_loss: 8.2705 - val_accuracy: 0.7869
Epoch 51/100
6/6 [==============================] - 0s 9ms/step - loss: 8.2098 - accuracy: 0.8399 - val_loss: 8.1722 - val_accuracy: 0.7869
Epoch 52/100
6/6 [==============================] - 0s 9ms/step - loss: 8.1065 - accuracy: 0.8427 - val_loss: 8.0733 - val_accuracy: 0.7923
Epoch 53/100
6/6 [==============================] - 0s 9ms/step - loss: 8.0050 - accuracy: 0.8523 - val_loss: 7.9741 - val_accuracy: 0.7978
Epoch 54/100
6/6 [==============================] - 0s 9ms/step - loss: 7.8994 - accuracy: 0.8577 - val_loss: 7.8743 - val_accuracy: 0.7923
Epoch 55/100
6/6 [==============================] - 0s 9ms/step - loss: 7.8035 - accuracy: 0.8605 - val_loss: 7.7747 - val_accuracy: 0.7923
Epoch 56/100
6/6 [==============================] - 0s 9ms/step - loss: 7.7079 - accuracy: 0.8564 - val_loss: 7.6744 - val_accuracy: 0.7923
Epoch 57/100
6/6 [==============================] - 0s 11ms/step - loss: 7.6020 - accuracy: 0.8605 - val_loss: 7.5735 - val_accuracy: 0.7978
Epoch 58/100
6/6 [==============================] - 0s 9ms/step - loss: 7.4986 - accuracy: 0.8605 - val_loss: 7.4718 - val_accuracy: 0.8033
Epoch 59/100
6/6 [==============================] - 0s 9ms/step - loss: 7.3971 - accuracy: 0.8618 - val_loss: 7.3702 - val_accuracy: 0.8087
Epoch 60/100
6/6 [==============================] - 0s 10ms/step - loss: 7.3004 - accuracy: 0.8509 - val_loss: 7.2681 - val_accuracy: 0.8142
Epoch 61/100
6/6 [==============================] - 0s 11ms/step - loss: 7.1918 - accuracy: 0.8605 - val_loss: 7.1661 - val_accuracy: 0.8142
Epoch 62/100
6/6 [==============================] - 0s 9ms/step - loss: 7.0963 - accuracy: 0.8564 - val_loss: 7.0639 - val_accuracy: 0.8087
Epoch 63/100
6/6 [==============================] - 0s 9ms/step - loss: 6.9803 - accuracy: 0.8536 - val_loss: 6.9621 - val_accuracy: 0.8087
Epoch 64/100
6/6 [==============================] - 0s 10ms/step - loss: 6.8824 - accuracy: 0.8550 - val_loss: 6.8603 - val_accuracy: 0.8142
Epoch 65/100
6/6 [==============================] - 0s 9ms/step - loss: 6.7753 - accuracy: 0.8591 - val_loss: 6.7583 - val_accuracy: 0.8142
Epoch 66/100
6/6 [==============================] - 0s 11ms/step - loss: 6.6812 - accuracy: 0.8591 - val_loss: 6.6569 - val_accuracy: 0.8142
Epoch 67/100
6/6 [==============================] - 0s 9ms/step - loss: 6.5747 - accuracy: 0.8618 - val_loss: 6.5568 - val_accuracy: 0.8142
Epoch 68/100
6/6 [==============================] - 0s 9ms/step - loss: 6.4710 - accuracy: 0.8605 - val_loss: 6.4577 - val_accuracy: 0.8142
Epoch 69/100
6/6 [==============================] - 0s 10ms/step - loss: 6.3799 - accuracy: 0.8605 - val_loss: 6.3597 - val_accuracy: 0.8142
Epoch 70/100
6/6 [==============================] - 0s 9ms/step - loss: 6.2684 - accuracy: 0.8605 - val_loss: 6.2621 - val_accuracy: 0.8142
Epoch 71/100
6/6 [==============================] - 0s 8ms/step - loss: 6.1794 - accuracy: 0.8591 - val_loss: 6.1642 - val_accuracy: 0.8142
Epoch 72/100
6/6 [==============================] - 0s 10ms/step - loss: 6.0788 - accuracy: 0.8605 - val_loss: 6.0674 - val_accuracy: 0.8142
Epoch 73/100
6/6 [==============================] - 0s 9ms/step - loss: 5.9842 - accuracy: 0.8591 - val_loss: 5.9722 - val_accuracy: 0.8142
Epoch 74/100
6/6 [==============================] - 0s 11ms/step - loss: 5.8857 - accuracy: 0.8591 - val_loss: 5.8782 - val_accuracy: 0.8142
Epoch 75/100
6/6 [==============================] - 0s 13ms/step - loss: 5.7916 - accuracy: 0.8591 - val_loss: 5.7859 - val_accuracy: 0.8142
Epoch 76/100
6/6 [==============================] - 0s 10ms/step - loss: 5.6990 - accuracy: 0.8591 - val_loss: 5.6951 - val_accuracy: 0.8142
Epoch 77/100
6/6 [==============================] - 0s 10ms/step - loss: 5.6115 - accuracy: 0.8591 - val_loss: 5.6054 - val_accuracy: 0.8142
Epoch 78/100
6/6 [==============================] - 0s 10ms/step - loss: 5.5213 - accuracy: 0.8591 - val_loss: 5.5157 - val_accuracy: 0.8142
Epoch 79/100
6/6 [==============================] - 0s 10ms/step - loss: 5.4263 - accuracy: 0.8591 - val_loss: 5.4268 - val_accuracy: 0.8142
Epoch 80/100
6/6 [==============================] - 0s 8ms/step - loss: 5.3444 - accuracy: 0.8591 - val_loss: 5.3384 - val_accuracy: 0.8142
Epoch 81/100
6/6 [==============================] - 0s 10ms/step - loss: 5.2500 - accuracy: 0.8591 - val_loss: 5.2502 - val_accuracy: 0.8142
Epoch 82/100
6/6 [==============================] - 0s 9ms/step - loss: 5.1656 - accuracy: 0.8591 - val_loss: 5.1632 - val_accuracy: 0.8142
Epoch 83/100
6/6 [==============================] - 0s 11ms/step - loss: 5.0718 - accuracy: 0.8591 - val_loss: 5.0772 - val_accuracy: 0.8142
Epoch 84/100
6/6 [==============================] - 0s 10ms/step - loss: 4.9911 - accuracy: 0.8591 - val_loss: 4.9924 - val_accuracy: 0.8142
Epoch 85/100
6/6 [==============================] - 0s 9ms/step - loss: 4.9071 - accuracy: 0.8591 - val_loss: 4.9078 - val_accuracy: 0.8142
Epoch 86/100
6/6 [==============================] - 0s 8ms/step - loss: 4.8215 - accuracy: 0.8591 - val_loss: 4.8254 - val_accuracy: 0.8142
Epoch 87/100
6/6 [==============================] - 0s 12ms/step - loss: 4.7448 - accuracy: 0.8591 - val_loss: 4.7438 - val_accuracy: 0.8142
Epoch 88/100
6/6 [==============================] - 0s 10ms/step - loss: 4.6587 - accuracy: 0.8591 - val_loss: 4.6627 - val_accuracy: 0.8142
Epoch 89/100
6/6 [==============================] - 0s 9ms/step - loss: 4.5798 - accuracy: 0.8591 - val_loss: 4.5830 - val_accuracy: 0.8142
Epoch 90/100
6/6 [==============================] - 0s 10ms/step - loss: 4.4979 - accuracy: 0.8591 - val_loss: 4.5040 - val_accuracy: 0.8142
Epoch 91/100
6/6 [==============================] - 0s 8ms/step - loss: 4.4158 - accuracy: 0.8591 - val_loss: 4.4259 - val_accuracy: 0.8142
Epoch 92/100
6/6 [==============================] - 0s 10ms/step - loss: 4.3421 - accuracy: 0.8591 - val_loss: 4.3502 - val_accuracy: 0.8142
Epoch 93/100
6/6 [==============================] - 0s 11ms/step - loss: 4.2665 - accuracy: 0.8591 - val_loss: 4.2750 - val_accuracy: 0.8142
Epoch 94/100
6/6 [==============================] - 0s 10ms/step - loss: 4.1890 - accuracy: 0.8591 - val_loss: 4.2016 - val_accuracy: 0.8142
Epoch 95/100
6/6 [==============================] - 0s 11ms/step - loss: 4.1185 - accuracy: 0.8591 - val_loss: 4.1308 - val_accuracy: 0.8142
Epoch 96/100
6/6 [==============================] - 0s 11ms/step - loss: 4.0496 - accuracy: 0.8591 - val_loss: 4.0624 - val_accuracy: 0.8142
Epoch 97/100
6/6 [==============================] - 0s 11ms/step - loss: 3.9806 - accuracy: 0.8591 - val_loss: 3.9958 - val_accuracy: 0.8142
Epoch 98/100
6/6 [==============================] - 0s 10ms/step - loss: 3.9125 - accuracy: 0.8591 - val_loss: 3.9314 - val_accuracy: 0.8142
Epoch 99/100
6/6 [==============================] - 0s 9ms/step - loss: 3.8474 - accuracy: 0.8591 - val_loss: 3.8690 - val_accuracy: 0.8142
Epoch 100/100
6/6 [==============================] - 0s 11ms/step - loss: 3.7850 - accuracy: 0.8591 - val_loss: 3.8099 - val_accuracy: 0.8142
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 128
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
6/6 [==============================] - 1s 46ms/step - loss: 11.8006 - accuracy: 0.3776 - val_loss: 11.7868 - val_accuracy: 0.3880
Epoch 2/100
6/6 [==============================] - 0s 9ms/step - loss: 11.8127 - accuracy: 0.3461 - val_loss: 11.7817 - val_accuracy: 0.3934
Epoch 3/100
6/6 [==============================] - 0s 9ms/step - loss: 11.7845 - accuracy: 0.3789 - val_loss: 11.7734 - val_accuracy: 0.3934
Epoch 4/100
6/6 [==============================] - 0s 10ms/step - loss: 11.7862 - accuracy: 0.3721 - val_loss: 11.7620 - val_accuracy: 0.3934
Epoch 5/100
6/6 [==============================] - 0s 19ms/step - loss: 11.7703 - accuracy: 0.3844 - val_loss: 11.7475 - val_accuracy: 0.3934
Epoch 6/100
6/6 [==============================] - 0s 11ms/step - loss: 11.7460 - accuracy: 0.3817 - val_loss: 11.7299 - val_accuracy: 0.3934
Epoch 7/100
6/6 [==============================] - 0s 10ms/step - loss: 11.7362 - accuracy: 0.3926 - val_loss: 11.7093 - val_accuracy: 0.3989
Epoch 8/100
6/6 [==============================] - 0s 9ms/step - loss: 11.7025 - accuracy: 0.4090 - val_loss: 11.6857 - val_accuracy: 0.4098
Epoch 9/100
6/6 [==============================] - 0s 10ms/step - loss: 11.7020 - accuracy: 0.3899 - val_loss: 11.6590 - val_accuracy: 0.4153
Epoch 10/100
6/6 [==============================] - 0s 10ms/step - loss: 11.6557 - accuracy: 0.3912 - val_loss: 11.6294 - val_accuracy: 0.4208
Epoch 11/100
6/6 [==============================] - 0s 9ms/step - loss: 11.6254 - accuracy: 0.3926 - val_loss: 11.5969 - val_accuracy: 0.4262
Epoch 12/100
6/6 [==============================] - 0s 8ms/step - loss: 11.5869 - accuracy: 0.4213 - val_loss: 11.5615 - val_accuracy: 0.4317
Epoch 13/100
6/6 [==============================] - 0s 10ms/step - loss: 11.5590 - accuracy: 0.4049 - val_loss: 11.5232 - val_accuracy: 0.4426
Epoch 14/100
6/6 [==============================] - 0s 9ms/step - loss: 11.5115 - accuracy: 0.4350 - val_loss: 11.4822 - val_accuracy: 0.4536
Epoch 15/100
6/6 [==============================] - 0s 9ms/step - loss: 11.4804 - accuracy: 0.3995 - val_loss: 11.4385 - val_accuracy: 0.4536
Epoch 16/100
6/6 [==============================] - 0s 9ms/step - loss: 11.4287 - accuracy: 0.4501 - val_loss: 11.3921 - val_accuracy: 0.4590
Epoch 17/100
6/6 [==============================] - 0s 9ms/step - loss: 11.3803 - accuracy: 0.4624 - val_loss: 11.3433 - val_accuracy: 0.4699
Epoch 18/100
6/6 [==============================] - 0s 9ms/step - loss: 11.3389 - accuracy: 0.4473 - val_loss: 11.2920 - val_accuracy: 0.4809
Epoch 19/100
6/6 [==============================] - 0s 10ms/step - loss: 11.2799 - accuracy: 0.4528 - val_loss: 11.2383 - val_accuracy: 0.4809
Epoch 20/100
6/6 [==============================] - 0s 10ms/step - loss: 11.2176 - accuracy: 0.4925 - val_loss: 11.1821 - val_accuracy: 0.4809
Epoch 21/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1657 - accuracy: 0.4761 - val_loss: 11.1237 - val_accuracy: 0.4918
Epoch 22/100
6/6 [==============================] - 0s 9ms/step - loss: 11.0977 - accuracy: 0.4952 - val_loss: 11.0632 - val_accuracy: 0.4973
Epoch 23/100
6/6 [==============================] - 0s 9ms/step - loss: 11.0452 - accuracy: 0.4911 - val_loss: 11.0005 - val_accuracy: 0.5027
Epoch 24/100
6/6 [==============================] - 0s 9ms/step - loss: 10.9834 - accuracy: 0.5171 - val_loss: 10.9358 - val_accuracy: 0.5137
Epoch 25/100
6/6 [==============================] - 0s 10ms/step - loss: 10.9193 - accuracy: 0.5308 - val_loss: 10.8689 - val_accuracy: 0.5301
Epoch 26/100
6/6 [==============================] - 0s 9ms/step - loss: 10.8367 - accuracy: 0.5663 - val_loss: 10.8003 - val_accuracy: 0.5519
Epoch 27/100
6/6 [==============================] - 0s 10ms/step - loss: 10.7844 - accuracy: 0.5431 - val_loss: 10.7296 - val_accuracy: 0.5519
Epoch 28/100
6/6 [==============================] - 0s 9ms/step - loss: 10.6955 - accuracy: 0.5458 - val_loss: 10.6568 - val_accuracy: 0.5792
Epoch 29/100
6/6 [==============================] - 0s 9ms/step - loss: 10.6338 - accuracy: 0.5568 - val_loss: 10.5819 - val_accuracy: 0.5902
Epoch 30/100
6/6 [==============================] - 0s 9ms/step - loss: 10.5459 - accuracy: 0.6005 - val_loss: 10.5051 - val_accuracy: 0.6120
Epoch 31/100
6/6 [==============================] - 0s 10ms/step - loss: 10.4757 - accuracy: 0.5964 - val_loss: 10.4261 - val_accuracy: 0.6339
Epoch 32/100
6/6 [==============================] - 0s 10ms/step - loss: 10.3931 - accuracy: 0.6197 - val_loss: 10.3459 - val_accuracy: 0.6557
Epoch 33/100
6/6 [==============================] - 0s 9ms/step - loss: 10.3014 - accuracy: 0.6471 - val_loss: 10.2641 - val_accuracy: 0.6831
Epoch 34/100
6/6 [==============================] - 0s 9ms/step - loss: 10.2275 - accuracy: 0.6320 - val_loss: 10.1805 - val_accuracy: 0.6885
Epoch 35/100
6/6 [==============================] - 0s 11ms/step - loss: 10.1532 - accuracy: 0.6539 - val_loss: 10.0963 - val_accuracy: 0.7049
Epoch 36/100
6/6 [==============================] - 0s 10ms/step - loss: 10.0502 - accuracy: 0.6854 - val_loss: 10.0109 - val_accuracy: 0.7158
Epoch 37/100
6/6 [==============================] - 0s 10ms/step - loss: 9.9767 - accuracy: 0.6854 - val_loss: 9.9240 - val_accuracy: 0.7377
Epoch 38/100
6/6 [==============================] - 0s 10ms/step - loss: 9.8808 - accuracy: 0.6949 - val_loss: 9.8355 - val_accuracy: 0.7650
Epoch 39/100
6/6 [==============================] - 0s 10ms/step - loss: 9.7903 - accuracy: 0.7086 - val_loss: 9.7455 - val_accuracy: 0.7705
Epoch 40/100
6/6 [==============================] - 0s 10ms/step - loss: 9.6956 - accuracy: 0.7606 - val_loss: 9.6541 - val_accuracy: 0.7869
Epoch 41/100
6/6 [==============================] - 0s 10ms/step - loss: 9.5997 - accuracy: 0.7592 - val_loss: 9.5618 - val_accuracy: 0.7923
Epoch 42/100
6/6 [==============================] - 0s 9ms/step - loss: 9.5069 - accuracy: 0.7579 - val_loss: 9.4687 - val_accuracy: 0.8033
Epoch 43/100
6/6 [==============================] - 0s 10ms/step - loss: 9.4160 - accuracy: 0.7674 - val_loss: 9.3749 - val_accuracy: 0.8033
Epoch 44/100
6/6 [==============================] - 0s 9ms/step - loss: 9.3129 - accuracy: 0.7852 - val_loss: 9.2795 - val_accuracy: 0.8251
Epoch 45/100
6/6 [==============================] - 0s 9ms/step - loss: 9.2228 - accuracy: 0.8030 - val_loss: 9.1827 - val_accuracy: 0.8251
Epoch 46/100
6/6 [==============================] - 0s 10ms/step - loss: 9.1368 - accuracy: 0.8016 - val_loss: 9.0848 - val_accuracy: 0.8306
Epoch 47/100
6/6 [==============================] - 0s 9ms/step - loss: 9.0365 - accuracy: 0.8140 - val_loss: 8.9862 - val_accuracy: 0.8306
Epoch 48/100
6/6 [==============================] - 0s 9ms/step - loss: 8.9305 - accuracy: 0.8167 - val_loss: 8.8868 - val_accuracy: 0.8306
Epoch 49/100
6/6 [==============================] - 0s 9ms/step - loss: 8.8328 - accuracy: 0.8304 - val_loss: 8.7866 - val_accuracy: 0.8361
Epoch 50/100
6/6 [==============================] - 0s 9ms/step - loss: 8.7217 - accuracy: 0.8358 - val_loss: 8.6870 - val_accuracy: 0.8361
Epoch 51/100
6/6 [==============================] - 0s 10ms/step - loss: 8.6251 - accuracy: 0.8413 - val_loss: 8.5872 - val_accuracy: 0.8415
Epoch 52/100
6/6 [==============================] - 0s 9ms/step - loss: 8.5339 - accuracy: 0.8427 - val_loss: 8.4870 - val_accuracy: 0.8415
Epoch 53/100
6/6 [==============================] - 0s 9ms/step - loss: 8.4352 - accuracy: 0.8358 - val_loss: 8.3867 - val_accuracy: 0.8415
Epoch 54/100
6/6 [==============================] - 0s 10ms/step - loss: 8.3267 - accuracy: 0.8482 - val_loss: 8.2875 - val_accuracy: 0.8415
Epoch 55/100
6/6 [==============================] - 0s 9ms/step - loss: 8.2285 - accuracy: 0.8523 - val_loss: 8.1880 - val_accuracy: 0.8415
Epoch 56/100
6/6 [==============================] - 0s 11ms/step - loss: 8.1216 - accuracy: 0.8523 - val_loss: 8.0880 - val_accuracy: 0.8415
Epoch 57/100
6/6 [==============================] - 0s 9ms/step - loss: 8.0238 - accuracy: 0.8482 - val_loss: 7.9879 - val_accuracy: 0.8415
Epoch 58/100
6/6 [==============================] - 0s 9ms/step - loss: 7.9289 - accuracy: 0.8509 - val_loss: 7.8881 - val_accuracy: 0.8415
Epoch 59/100
6/6 [==============================] - 0s 10ms/step - loss: 7.8256 - accuracy: 0.8523 - val_loss: 7.7884 - val_accuracy: 0.8415
Epoch 60/100
6/6 [==============================] - 0s 9ms/step - loss: 7.7259 - accuracy: 0.8509 - val_loss: 7.6876 - val_accuracy: 0.8415
Epoch 61/100
6/6 [==============================] - 0s 9ms/step - loss: 7.6352 - accuracy: 0.8509 - val_loss: 7.5856 - val_accuracy: 0.8415
Epoch 62/100
6/6 [==============================] - 0s 10ms/step - loss: 7.5206 - accuracy: 0.8523 - val_loss: 7.4823 - val_accuracy: 0.8415
Epoch 63/100
6/6 [==============================] - 0s 9ms/step - loss: 7.4213 - accuracy: 0.8523 - val_loss: 7.3782 - val_accuracy: 0.8415
Epoch 64/100
6/6 [==============================] - 0s 10ms/step - loss: 7.3088 - accuracy: 0.8523 - val_loss: 7.2740 - val_accuracy: 0.8415
Epoch 65/100
6/6 [==============================] - 0s 9ms/step - loss: 7.2021 - accuracy: 0.8523 - val_loss: 7.1700 - val_accuracy: 0.8415
Epoch 66/100
6/6 [==============================] - 0s 9ms/step - loss: 7.1031 - accuracy: 0.8523 - val_loss: 7.0649 - val_accuracy: 0.8415
Epoch 67/100
6/6 [==============================] - 0s 9ms/step - loss: 6.9978 - accuracy: 0.8523 - val_loss: 6.9592 - val_accuracy: 0.8415
Epoch 68/100
6/6 [==============================] - 0s 8ms/step - loss: 6.8858 - accuracy: 0.8523 - val_loss: 6.8544 - val_accuracy: 0.8415
Epoch 69/100
6/6 [==============================] - 0s 10ms/step - loss: 6.7807 - accuracy: 0.8523 - val_loss: 6.7498 - val_accuracy: 0.8415
Epoch 70/100
6/6 [==============================] - 0s 10ms/step - loss: 6.6781 - accuracy: 0.8523 - val_loss: 6.6460 - val_accuracy: 0.8415
Epoch 71/100
6/6 [==============================] - 0s 9ms/step - loss: 6.5708 - accuracy: 0.8523 - val_loss: 6.5421 - val_accuracy: 0.8415
Epoch 72/100
6/6 [==============================] - 0s 10ms/step - loss: 6.4747 - accuracy: 0.8536 - val_loss: 6.4376 - val_accuracy: 0.8415
Epoch 73/100
6/6 [==============================] - 0s 9ms/step - loss: 6.3734 - accuracy: 0.8523 - val_loss: 6.3335 - val_accuracy: 0.8415
Epoch 74/100
6/6 [==============================] - 0s 10ms/step - loss: 6.2659 - accuracy: 0.8523 - val_loss: 6.2308 - val_accuracy: 0.8415
Epoch 75/100
6/6 [==============================] - 0s 10ms/step - loss: 6.1640 - accuracy: 0.8523 - val_loss: 6.1285 - val_accuracy: 0.8415
Epoch 76/100
6/6 [==============================] - 0s 9ms/step - loss: 6.0667 - accuracy: 0.8523 - val_loss: 6.0252 - val_accuracy: 0.8415
Epoch 77/100
6/6 [==============================] - 0s 9ms/step - loss: 5.9606 - accuracy: 0.8523 - val_loss: 5.9221 - val_accuracy: 0.8415
Epoch 78/100
6/6 [==============================] - 0s 9ms/step - loss: 5.8532 - accuracy: 0.8523 - val_loss: 5.8190 - val_accuracy: 0.8415
Epoch 79/100
6/6 [==============================] - 0s 9ms/step - loss: 5.7533 - accuracy: 0.8523 - val_loss: 5.7164 - val_accuracy: 0.8415
Epoch 80/100
6/6 [==============================] - 0s 9ms/step - loss: 5.6510 - accuracy: 0.8523 - val_loss: 5.6141 - val_accuracy: 0.8415
Epoch 81/100
6/6 [==============================] - 0s 9ms/step - loss: 5.5495 - accuracy: 0.8523 - val_loss: 5.5125 - val_accuracy: 0.8415
Epoch 82/100
6/6 [==============================] - 0s 9ms/step - loss: 5.4488 - accuracy: 0.8523 - val_loss: 5.4125 - val_accuracy: 0.8415
Epoch 83/100
6/6 [==============================] - 0s 9ms/step - loss: 5.3551 - accuracy: 0.8523 - val_loss: 5.3136 - val_accuracy: 0.8415
Epoch 84/100
6/6 [==============================] - 0s 10ms/step - loss: 5.2587 - accuracy: 0.8523 - val_loss: 5.2162 - val_accuracy: 0.8415
Epoch 85/100
6/6 [==============================] - 0s 8ms/step - loss: 5.1573 - accuracy: 0.8523 - val_loss: 5.1212 - val_accuracy: 0.8415
Epoch 86/100
6/6 [==============================] - 0s 9ms/step - loss: 5.0647 - accuracy: 0.8523 - val_loss: 5.0257 - val_accuracy: 0.8415
Epoch 87/100
6/6 [==============================] - 0s 9ms/step - loss: 4.9658 - accuracy: 0.8523 - val_loss: 4.9312 - val_accuracy: 0.8415
Epoch 88/100
6/6 [==============================] - 0s 9ms/step - loss: 4.8734 - accuracy: 0.8523 - val_loss: 4.8390 - val_accuracy: 0.8415
Epoch 89/100
6/6 [==============================] - 0s 9ms/step - loss: 4.7817 - accuracy: 0.8523 - val_loss: 4.7475 - val_accuracy: 0.8415
Epoch 90/100
6/6 [==============================] - 0s 10ms/step - loss: 4.6960 - accuracy: 0.8523 - val_loss: 4.6571 - val_accuracy: 0.8415
Epoch 91/100
6/6 [==============================] - 0s 10ms/step - loss: 4.6037 - accuracy: 0.8523 - val_loss: 4.5704 - val_accuracy: 0.8415
Epoch 92/100
6/6 [==============================] - 0s 9ms/step - loss: 4.5227 - accuracy: 0.8523 - val_loss: 4.4877 - val_accuracy: 0.8415
Epoch 93/100
6/6 [==============================] - 0s 9ms/step - loss: 4.4361 - accuracy: 0.8523 - val_loss: 4.4054 - val_accuracy: 0.8415
Epoch 94/100
6/6 [==============================] - 0s 9ms/step - loss: 4.3628 - accuracy: 0.8523 - val_loss: 4.3247 - val_accuracy: 0.8415
Epoch 95/100
6/6 [==============================] - 0s 9ms/step - loss: 4.2777 - accuracy: 0.8523 - val_loss: 4.2454 - val_accuracy: 0.8415
Epoch 96/100
6/6 [==============================] - 0s 10ms/step - loss: 4.2055 - accuracy: 0.8523 - val_loss: 4.1677 - val_accuracy: 0.8415
Epoch 97/100
6/6 [==============================] - 0s 9ms/step - loss: 4.1232 - accuracy: 0.8523 - val_loss: 4.0917 - val_accuracy: 0.8415
Epoch 98/100
6/6 [==============================] - 0s 9ms/step - loss: 4.0541 - accuracy: 0.8523 - val_loss: 4.0164 - val_accuracy: 0.8415
Epoch 99/100
6/6 [==============================] - 0s 9ms/step - loss: 3.9796 - accuracy: 0.8523 - val_loss: 3.9424 - val_accuracy: 0.8415
Epoch 100/100
6/6 [==============================] - 0s 9ms/step - loss: 3.9067 - accuracy: 0.8523 - val_loss: 3.8712 - val_accuracy: 0.8415
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 128
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
6/6 [==============================] - 1s 47ms/step - loss: 11.1724 - accuracy: 0.4473 - val_loss: 11.1601 - val_accuracy: 0.5137
Epoch 2/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1738 - accuracy: 0.4337 - val_loss: 11.1553 - val_accuracy: 0.5137
Epoch 3/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1607 - accuracy: 0.4514 - val_loss: 11.1476 - val_accuracy: 0.5137
Epoch 4/100
6/6 [==============================] - 0s 12ms/step - loss: 11.1570 - accuracy: 0.4432 - val_loss: 11.1369 - val_accuracy: 0.5137
Epoch 5/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1426 - accuracy: 0.4583 - val_loss: 11.1233 - val_accuracy: 0.5137
Epoch 6/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1268 - accuracy: 0.4774 - val_loss: 11.1068 - val_accuracy: 0.5137
Epoch 7/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1137 - accuracy: 0.4637 - val_loss: 11.0874 - val_accuracy: 0.5137
Epoch 8/100
6/6 [==============================] - 0s 9ms/step - loss: 11.0809 - accuracy: 0.4692 - val_loss: 11.0653 - val_accuracy: 0.5082
Epoch 9/100
6/6 [==============================] - 0s 9ms/step - loss: 11.0694 - accuracy: 0.4761 - val_loss: 11.0404 - val_accuracy: 0.5082
Epoch 10/100
6/6 [==============================] - 0s 10ms/step - loss: 11.0523 - accuracy: 0.4788 - val_loss: 11.0127 - val_accuracy: 0.5137
Epoch 11/100
6/6 [==============================] - 0s 9ms/step - loss: 11.0049 - accuracy: 0.4815 - val_loss: 10.9824 - val_accuracy: 0.5137
Epoch 12/100
6/6 [==============================] - 0s 10ms/step - loss: 10.9889 - accuracy: 0.4966 - val_loss: 10.9495 - val_accuracy: 0.5246
Epoch 13/100
6/6 [==============================] - 0s 9ms/step - loss: 10.9334 - accuracy: 0.5048 - val_loss: 10.9141 - val_accuracy: 0.5355
Epoch 14/100
6/6 [==============================] - 0s 9ms/step - loss: 10.9112 - accuracy: 0.5089 - val_loss: 10.8761 - val_accuracy: 0.5410
Epoch 15/100
6/6 [==============================] - 0s 10ms/step - loss: 10.8741 - accuracy: 0.5294 - val_loss: 10.8356 - val_accuracy: 0.5410
Epoch 16/100
6/6 [==============================] - 0s 9ms/step - loss: 10.8246 - accuracy: 0.5185 - val_loss: 10.7925 - val_accuracy: 0.5574
Epoch 17/100
6/6 [==============================] - 0s 9ms/step - loss: 10.7839 - accuracy: 0.5280 - val_loss: 10.7469 - val_accuracy: 0.5847
Epoch 18/100
6/6 [==============================] - 0s 9ms/step - loss: 10.7420 - accuracy: 0.5294 - val_loss: 10.6988 - val_accuracy: 0.5902
Epoch 19/100
6/6 [==============================] - 0s 10ms/step - loss: 10.6958 - accuracy: 0.5677 - val_loss: 10.6485 - val_accuracy: 0.6011
Epoch 20/100
6/6 [==============================] - 0s 9ms/step - loss: 10.6331 - accuracy: 0.5732 - val_loss: 10.5959 - val_accuracy: 0.6175
Epoch 21/100
6/6 [==============================] - 0s 10ms/step - loss: 10.5840 - accuracy: 0.5882 - val_loss: 10.5412 - val_accuracy: 0.6393
Epoch 22/100
6/6 [==============================] - 0s 10ms/step - loss: 10.5386 - accuracy: 0.5951 - val_loss: 10.4842 - val_accuracy: 0.6557
Epoch 23/100
6/6 [==============================] - 0s 9ms/step - loss: 10.4671 - accuracy: 0.6101 - val_loss: 10.4254 - val_accuracy: 0.6557
Epoch 24/100
6/6 [==============================] - 0s 10ms/step - loss: 10.4050 - accuracy: 0.6279 - val_loss: 10.3644 - val_accuracy: 0.6831
Epoch 25/100
6/6 [==============================] - 0s 11ms/step - loss: 10.3451 - accuracy: 0.6265 - val_loss: 10.3013 - val_accuracy: 0.7104
Epoch 26/100
6/6 [==============================] - 0s 11ms/step - loss: 10.2823 - accuracy: 0.6265 - val_loss: 10.2361 - val_accuracy: 0.7322
Epoch 27/100
6/6 [==============================] - 0s 10ms/step - loss: 10.2104 - accuracy: 0.6936 - val_loss: 10.1690 - val_accuracy: 0.7432
Epoch 28/100
6/6 [==============================] - 0s 10ms/step - loss: 10.1294 - accuracy: 0.6922 - val_loss: 10.0999 - val_accuracy: 0.7760
Epoch 29/100
6/6 [==============================] - 0s 9ms/step - loss: 10.0645 - accuracy: 0.7127 - val_loss: 10.0292 - val_accuracy: 0.7869
Epoch 30/100
6/6 [==============================] - 0s 10ms/step - loss: 9.9981 - accuracy: 0.7155 - val_loss: 9.9565 - val_accuracy: 0.7978
Epoch 31/100
6/6 [==============================] - 0s 11ms/step - loss: 9.9292 - accuracy: 0.7073 - val_loss: 9.8823 - val_accuracy: 0.8142
Epoch 32/100
6/6 [==============================] - 0s 9ms/step - loss: 9.8527 - accuracy: 0.7373 - val_loss: 9.8064 - val_accuracy: 0.8251
Epoch 33/100
6/6 [==============================] - 0s 10ms/step - loss: 9.7769 - accuracy: 0.7456 - val_loss: 9.7289 - val_accuracy: 0.8415
Epoch 34/100
6/6 [==============================] - 0s 9ms/step - loss: 9.7007 - accuracy: 0.7756 - val_loss: 9.6502 - val_accuracy: 0.8470
Epoch 35/100
6/6 [==============================] - 0s 9ms/step - loss: 9.6123 - accuracy: 0.7770 - val_loss: 9.5703 - val_accuracy: 0.8470
Epoch 36/100
6/6 [==============================] - 0s 10ms/step - loss: 9.5318 - accuracy: 0.8003 - val_loss: 9.4888 - val_accuracy: 0.8470
Epoch 37/100
6/6 [==============================] - 0s 9ms/step - loss: 9.4543 - accuracy: 0.7880 - val_loss: 9.4057 - val_accuracy: 0.8470
Epoch 38/100
6/6 [==============================] - 0s 10ms/step - loss: 9.3745 - accuracy: 0.8016 - val_loss: 9.3209 - val_accuracy: 0.8470
Epoch 39/100
6/6 [==============================] - 0s 9ms/step - loss: 9.2786 - accuracy: 0.8016 - val_loss: 9.2346 - val_accuracy: 0.8470
Epoch 40/100
6/6 [==============================] - 0s 11ms/step - loss: 9.2043 - accuracy: 0.8112 - val_loss: 9.1471 - val_accuracy: 0.8470
Epoch 41/100
6/6 [==============================] - 0s 11ms/step - loss: 9.1051 - accuracy: 0.8235 - val_loss: 9.0580 - val_accuracy: 0.8470
Epoch 42/100
6/6 [==============================] - 0s 9ms/step - loss: 9.0186 - accuracy: 0.8386 - val_loss: 8.9674 - val_accuracy: 0.8470
Epoch 43/100
6/6 [==============================] - 0s 9ms/step - loss: 8.9259 - accuracy: 0.8304 - val_loss: 8.8758 - val_accuracy: 0.8470
Epoch 44/100
6/6 [==============================] - 0s 9ms/step - loss: 8.8325 - accuracy: 0.8413 - val_loss: 8.7839 - val_accuracy: 0.8470
Epoch 45/100
6/6 [==============================] - 0s 9ms/step - loss: 8.7400 - accuracy: 0.8468 - val_loss: 8.6920 - val_accuracy: 0.8470
Epoch 46/100
6/6 [==============================] - 0s 10ms/step - loss: 8.6473 - accuracy: 0.8427 - val_loss: 8.5996 - val_accuracy: 0.8470
Epoch 47/100
6/6 [==============================] - 0s 9ms/step - loss: 8.5586 - accuracy: 0.8468 - val_loss: 8.5061 - val_accuracy: 0.8470
Epoch 48/100
6/6 [==============================] - 0s 9ms/step - loss: 8.4689 - accuracy: 0.8468 - val_loss: 8.4116 - val_accuracy: 0.8470
Epoch 49/100
6/6 [==============================] - 0s 9ms/step - loss: 8.3666 - accuracy: 0.8495 - val_loss: 8.3158 - val_accuracy: 0.8470
Epoch 50/100
6/6 [==============================] - 0s 9ms/step - loss: 8.2716 - accuracy: 0.8523 - val_loss: 8.2188 - val_accuracy: 0.8470
Epoch 51/100
6/6 [==============================] - 0s 10ms/step - loss: 8.1770 - accuracy: 0.8495 - val_loss: 8.1211 - val_accuracy: 0.8470
Epoch 52/100
6/6 [==============================] - 0s 10ms/step - loss: 8.0699 - accuracy: 0.8495 - val_loss: 8.0227 - val_accuracy: 0.8470
Epoch 53/100
6/6 [==============================] - 0s 10ms/step - loss: 7.9704 - accuracy: 0.8509 - val_loss: 7.9249 - val_accuracy: 0.8470
Epoch 54/100
6/6 [==============================] - 0s 10ms/step - loss: 7.8768 - accuracy: 0.8509 - val_loss: 7.8266 - val_accuracy: 0.8470
Epoch 55/100
6/6 [==============================] - 0s 9ms/step - loss: 7.7824 - accuracy: 0.8509 - val_loss: 7.7277 - val_accuracy: 0.8470
Epoch 56/100
6/6 [==============================] - 0s 10ms/step - loss: 7.6819 - accuracy: 0.8509 - val_loss: 7.6309 - val_accuracy: 0.8470
Epoch 57/100
6/6 [==============================] - 0s 10ms/step - loss: 7.5881 - accuracy: 0.8495 - val_loss: 7.5344 - val_accuracy: 0.8470
Epoch 58/100
6/6 [==============================] - 0s 8ms/step - loss: 7.4843 - accuracy: 0.8509 - val_loss: 7.4380 - val_accuracy: 0.8470
Epoch 59/100
6/6 [==============================] - 0s 9ms/step - loss: 7.3815 - accuracy: 0.8509 - val_loss: 7.3422 - val_accuracy: 0.8470
Epoch 60/100
6/6 [==============================] - 0s 9ms/step - loss: 7.2963 - accuracy: 0.8509 - val_loss: 7.2457 - val_accuracy: 0.8470
Epoch 61/100
6/6 [==============================] - 0s 9ms/step - loss: 7.1943 - accuracy: 0.8509 - val_loss: 7.1496 - val_accuracy: 0.8470
Epoch 62/100
6/6 [==============================] - 0s 10ms/step - loss: 7.1045 - accuracy: 0.8509 - val_loss: 7.0541 - val_accuracy: 0.8470
Epoch 63/100
6/6 [==============================] - 0s 10ms/step - loss: 7.0052 - accuracy: 0.8509 - val_loss: 6.9580 - val_accuracy: 0.8470
Epoch 64/100
6/6 [==============================] - 0s 18ms/step - loss: 6.9129 - accuracy: 0.8495 - val_loss: 6.8621 - val_accuracy: 0.8470
Epoch 65/100
6/6 [==============================] - 0s 9ms/step - loss: 6.8016 - accuracy: 0.8509 - val_loss: 6.7659 - val_accuracy: 0.8470
Epoch 66/100
6/6 [==============================] - 0s 9ms/step - loss: 6.7135 - accuracy: 0.8509 - val_loss: 6.6696 - val_accuracy: 0.8470
Epoch 67/100
6/6 [==============================] - 0s 9ms/step - loss: 6.6180 - accuracy: 0.8509 - val_loss: 6.5725 - val_accuracy: 0.8470
Epoch 68/100
6/6 [==============================] - 0s 9ms/step - loss: 6.5254 - accuracy: 0.8509 - val_loss: 6.4748 - val_accuracy: 0.8470
Epoch 69/100
6/6 [==============================] - 0s 10ms/step - loss: 6.4256 - accuracy: 0.8509 - val_loss: 6.3781 - val_accuracy: 0.8470
Epoch 70/100
6/6 [==============================] - 0s 9ms/step - loss: 6.3270 - accuracy: 0.8509 - val_loss: 6.2816 - val_accuracy: 0.8470
Epoch 71/100
6/6 [==============================] - 0s 10ms/step - loss: 6.2336 - accuracy: 0.8509 - val_loss: 6.1843 - val_accuracy: 0.8470
Epoch 72/100
6/6 [==============================] - 0s 10ms/step - loss: 6.1338 - accuracy: 0.8509 - val_loss: 6.0880 - val_accuracy: 0.8470
Epoch 73/100
6/6 [==============================] - 0s 10ms/step - loss: 6.0339 - accuracy: 0.8509 - val_loss: 5.9919 - val_accuracy: 0.8470
Epoch 74/100
6/6 [==============================] - 0s 9ms/step - loss: 5.9369 - accuracy: 0.8509 - val_loss: 5.8951 - val_accuracy: 0.8470
Epoch 75/100
6/6 [==============================] - 0s 10ms/step - loss: 5.8384 - accuracy: 0.8509 - val_loss: 5.7974 - val_accuracy: 0.8470
Epoch 76/100
6/6 [==============================] - 0s 9ms/step - loss: 5.7412 - accuracy: 0.8509 - val_loss: 5.6993 - val_accuracy: 0.8470
Epoch 77/100
6/6 [==============================] - 0s 10ms/step - loss: 5.6535 - accuracy: 0.8509 - val_loss: 5.6012 - val_accuracy: 0.8470
Epoch 78/100
6/6 [==============================] - 0s 10ms/step - loss: 5.5450 - accuracy: 0.8509 - val_loss: 5.5036 - val_accuracy: 0.8470
Epoch 79/100
6/6 [==============================] - 0s 10ms/step - loss: 5.4498 - accuracy: 0.8509 - val_loss: 5.4074 - val_accuracy: 0.8470
Epoch 80/100
6/6 [==============================] - 0s 10ms/step - loss: 5.3560 - accuracy: 0.8509 - val_loss: 5.3120 - val_accuracy: 0.8470
Epoch 81/100
6/6 [==============================] - 0s 9ms/step - loss: 5.2584 - accuracy: 0.8509 - val_loss: 5.2201 - val_accuracy: 0.8470
Epoch 82/100
6/6 [==============================] - 0s 9ms/step - loss: 5.1680 - accuracy: 0.8509 - val_loss: 5.1301 - val_accuracy: 0.8470
Epoch 83/100
6/6 [==============================] - 0s 10ms/step - loss: 5.0805 - accuracy: 0.8509 - val_loss: 5.0422 - val_accuracy: 0.8470
Epoch 84/100
6/6 [==============================] - 0s 9ms/step - loss: 4.9889 - accuracy: 0.8509 - val_loss: 4.9571 - val_accuracy: 0.8470
Epoch 85/100
6/6 [==============================] - 0s 9ms/step - loss: 4.9099 - accuracy: 0.8509 - val_loss: 4.8747 - val_accuracy: 0.8470
Epoch 86/100
6/6 [==============================] - 0s 10ms/step - loss: 4.8307 - accuracy: 0.8509 - val_loss: 4.7925 - val_accuracy: 0.8470
Epoch 87/100
6/6 [==============================] - 0s 9ms/step - loss: 4.7459 - accuracy: 0.8509 - val_loss: 4.7109 - val_accuracy: 0.8470
Epoch 88/100
6/6 [==============================] - 0s 9ms/step - loss: 4.6665 - accuracy: 0.8509 - val_loss: 4.6305 - val_accuracy: 0.8470
Epoch 89/100
6/6 [==============================] - 0s 9ms/step - loss: 4.5841 - accuracy: 0.8509 - val_loss: 4.5515 - val_accuracy: 0.8470
Epoch 90/100
6/6 [==============================] - 0s 9ms/step - loss: 4.5091 - accuracy: 0.8509 - val_loss: 4.4742 - val_accuracy: 0.8470
Epoch 91/100
6/6 [==============================] - 0s 10ms/step - loss: 4.4255 - accuracy: 0.8509 - val_loss: 4.3972 - val_accuracy: 0.8470
Epoch 92/100
6/6 [==============================] - 0s 9ms/step - loss: 4.3501 - accuracy: 0.8509 - val_loss: 4.3206 - val_accuracy: 0.8470
Epoch 93/100
6/6 [==============================] - 0s 9ms/step - loss: 4.2776 - accuracy: 0.8509 - val_loss: 4.2476 - val_accuracy: 0.8470
Epoch 94/100
6/6 [==============================] - 0s 9ms/step - loss: 4.2029 - accuracy: 0.8509 - val_loss: 4.1767 - val_accuracy: 0.8470
Epoch 95/100
6/6 [==============================] - 0s 8ms/step - loss: 4.1409 - accuracy: 0.8509 - val_loss: 4.1081 - val_accuracy: 0.8470
Epoch 96/100
6/6 [==============================] - 0s 10ms/step - loss: 4.0695 - accuracy: 0.8509 - val_loss: 4.0414 - val_accuracy: 0.8470
Epoch 97/100
6/6 [==============================] - 0s 9ms/step - loss: 4.0041 - accuracy: 0.8509 - val_loss: 3.9761 - val_accuracy: 0.8470
Epoch 98/100
6/6 [==============================] - 0s 9ms/step - loss: 3.9397 - accuracy: 0.8509 - val_loss: 3.9129 - val_accuracy: 0.8470
Epoch 99/100
6/6 [==============================] - 0s 9ms/step - loss: 3.8807 - accuracy: 0.8509 - val_loss: 3.8526 - val_accuracy: 0.8470
Epoch 100/100
6/6 [==============================] - 0s 10ms/step - loss: 3.8208 - accuracy: 0.8509 - val_loss: 3.7936 - val_accuracy: 0.8470
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 338us/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 128
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
6/6 [==============================] - 1s 49ms/step - loss: 11.7634 - accuracy: 0.2845 - val_loss: 11.7880 - val_accuracy: 0.2404
Epoch 2/100
6/6 [==============================] - 0s 9ms/step - loss: 11.7696 - accuracy: 0.2681 - val_loss: 11.7826 - val_accuracy: 0.2404
Epoch 3/100
6/6 [==============================] - 0s 9ms/step - loss: 11.7694 - accuracy: 0.2914 - val_loss: 11.7738 - val_accuracy: 0.2404
Epoch 4/100
6/6 [==============================] - 0s 10ms/step - loss: 11.7642 - accuracy: 0.2668 - val_loss: 11.7617 - val_accuracy: 0.2459
Epoch 5/100
6/6 [==============================] - 0s 10ms/step - loss: 11.7318 - accuracy: 0.3051 - val_loss: 11.7462 - val_accuracy: 0.2459
Epoch 6/100
6/6 [==============================] - 0s 9ms/step - loss: 11.7304 - accuracy: 0.2818 - val_loss: 11.7274 - val_accuracy: 0.2459
Epoch 7/100
6/6 [==============================] - 0s 8ms/step - loss: 11.7053 - accuracy: 0.3146 - val_loss: 11.7055 - val_accuracy: 0.2514
Epoch 8/100
6/6 [==============================] - 0s 11ms/step - loss: 11.6628 - accuracy: 0.3338 - val_loss: 11.6804 - val_accuracy: 0.2514
Epoch 9/100
6/6 [==============================] - 0s 9ms/step - loss: 11.6412 - accuracy: 0.3023 - val_loss: 11.6521 - val_accuracy: 0.2678
Epoch 10/100
6/6 [==============================] - 0s 9ms/step - loss: 11.6270 - accuracy: 0.3078 - val_loss: 11.6206 - val_accuracy: 0.2787
Epoch 11/100
6/6 [==============================] - 0s 9ms/step - loss: 11.5819 - accuracy: 0.3283 - val_loss: 11.5861 - val_accuracy: 0.2787
Epoch 12/100
6/6 [==============================] - 0s 11ms/step - loss: 11.5494 - accuracy: 0.3269 - val_loss: 11.5486 - val_accuracy: 0.2896
Epoch 13/100
6/6 [==============================] - 0s 10ms/step - loss: 11.5217 - accuracy: 0.3365 - val_loss: 11.5080 - val_accuracy: 0.3060
Epoch 14/100
6/6 [==============================] - 0s 10ms/step - loss: 11.4715 - accuracy: 0.3311 - val_loss: 11.4644 - val_accuracy: 0.3224
Epoch 15/100
6/6 [==============================] - 0s 10ms/step - loss: 11.4305 - accuracy: 0.3488 - val_loss: 11.4180 - val_accuracy: 0.3443
Epoch 16/100
6/6 [==============================] - 0s 10ms/step - loss: 11.3870 - accuracy: 0.3680 - val_loss: 11.3688 - val_accuracy: 0.3443
Epoch 17/100
6/6 [==============================] - 0s 9ms/step - loss: 11.3270 - accuracy: 0.4063 - val_loss: 11.3170 - val_accuracy: 0.3497
Epoch 18/100
6/6 [==============================] - 0s 9ms/step - loss: 11.2746 - accuracy: 0.3981 - val_loss: 11.2626 - val_accuracy: 0.3716
Epoch 19/100
6/6 [==============================] - 0s 99ms/step - loss: 11.2224 - accuracy: 0.4254 - val_loss: 11.2055 - val_accuracy: 0.3989
Epoch 20/100
6/6 [==============================] - 0s 10ms/step - loss: 11.1667 - accuracy: 0.4159 - val_loss: 11.1458 - val_accuracy: 0.4153
Epoch 21/100
6/6 [==============================] - 0s 9ms/step - loss: 11.1033 - accuracy: 0.4473 - val_loss: 11.0838 - val_accuracy: 0.4426
Epoch 22/100
6/6 [==============================] - 0s 10ms/step - loss: 11.0413 - accuracy: 0.4542 - val_loss: 11.0192 - val_accuracy: 0.4699
Epoch 23/100
6/6 [==============================] - 0s 9ms/step - loss: 10.9904 - accuracy: 0.4487 - val_loss: 10.9524 - val_accuracy: 0.5027
Epoch 24/100
6/6 [==============================] - 0s 9ms/step - loss: 10.9253 - accuracy: 0.4610 - val_loss: 10.8833 - val_accuracy: 0.5410
Epoch 25/100
6/6 [==============================] - 0s 9ms/step - loss: 10.8266 - accuracy: 0.5075 - val_loss: 10.8120 - val_accuracy: 0.5738
Epoch 26/100
6/6 [==============================] - 0s 8ms/step - loss: 10.7671 - accuracy: 0.5417 - val_loss: 10.7385 - val_accuracy: 0.5956
Epoch 27/100
6/6 [==============================] - 0s 9ms/step - loss: 10.7020 - accuracy: 0.5581 - val_loss: 10.6629 - val_accuracy: 0.5956
Epoch 28/100
6/6 [==============================] - 0s 9ms/step - loss: 10.6198 - accuracy: 0.5705 - val_loss: 10.5855 - val_accuracy: 0.6230
Epoch 29/100
6/6 [==============================] - 0s 10ms/step - loss: 10.5488 - accuracy: 0.5636 - val_loss: 10.5061 - val_accuracy: 0.6284
Epoch 30/100
6/6 [==============================] - 0s 7ms/step - loss: 10.4709 - accuracy: 0.6019 - val_loss: 10.4250 - val_accuracy: 0.6776
Epoch 31/100
6/6 [==============================] - 0s 9ms/step - loss: 10.3955 - accuracy: 0.6293 - val_loss: 10.3421 - val_accuracy: 0.6885
Epoch 32/100
6/6 [==============================] - 0s 9ms/step - loss: 10.3038 - accuracy: 0.6347 - val_loss: 10.2578 - val_accuracy: 0.7104
Epoch 33/100
6/6 [==============================] - 0s 10ms/step - loss: 10.2158 - accuracy: 0.6867 - val_loss: 10.1716 - val_accuracy: 0.7322
Epoch 34/100
6/6 [==============================] - 0s 9ms/step - loss: 10.1375 - accuracy: 0.6744 - val_loss: 10.0836 - val_accuracy: 0.7432
Epoch 35/100
6/6 [==============================] - 0s 9ms/step - loss: 10.0410 - accuracy: 0.7031 - val_loss: 9.9942 - val_accuracy: 0.7541
Epoch 36/100
6/6 [==============================] - 0s 10ms/step - loss: 9.9555 - accuracy: 0.7018 - val_loss: 9.9035 - val_accuracy: 0.7650
Epoch 37/100
6/6 [==============================] - 0s 9ms/step - loss: 9.8711 - accuracy: 0.7196 - val_loss: 9.8110 - val_accuracy: 0.7760
Epoch 38/100
6/6 [==============================] - 0s 8ms/step - loss: 9.7782 - accuracy: 0.7332 - val_loss: 9.7168 - val_accuracy: 0.7923
Epoch 39/100
6/6 [==============================] - 0s 9ms/step - loss: 9.6859 - accuracy: 0.7442 - val_loss: 9.6213 - val_accuracy: 0.7923
Epoch 40/100
6/6 [==============================] - 0s 9ms/step - loss: 9.5883 - accuracy: 0.7510 - val_loss: 9.5246 - val_accuracy: 0.8033
Epoch 41/100
6/6 [==============================] - 0s 10ms/step - loss: 9.4847 - accuracy: 0.7729 - val_loss: 9.4265 - val_accuracy: 0.8033
Epoch 42/100
6/6 [==============================] - 0s 9ms/step - loss: 9.3868 - accuracy: 0.7880 - val_loss: 9.3275 - val_accuracy: 0.8087
Epoch 43/100
6/6 [==============================] - 0s 9ms/step - loss: 9.3037 - accuracy: 0.7880 - val_loss: 9.2281 - val_accuracy: 0.8197
Epoch 44/100
6/6 [==============================] - 0s 9ms/step - loss: 9.2036 - accuracy: 0.7756 - val_loss: 9.1281 - val_accuracy: 0.8251
Epoch 45/100
6/6 [==============================] - 0s 9ms/step - loss: 9.1002 - accuracy: 0.7948 - val_loss: 9.0278 - val_accuracy: 0.8361
Epoch 46/100
6/6 [==============================] - 0s 7ms/step - loss: 8.9908 - accuracy: 0.8030 - val_loss: 8.9264 - val_accuracy: 0.8415
Epoch 47/100
6/6 [==============================] - 0s 9ms/step - loss: 8.9015 - accuracy: 0.7975 - val_loss: 8.8243 - val_accuracy: 0.8415
Epoch 48/100
6/6 [==============================] - 0s 9ms/step - loss: 8.8062 - accuracy: 0.8016 - val_loss: 8.7222 - val_accuracy: 0.8415
Epoch 49/100
6/6 [==============================] - 0s 9ms/step - loss: 8.6958 - accuracy: 0.8208 - val_loss: 8.6192 - val_accuracy: 0.8634
Epoch 50/100
6/6 [==============================] - 0s 9ms/step - loss: 8.5911 - accuracy: 0.8276 - val_loss: 8.5155 - val_accuracy: 0.8634
Epoch 51/100
6/6 [==============================] - 0s 9ms/step - loss: 8.4949 - accuracy: 0.8290 - val_loss: 8.4109 - val_accuracy: 0.8634
Epoch 52/100
6/6 [==============================] - 0s 9ms/step - loss: 8.3861 - accuracy: 0.8317 - val_loss: 8.3061 - val_accuracy: 0.8634
Epoch 53/100
6/6 [==============================] - 0s 9ms/step - loss: 8.2753 - accuracy: 0.8317 - val_loss: 8.2003 - val_accuracy: 0.8634
Epoch 54/100
6/6 [==============================] - 0s 9ms/step - loss: 8.1813 - accuracy: 0.8331 - val_loss: 8.0942 - val_accuracy: 0.8743
Epoch 55/100
6/6 [==============================] - 0s 8ms/step - loss: 8.0600 - accuracy: 0.8358 - val_loss: 7.9877 - val_accuracy: 0.8798
Epoch 56/100
6/6 [==============================] - 0s 10ms/step - loss: 7.9639 - accuracy: 0.8413 - val_loss: 7.8802 - val_accuracy: 0.8798
Epoch 57/100
6/6 [==============================] - 0s 10ms/step - loss: 7.8591 - accuracy: 0.8372 - val_loss: 7.7726 - val_accuracy: 0.8798
Epoch 58/100
6/6 [==============================] - 0s 10ms/step - loss: 7.7550 - accuracy: 0.8386 - val_loss: 7.6655 - val_accuracy: 0.8798
Epoch 59/100
6/6 [==============================] - 0s 9ms/step - loss: 7.6419 - accuracy: 0.8386 - val_loss: 7.5589 - val_accuracy: 0.8798
Epoch 60/100
6/6 [==============================] - 0s 9ms/step - loss: 7.5329 - accuracy: 0.8413 - val_loss: 7.4531 - val_accuracy: 0.8798
Epoch 61/100
6/6 [==============================] - 0s 10ms/step - loss: 7.4326 - accuracy: 0.8440 - val_loss: 7.3472 - val_accuracy: 0.8798
Epoch 62/100
6/6 [==============================] - 0s 9ms/step - loss: 7.3328 - accuracy: 0.8454 - val_loss: 7.2412 - val_accuracy: 0.8798
Epoch 63/100
6/6 [==============================] - 0s 9ms/step - loss: 7.2183 - accuracy: 0.8413 - val_loss: 7.1357 - val_accuracy: 0.8798
Epoch 64/100
6/6 [==============================] - 0s 10ms/step - loss: 7.1262 - accuracy: 0.8413 - val_loss: 7.0304 - val_accuracy: 0.8798
Epoch 65/100
6/6 [==============================] - 0s 9ms/step - loss: 7.0220 - accuracy: 0.8413 - val_loss: 6.9246 - val_accuracy: 0.8798
Epoch 66/100
6/6 [==============================] - 0s 9ms/step - loss: 6.9096 - accuracy: 0.8427 - val_loss: 6.8182 - val_accuracy: 0.8798
Epoch 67/100
6/6 [==============================] - 0s 8ms/step - loss: 6.8012 - accuracy: 0.8413 - val_loss: 6.7131 - val_accuracy: 0.8798
Epoch 68/100
6/6 [==============================] - 0s 10ms/step - loss: 6.7026 - accuracy: 0.8413 - val_loss: 6.6071 - val_accuracy: 0.8798
Epoch 69/100
6/6 [==============================] - 0s 9ms/step - loss: 6.5878 - accuracy: 0.8468 - val_loss: 6.4999 - val_accuracy: 0.8852
Epoch 70/100
6/6 [==============================] - 0s 9ms/step - loss: 6.4855 - accuracy: 0.8454 - val_loss: 6.3928 - val_accuracy: 0.8852
Epoch 71/100
6/6 [==============================] - 0s 11ms/step - loss: 6.3808 - accuracy: 0.8440 - val_loss: 6.2855 - val_accuracy: 0.8852
Epoch 72/100
6/6 [==============================] - 0s 8ms/step - loss: 6.2702 - accuracy: 0.8454 - val_loss: 6.1781 - val_accuracy: 0.8852
Epoch 73/100
6/6 [==============================] - 0s 9ms/step - loss: 6.1654 - accuracy: 0.8427 - val_loss: 6.0707 - val_accuracy: 0.8852
Epoch 74/100
6/6 [==============================] - 0s 9ms/step - loss: 6.0597 - accuracy: 0.8413 - val_loss: 5.9642 - val_accuracy: 0.8852
Epoch 75/100
6/6 [==============================] - 0s 9ms/step - loss: 5.9603 - accuracy: 0.8427 - val_loss: 5.8586 - val_accuracy: 0.8852
Epoch 76/100
6/6 [==============================] - 0s 10ms/step - loss: 5.8428 - accuracy: 0.8413 - val_loss: 5.7538 - val_accuracy: 0.8852
Epoch 77/100
6/6 [==============================] - 0s 13ms/step - loss: 5.7432 - accuracy: 0.8413 - val_loss: 5.6516 - val_accuracy: 0.8852
Epoch 78/100
6/6 [==============================] - 0s 9ms/step - loss: 5.6437 - accuracy: 0.8440 - val_loss: 5.5497 - val_accuracy: 0.8852
Epoch 79/100
6/6 [==============================] - 0s 9ms/step - loss: 5.5435 - accuracy: 0.8427 - val_loss: 5.4498 - val_accuracy: 0.8852
Epoch 80/100
6/6 [==============================] - 0s 9ms/step - loss: 5.4453 - accuracy: 0.8427 - val_loss: 5.3515 - val_accuracy: 0.8852
Epoch 81/100
6/6 [==============================] - 0s 10ms/step - loss: 5.3526 - accuracy: 0.8413 - val_loss: 5.2526 - val_accuracy: 0.8852
Epoch 82/100
6/6 [==============================] - 0s 8ms/step - loss: 5.2480 - accuracy: 0.8399 - val_loss: 5.1545 - val_accuracy: 0.8852
Epoch 83/100
6/6 [==============================] - 0s 7ms/step - loss: 5.1501 - accuracy: 0.8413 - val_loss: 5.0587 - val_accuracy: 0.8852
Epoch 84/100
6/6 [==============================] - 0s 8ms/step - loss: 5.0532 - accuracy: 0.8413 - val_loss: 4.9627 - val_accuracy: 0.8852
Epoch 85/100
6/6 [==============================] - 0s 8ms/step - loss: 4.9550 - accuracy: 0.8413 - val_loss: 4.8679 - val_accuracy: 0.8852
Epoch 86/100
6/6 [==============================] - 0s 9ms/step - loss: 4.8701 - accuracy: 0.8427 - val_loss: 4.7752 - val_accuracy: 0.8852
Epoch 87/100
6/6 [==============================] - 0s 9ms/step - loss: 4.7784 - accuracy: 0.8427 - val_loss: 4.6837 - val_accuracy: 0.8852
Epoch 88/100
6/6 [==============================] - 0s 9ms/step - loss: 4.6810 - accuracy: 0.8413 - val_loss: 4.5926 - val_accuracy: 0.8852
Epoch 89/100
6/6 [==============================] - 0s 11ms/step - loss: 4.5957 - accuracy: 0.8413 - val_loss: 4.5042 - val_accuracy: 0.8852
Epoch 90/100
6/6 [==============================] - 0s 10ms/step - loss: 4.5107 - accuracy: 0.8413 - val_loss: 4.4190 - val_accuracy: 0.8852
Epoch 91/100
6/6 [==============================] - 0s 10ms/step - loss: 4.4220 - accuracy: 0.8413 - val_loss: 4.3357 - val_accuracy: 0.8852
Epoch 92/100
6/6 [==============================] - 0s 9ms/step - loss: 4.3410 - accuracy: 0.8413 - val_loss: 4.2558 - val_accuracy: 0.8852
Epoch 93/100
6/6 [==============================] - 0s 9ms/step - loss: 4.2596 - accuracy: 0.8413 - val_loss: 4.1788 - val_accuracy: 0.8852
Epoch 94/100
6/6 [==============================] - 0s 9ms/step - loss: 4.1896 - accuracy: 0.8413 - val_loss: 4.1047 - val_accuracy: 0.8852
Epoch 95/100
6/6 [==============================] - 0s 10ms/step - loss: 4.1156 - accuracy: 0.8413 - val_loss: 4.0363 - val_accuracy: 0.8852
Epoch 96/100
6/6 [==============================] - 0s 10ms/step - loss: 4.0482 - accuracy: 0.8413 - val_loss: 3.9700 - val_accuracy: 0.8852
Epoch 97/100
6/6 [==============================] - 0s 8ms/step - loss: 3.9802 - accuracy: 0.8413 - val_loss: 3.9042 - val_accuracy: 0.8852
Epoch 98/100
6/6 [==============================] - 0s 8ms/step - loss: 3.9211 - accuracy: 0.8413 - val_loss: 3.8388 - val_accuracy: 0.8852
Epoch 99/100
6/6 [==============================] - 0s 10ms/step - loss: 3.8517 - accuracy: 0.8427 - val_loss: 3.7753 - val_accuracy: 0.8852
Epoch 100/100
6/6 [==============================] - 0s 8ms/step - loss: 3.7878 - accuracy: 0.8413 - val_loss: 3.7133 - val_accuracy: 0.8852
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 128
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
6/6 [==============================] - 1s 46ms/step - loss: 10.8853 - accuracy: 0.5191 - val_loss: 10.8704 - val_accuracy: 0.5440
Epoch 2/100
6/6 [==============================] - 0s 10ms/step - loss: 10.8897 - accuracy: 0.5082 - val_loss: 10.8657 - val_accuracy: 0.5440
Epoch 3/100
6/6 [==============================] - 0s 11ms/step - loss: 10.8879 - accuracy: 0.5314 - val_loss: 10.8580 - val_accuracy: 0.5440
Epoch 4/100
6/6 [==============================] - 0s 10ms/step - loss: 10.8818 - accuracy: 0.5027 - val_loss: 10.8474 - val_accuracy: 0.5440
Epoch 5/100
6/6 [==============================] - 0s 9ms/step - loss: 10.8743 - accuracy: 0.5082 - val_loss: 10.8338 - val_accuracy: 0.5440
Epoch 6/100
6/6 [==============================] - 0s 9ms/step - loss: 10.8589 - accuracy: 0.5082 - val_loss: 10.8174 - val_accuracy: 0.5495
Epoch 7/100
6/6 [==============================] - 0s 9ms/step - loss: 10.8210 - accuracy: 0.5232 - val_loss: 10.7983 - val_accuracy: 0.5549
Epoch 8/100
6/6 [==============================] - 0s 10ms/step - loss: 10.8340 - accuracy: 0.5164 - val_loss: 10.7763 - val_accuracy: 0.5604
Epoch 9/100
6/6 [==============================] - 0s 10ms/step - loss: 10.8004 - accuracy: 0.5191 - val_loss: 10.7515 - val_accuracy: 0.5604
Epoch 10/100
6/6 [==============================] - 0s 10ms/step - loss: 10.7722 - accuracy: 0.5246 - val_loss: 10.7239 - val_accuracy: 0.5604
Epoch 11/100
6/6 [==============================] - 0s 9ms/step - loss: 10.7418 - accuracy: 0.5383 - val_loss: 10.6936 - val_accuracy: 0.5604
Epoch 12/100
6/6 [==============================] - 0s 9ms/step - loss: 10.7028 - accuracy: 0.5437 - val_loss: 10.6605 - val_accuracy: 0.5659
Epoch 13/100
6/6 [==============================] - 0s 10ms/step - loss: 10.6689 - accuracy: 0.5464 - val_loss: 10.6250 - val_accuracy: 0.5714
Epoch 14/100
6/6 [==============================] - 0s 9ms/step - loss: 10.6356 - accuracy: 0.5342 - val_loss: 10.5870 - val_accuracy: 0.5769
Epoch 15/100
6/6 [==============================] - 0s 9ms/step - loss: 10.5867 - accuracy: 0.5915 - val_loss: 10.5467 - val_accuracy: 0.5934
Epoch 16/100
6/6 [==============================] - 0s 9ms/step - loss: 10.5508 - accuracy: 0.5560 - val_loss: 10.5040 - val_accuracy: 0.6044
Epoch 17/100
6/6 [==============================] - 0s 10ms/step - loss: 10.5086 - accuracy: 0.5560 - val_loss: 10.4589 - val_accuracy: 0.6209
Epoch 18/100
6/6 [==============================] - 0s 9ms/step - loss: 10.4728 - accuracy: 0.5642 - val_loss: 10.4112 - val_accuracy: 0.6264
Epoch 19/100
6/6 [==============================] - 0s 9ms/step - loss: 10.4165 - accuracy: 0.5806 - val_loss: 10.3610 - val_accuracy: 0.6374
Epoch 20/100
6/6 [==============================] - 0s 9ms/step - loss: 10.3668 - accuracy: 0.5697 - val_loss: 10.3083 - val_accuracy: 0.6429
Epoch 21/100
6/6 [==============================] - 0s 8ms/step - loss: 10.3252 - accuracy: 0.5874 - val_loss: 10.2531 - val_accuracy: 0.6593
Epoch 22/100
6/6 [==============================] - 0s 9ms/step - loss: 10.2544 - accuracy: 0.6011 - val_loss: 10.1957 - val_accuracy: 0.6703
Epoch 23/100
6/6 [==============================] - 0s 9ms/step - loss: 10.1875 - accuracy: 0.6175 - val_loss: 10.1360 - val_accuracy: 0.6648
Epoch 24/100
6/6 [==============================] - 0s 9ms/step - loss: 10.1260 - accuracy: 0.6107 - val_loss: 10.0744 - val_accuracy: 0.6703
Epoch 25/100
6/6 [==============================] - 0s 9ms/step - loss: 10.0800 - accuracy: 0.6462 - val_loss: 10.0113 - val_accuracy: 0.6813
Epoch 26/100
6/6 [==============================] - 0s 9ms/step - loss: 10.0066 - accuracy: 0.6530 - val_loss: 9.9465 - val_accuracy: 0.6813
Epoch 27/100
6/6 [==============================] - 0s 10ms/step - loss: 9.9455 - accuracy: 0.6462 - val_loss: 9.8799 - val_accuracy: 0.6923
Epoch 28/100
6/6 [==============================] - 0s 9ms/step - loss: 9.8708 - accuracy: 0.6612 - val_loss: 9.8114 - val_accuracy: 0.7033
Epoch 29/100
6/6 [==============================] - 0s 10ms/step - loss: 9.8035 - accuracy: 0.6667 - val_loss: 9.7412 - val_accuracy: 0.7143
Epoch 30/100
6/6 [==============================] - 0s 10ms/step - loss: 9.7458 - accuracy: 0.6571 - val_loss: 9.6699 - val_accuracy: 0.7143
Epoch 31/100
6/6 [==============================] - 0s 11ms/step - loss: 9.6681 - accuracy: 0.6776 - val_loss: 9.5971 - val_accuracy: 0.7143
Epoch 32/100
6/6 [==============================] - 0s 11ms/step - loss: 9.5930 - accuracy: 0.6790 - val_loss: 9.5232 - val_accuracy: 0.7418
Epoch 33/100
6/6 [==============================] - 0s 13ms/step - loss: 9.5067 - accuracy: 0.7008 - val_loss: 9.4484 - val_accuracy: 0.7582
Epoch 34/100
6/6 [==============================] - 0s 10ms/step - loss: 9.4445 - accuracy: 0.6967 - val_loss: 9.3724 - val_accuracy: 0.7802
Epoch 35/100
6/6 [==============================] - 0s 7ms/step - loss: 9.3725 - accuracy: 0.7063 - val_loss: 9.2956 - val_accuracy: 0.7967
Epoch 36/100
6/6 [==============================] - 0s 9ms/step - loss: 9.2895 - accuracy: 0.7186 - val_loss: 9.2180 - val_accuracy: 0.8022
Epoch 37/100
6/6 [==============================] - 0s 10ms/step - loss: 9.2175 - accuracy: 0.7172 - val_loss: 9.1390 - val_accuracy: 0.8022
Epoch 38/100
6/6 [==============================] - 0s 9ms/step - loss: 9.1190 - accuracy: 0.7363 - val_loss: 9.0581 - val_accuracy: 0.7967
Epoch 39/100
6/6 [==============================] - 0s 10ms/step - loss: 9.0583 - accuracy: 0.7404 - val_loss: 8.9756 - val_accuracy: 0.8077
Epoch 40/100
6/6 [==============================] - 0s 10ms/step - loss: 8.9696 - accuracy: 0.7486 - val_loss: 8.8917 - val_accuracy: 0.8187
Epoch 41/100
6/6 [==============================] - 0s 10ms/step - loss: 8.8843 - accuracy: 0.7623 - val_loss: 8.8070 - val_accuracy: 0.8242
Epoch 42/100
6/6 [==============================] - 0s 10ms/step - loss: 8.8060 - accuracy: 0.7691 - val_loss: 8.7214 - val_accuracy: 0.8297
Epoch 43/100
6/6 [==============================] - 0s 10ms/step - loss: 8.7133 - accuracy: 0.7746 - val_loss: 8.6345 - val_accuracy: 0.8242
Epoch 44/100
6/6 [==============================] - 0s 10ms/step - loss: 8.6249 - accuracy: 0.7828 - val_loss: 8.5472 - val_accuracy: 0.8297
Epoch 45/100
6/6 [==============================] - 0s 10ms/step - loss: 8.5431 - accuracy: 0.7746 - val_loss: 8.4585 - val_accuracy: 0.8297
Epoch 46/100
6/6 [==============================] - 0s 10ms/step - loss: 8.4489 - accuracy: 0.7937 - val_loss: 8.3688 - val_accuracy: 0.8242
Epoch 47/100
6/6 [==============================] - 0s 9ms/step - loss: 8.3703 - accuracy: 0.7964 - val_loss: 8.2793 - val_accuracy: 0.8352
Epoch 48/100
6/6 [==============================] - 0s 9ms/step - loss: 8.2773 - accuracy: 0.8115 - val_loss: 8.1896 - val_accuracy: 0.8407
Epoch 49/100
6/6 [==============================] - 0s 9ms/step - loss: 8.1755 - accuracy: 0.8142 - val_loss: 8.0988 - val_accuracy: 0.8407
Epoch 50/100
6/6 [==============================] - 0s 10ms/step - loss: 8.0951 - accuracy: 0.8169 - val_loss: 8.0066 - val_accuracy: 0.8462
Epoch 51/100
6/6 [==============================] - 0s 10ms/step - loss: 8.0002 - accuracy: 0.8224 - val_loss: 7.9132 - val_accuracy: 0.8462
Epoch 52/100
6/6 [==============================] - 0s 10ms/step - loss: 7.9029 - accuracy: 0.8333 - val_loss: 7.8198 - val_accuracy: 0.8571
Epoch 53/100
6/6 [==============================] - 0s 10ms/step - loss: 7.8065 - accuracy: 0.8306 - val_loss: 7.7259 - val_accuracy: 0.8571
Epoch 54/100
6/6 [==============================] - 0s 10ms/step - loss: 7.7161 - accuracy: 0.8333 - val_loss: 7.6315 - val_accuracy: 0.8571
Epoch 55/100
6/6 [==============================] - 0s 9ms/step - loss: 7.6192 - accuracy: 0.8265 - val_loss: 7.5370 - val_accuracy: 0.8571
Epoch 56/100
6/6 [==============================] - 0s 10ms/step - loss: 7.5244 - accuracy: 0.8374 - val_loss: 7.4418 - val_accuracy: 0.8571
Epoch 57/100
6/6 [==============================] - 0s 9ms/step - loss: 7.4298 - accuracy: 0.8279 - val_loss: 7.3461 - val_accuracy: 0.8571
Epoch 58/100
6/6 [==============================] - 0s 9ms/step - loss: 7.3276 - accuracy: 0.8443 - val_loss: 7.2497 - val_accuracy: 0.8571
Epoch 59/100
6/6 [==============================] - 0s 10ms/step - loss: 7.2322 - accuracy: 0.8374 - val_loss: 7.1536 - val_accuracy: 0.8571
Epoch 60/100
6/6 [==============================] - 0s 8ms/step - loss: 7.1400 - accuracy: 0.8443 - val_loss: 7.0575 - val_accuracy: 0.8571
Epoch 61/100
6/6 [==============================] - 0s 7ms/step - loss: 7.0378 - accuracy: 0.8456 - val_loss: 6.9608 - val_accuracy: 0.8571
Epoch 62/100
6/6 [==============================] - 0s 9ms/step - loss: 6.9518 - accuracy: 0.8388 - val_loss: 6.8637 - val_accuracy: 0.8571
Epoch 63/100
6/6 [==============================] - 0s 10ms/step - loss: 6.8470 - accuracy: 0.8470 - val_loss: 6.7676 - val_accuracy: 0.8571
Epoch 64/100
6/6 [==============================] - 0s 10ms/step - loss: 6.7554 - accuracy: 0.8443 - val_loss: 6.6717 - val_accuracy: 0.8571
Epoch 65/100
6/6 [==============================] - 0s 10ms/step - loss: 6.6606 - accuracy: 0.8374 - val_loss: 6.5757 - val_accuracy: 0.8571
Epoch 66/100
6/6 [==============================] - 0s 10ms/step - loss: 6.5716 - accuracy: 0.8456 - val_loss: 6.4801 - val_accuracy: 0.8626
Epoch 67/100
6/6 [==============================] - 0s 10ms/step - loss: 6.4623 - accuracy: 0.8456 - val_loss: 6.3855 - val_accuracy: 0.8626
Epoch 68/100
6/6 [==============================] - 0s 10ms/step - loss: 6.3775 - accuracy: 0.8443 - val_loss: 6.2905 - val_accuracy: 0.8626
Epoch 69/100
6/6 [==============================] - 0s 10ms/step - loss: 6.2849 - accuracy: 0.8443 - val_loss: 6.1950 - val_accuracy: 0.8626
Epoch 70/100
6/6 [==============================] - 0s 10ms/step - loss: 6.1810 - accuracy: 0.8456 - val_loss: 6.1000 - val_accuracy: 0.8626
Epoch 71/100
6/6 [==============================] - 0s 10ms/step - loss: 6.0872 - accuracy: 0.8470 - val_loss: 6.0056 - val_accuracy: 0.8626
Epoch 72/100
6/6 [==============================] - 0s 8ms/step - loss: 5.9929 - accuracy: 0.8456 - val_loss: 5.9121 - val_accuracy: 0.8626
Epoch 73/100
6/6 [==============================] - 0s 9ms/step - loss: 5.8930 - accuracy: 0.8470 - val_loss: 5.8187 - val_accuracy: 0.8626
Epoch 74/100
6/6 [==============================] - 0s 11ms/step - loss: 5.8026 - accuracy: 0.8470 - val_loss: 5.7256 - val_accuracy: 0.8626
Epoch 75/100
6/6 [==============================] - 0s 10ms/step - loss: 5.7081 - accuracy: 0.8470 - val_loss: 5.6340 - val_accuracy: 0.8626
Epoch 76/100
6/6 [==============================] - 0s 9ms/step - loss: 5.6207 - accuracy: 0.8470 - val_loss: 5.5442 - val_accuracy: 0.8626
Epoch 77/100
6/6 [==============================] - 0s 9ms/step - loss: 5.5314 - accuracy: 0.8470 - val_loss: 5.4550 - val_accuracy: 0.8626
Epoch 78/100
6/6 [==============================] - 0s 9ms/step - loss: 5.4421 - accuracy: 0.8470 - val_loss: 5.3659 - val_accuracy: 0.8626
Epoch 79/100
6/6 [==============================] - 0s 10ms/step - loss: 5.3599 - accuracy: 0.8470 - val_loss: 5.2760 - val_accuracy: 0.8626
Epoch 80/100
6/6 [==============================] - 0s 9ms/step - loss: 5.2626 - accuracy: 0.8470 - val_loss: 5.1866 - val_accuracy: 0.8626
Epoch 81/100
6/6 [==============================] - 0s 9ms/step - loss: 5.1700 - accuracy: 0.8470 - val_loss: 5.0975 - val_accuracy: 0.8626
Epoch 82/100
6/6 [==============================] - 0s 9ms/step - loss: 5.0831 - accuracy: 0.8470 - val_loss: 5.0113 - val_accuracy: 0.8626
Epoch 83/100
6/6 [==============================] - 0s 8ms/step - loss: 4.9994 - accuracy: 0.8470 - val_loss: 4.9262 - val_accuracy: 0.8626
Epoch 84/100
6/6 [==============================] - 0s 9ms/step - loss: 4.9148 - accuracy: 0.8470 - val_loss: 4.8423 - val_accuracy: 0.8626
Epoch 85/100
6/6 [==============================] - 0s 9ms/step - loss: 4.8360 - accuracy: 0.8470 - val_loss: 4.7607 - val_accuracy: 0.8626
Epoch 86/100
6/6 [==============================] - 0s 10ms/step - loss: 4.7472 - accuracy: 0.8470 - val_loss: 4.6815 - val_accuracy: 0.8626
Epoch 87/100
6/6 [==============================] - 0s 9ms/step - loss: 4.6768 - accuracy: 0.8470 - val_loss: 4.6049 - val_accuracy: 0.8626
Epoch 88/100
6/6 [==============================] - 0s 9ms/step - loss: 4.5988 - accuracy: 0.8470 - val_loss: 4.5295 - val_accuracy: 0.8626
Epoch 89/100
6/6 [==============================] - 0s 7ms/step - loss: 4.5267 - accuracy: 0.8470 - val_loss: 4.4556 - val_accuracy: 0.8626
Epoch 90/100
6/6 [==============================] - 0s 9ms/step - loss: 4.4469 - accuracy: 0.8470 - val_loss: 4.3834 - val_accuracy: 0.8626
Epoch 91/100
6/6 [==============================] - 0s 10ms/step - loss: 4.3832 - accuracy: 0.8470 - val_loss: 4.3133 - val_accuracy: 0.8626
Epoch 92/100
6/6 [==============================] - 0s 8ms/step - loss: 4.3111 - accuracy: 0.8470 - val_loss: 4.2443 - val_accuracy: 0.8626
Epoch 93/100
6/6 [==============================] - 0s 9ms/step - loss: 4.2358 - accuracy: 0.8470 - val_loss: 4.1761 - val_accuracy: 0.8626
Epoch 94/100
6/6 [==============================] - 0s 11ms/step - loss: 4.1740 - accuracy: 0.8470 - val_loss: 4.1093 - val_accuracy: 0.8626
Epoch 95/100
6/6 [==============================] - 0s 10ms/step - loss: 4.1022 - accuracy: 0.8470 - val_loss: 4.0430 - val_accuracy: 0.8626
Epoch 96/100
6/6 [==============================] - 0s 9ms/step - loss: 4.0357 - accuracy: 0.8470 - val_loss: 3.9777 - val_accuracy: 0.8626
Epoch 97/100
6/6 [==============================] - 0s 9ms/step - loss: 3.9790 - accuracy: 0.8470 - val_loss: 3.9150 - val_accuracy: 0.8626
Epoch 98/100
6/6 [==============================] - 0s 10ms/step - loss: 3.9120 - accuracy: 0.8470 - val_loss: 3.8543 - val_accuracy: 0.8626
Epoch 99/100
6/6 [==============================] - 0s 10ms/step - loss: 3.8529 - accuracy: 0.8470 - val_loss: 3.7939 - val_accuracy: 0.8626
Epoch 100/100
6/6 [==============================] - 0s 9ms/step - loss: 3.7948 - accuracy: 0.8470 - val_loss: 3.7349 - val_accuracy: 0.8626
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Experiment number: 7
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 32, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 128
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
6/6 [==============================] - 1s 50ms/step - loss: 7.8927 - accuracy: 0.3707 - val_loss: 7.5955 - val_accuracy: 0.5246
Epoch 2/100
6/6 [==============================] - 0s 10ms/step - loss: 7.6431 - accuracy: 0.3953 - val_loss: 7.3408 - val_accuracy: 0.5574
Epoch 3/100
6/6 [==============================] - 0s 10ms/step - loss: 7.3670 - accuracy: 0.4651 - val_loss: 7.0950 - val_accuracy: 0.6175
Epoch 4/100
6/6 [==============================] - 0s 9ms/step - loss: 7.0935 - accuracy: 0.5185 - val_loss: 6.8599 - val_accuracy: 0.6175
Epoch 5/100
6/6 [==============================] - 0s 9ms/step - loss: 6.8602 - accuracy: 0.5349 - val_loss: 6.6323 - val_accuracy: 0.6612
Epoch 6/100
6/6 [==============================] - 0s 9ms/step - loss: 6.6542 - accuracy: 0.5663 - val_loss: 6.4117 - val_accuracy: 0.6776
Epoch 7/100
6/6 [==============================] - 0s 9ms/step - loss: 6.4045 - accuracy: 0.6252 - val_loss: 6.1973 - val_accuracy: 0.7104
Epoch 8/100
6/6 [==============================] - 0s 9ms/step - loss: 6.1937 - accuracy: 0.6539 - val_loss: 5.9909 - val_accuracy: 0.7213
Epoch 9/100
6/6 [==============================] - 0s 9ms/step - loss: 5.9708 - accuracy: 0.6813 - val_loss: 5.7919 - val_accuracy: 0.7377
Epoch 10/100
6/6 [==============================] - 0s 11ms/step - loss: 5.7738 - accuracy: 0.7127 - val_loss: 5.5982 - val_accuracy: 0.7705
Epoch 11/100
6/6 [==============================] - 0s 9ms/step - loss: 5.5834 - accuracy: 0.7250 - val_loss: 5.4088 - val_accuracy: 0.7869
Epoch 12/100
6/6 [==============================] - 0s 9ms/step - loss: 5.3945 - accuracy: 0.7592 - val_loss: 5.2227 - val_accuracy: 0.7978
Epoch 13/100
6/6 [==============================] - 0s 9ms/step - loss: 5.1875 - accuracy: 0.7852 - val_loss: 5.0419 - val_accuracy: 0.7923
Epoch 14/100
6/6 [==============================] - 0s 9ms/step - loss: 4.9999 - accuracy: 0.7962 - val_loss: 4.8654 - val_accuracy: 0.8033
Epoch 15/100
6/6 [==============================] - 0s 9ms/step - loss: 4.8269 - accuracy: 0.7989 - val_loss: 4.6931 - val_accuracy: 0.8087
Epoch 16/100
6/6 [==============================] - 0s 10ms/step - loss: 4.6581 - accuracy: 0.8016 - val_loss: 4.5246 - val_accuracy: 0.8142
Epoch 17/100
6/6 [==============================] - 0s 9ms/step - loss: 4.4848 - accuracy: 0.8126 - val_loss: 4.3617 - val_accuracy: 0.8142
Epoch 18/100
6/6 [==============================] - 0s 10ms/step - loss: 4.3077 - accuracy: 0.8263 - val_loss: 4.2007 - val_accuracy: 0.8142
Epoch 19/100
6/6 [==============================] - 0s 9ms/step - loss: 4.1539 - accuracy: 0.8276 - val_loss: 4.0437 - val_accuracy: 0.8142
Epoch 20/100
6/6 [==============================] - 0s 9ms/step - loss: 3.9914 - accuracy: 0.8413 - val_loss: 3.8864 - val_accuracy: 0.8142
Epoch 21/100
6/6 [==============================] - 0s 9ms/step - loss: 3.8361 - accuracy: 0.8536 - val_loss: 3.7341 - val_accuracy: 0.8142
Epoch 22/100
6/6 [==============================] - 0s 10ms/step - loss: 3.6883 - accuracy: 0.8495 - val_loss: 3.5864 - val_accuracy: 0.8142
Epoch 23/100
6/6 [==============================] - 0s 9ms/step - loss: 3.5360 - accuracy: 0.8495 - val_loss: 3.4425 - val_accuracy: 0.8142
Epoch 24/100
6/6 [==============================] - 0s 9ms/step - loss: 3.3740 - accuracy: 0.8495 - val_loss: 3.3000 - val_accuracy: 0.8142
Epoch 25/100
6/6 [==============================] - 0s 10ms/step - loss: 3.2403 - accuracy: 0.8577 - val_loss: 3.1623 - val_accuracy: 0.8142
Epoch 26/100
6/6 [==============================] - 0s 9ms/step - loss: 3.1049 - accuracy: 0.8495 - val_loss: 3.0263 - val_accuracy: 0.8142
Epoch 27/100
6/6 [==============================] - 0s 9ms/step - loss: 2.9683 - accuracy: 0.8523 - val_loss: 2.8958 - val_accuracy: 0.8142
Epoch 28/100
6/6 [==============================] - 0s 10ms/step - loss: 2.8325 - accuracy: 0.8577 - val_loss: 2.7694 - val_accuracy: 0.8142
Epoch 29/100
6/6 [==============================] - 0s 7ms/step - loss: 2.7019 - accuracy: 0.8591 - val_loss: 2.6442 - val_accuracy: 0.8142
Epoch 30/100
6/6 [==============================] - 0s 9ms/step - loss: 2.5766 - accuracy: 0.8577 - val_loss: 2.5224 - val_accuracy: 0.8142
Epoch 31/100
6/6 [==============================] - 0s 9ms/step - loss: 2.4538 - accuracy: 0.8577 - val_loss: 2.4036 - val_accuracy: 0.8142
Epoch 32/100
6/6 [==============================] - 0s 9ms/step - loss: 2.3258 - accuracy: 0.8591 - val_loss: 2.2874 - val_accuracy: 0.8142
Epoch 33/100
6/6 [==============================] - 0s 9ms/step - loss: 2.2132 - accuracy: 0.8577 - val_loss: 2.1773 - val_accuracy: 0.8142
Epoch 34/100
6/6 [==============================] - 0s 9ms/step - loss: 2.1089 - accuracy: 0.8591 - val_loss: 2.0708 - val_accuracy: 0.8142
Epoch 35/100
6/6 [==============================] - 0s 9ms/step - loss: 2.0010 - accuracy: 0.8591 - val_loss: 1.9681 - val_accuracy: 0.8142
Epoch 36/100
6/6 [==============================] - 0s 9ms/step - loss: 1.8917 - accuracy: 0.8591 - val_loss: 1.8684 - val_accuracy: 0.8142
Epoch 37/100
6/6 [==============================] - 0s 9ms/step - loss: 1.7961 - accuracy: 0.8591 - val_loss: 1.7717 - val_accuracy: 0.8142
Epoch 38/100
6/6 [==============================] - 0s 9ms/step - loss: 1.7035 - accuracy: 0.8591 - val_loss: 1.6787 - val_accuracy: 0.8142
Epoch 39/100
6/6 [==============================] - 0s 9ms/step - loss: 1.6051 - accuracy: 0.8591 - val_loss: 1.5918 - val_accuracy: 0.8142
Epoch 40/100
6/6 [==============================] - 0s 9ms/step - loss: 1.5192 - accuracy: 0.8591 - val_loss: 1.5085 - val_accuracy: 0.8142
Epoch 41/100
6/6 [==============================] - 0s 10ms/step - loss: 1.4256 - accuracy: 0.8591 - val_loss: 1.4305 - val_accuracy: 0.8142
Epoch 42/100
6/6 [==============================] - 0s 9ms/step - loss: 1.3586 - accuracy: 0.8591 - val_loss: 1.3551 - val_accuracy: 0.8142
Epoch 43/100
6/6 [==============================] - 0s 9ms/step - loss: 1.2727 - accuracy: 0.8591 - val_loss: 1.2843 - val_accuracy: 0.8142
Epoch 44/100
6/6 [==============================] - 0s 9ms/step - loss: 1.1915 - accuracy: 0.8591 - val_loss: 1.2156 - val_accuracy: 0.8142
Epoch 45/100
6/6 [==============================] - 0s 9ms/step - loss: 1.1380 - accuracy: 0.8591 - val_loss: 1.1535 - val_accuracy: 0.8142
Epoch 46/100
6/6 [==============================] - 0s 10ms/step - loss: 1.0618 - accuracy: 0.8591 - val_loss: 1.0932 - val_accuracy: 0.8142
Epoch 47/100
6/6 [==============================] - 0s 9ms/step - loss: 0.9959 - accuracy: 0.8591 - val_loss: 1.0373 - val_accuracy: 0.8142
Epoch 48/100
6/6 [==============================] - 0s 9ms/step - loss: 0.9530 - accuracy: 0.8591 - val_loss: 0.9843 - val_accuracy: 0.8142
Epoch 49/100
6/6 [==============================] - 0s 8ms/step - loss: 0.8939 - accuracy: 0.8591 - val_loss: 0.9326 - val_accuracy: 0.8142
Epoch 50/100
6/6 [==============================] - 0s 9ms/step - loss: 0.8400 - accuracy: 0.8591 - val_loss: 0.8839 - val_accuracy: 0.8142
Epoch 51/100
6/6 [==============================] - 0s 9ms/step - loss: 0.7944 - accuracy: 0.8591 - val_loss: 0.8398 - val_accuracy: 0.8142
Epoch 52/100
6/6 [==============================] - 0s 9ms/step - loss: 0.7545 - accuracy: 0.8591 - val_loss: 0.7980 - val_accuracy: 0.8142
Epoch 53/100
6/6 [==============================] - 0s 9ms/step - loss: 0.7090 - accuracy: 0.8591 - val_loss: 0.7597 - val_accuracy: 0.8142
Epoch 54/100
6/6 [==============================] - 0s 9ms/step - loss: 0.6709 - accuracy: 0.8591 - val_loss: 0.7260 - val_accuracy: 0.8142
Epoch 55/100
6/6 [==============================] - 0s 10ms/step - loss: 0.6405 - accuracy: 0.8591 - val_loss: 0.6939 - val_accuracy: 0.8142
Epoch 56/100
6/6 [==============================] - 0s 10ms/step - loss: 0.6024 - accuracy: 0.8591 - val_loss: 0.6671 - val_accuracy: 0.8142
Epoch 57/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5788 - accuracy: 0.8591 - val_loss: 0.6444 - val_accuracy: 0.8142
Epoch 58/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5543 - accuracy: 0.8591 - val_loss: 0.6229 - val_accuracy: 0.8142
Epoch 59/100
6/6 [==============================] - 0s 10ms/step - loss: 0.5408 - accuracy: 0.8591 - val_loss: 0.6034 - val_accuracy: 0.8142
Epoch 60/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5181 - accuracy: 0.8591 - val_loss: 0.5887 - val_accuracy: 0.8142
Epoch 61/100
6/6 [==============================] - 0s 8ms/step - loss: 0.5058 - accuracy: 0.8591 - val_loss: 0.5744 - val_accuracy: 0.8142
Epoch 62/100
6/6 [==============================] - 0s 20ms/step - loss: 0.4851 - accuracy: 0.8591 - val_loss: 0.5655 - val_accuracy: 0.8142
Epoch 63/100
6/6 [==============================] - 0s 12ms/step - loss: 0.4855 - accuracy: 0.8591 - val_loss: 0.5572 - val_accuracy: 0.8142
Epoch 64/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4739 - accuracy: 0.8591 - val_loss: 0.5491 - val_accuracy: 0.8142
Epoch 65/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4759 - accuracy: 0.8591 - val_loss: 0.5439 - val_accuracy: 0.8142
Epoch 66/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4638 - accuracy: 0.8591 - val_loss: 0.5400 - val_accuracy: 0.8142
Epoch 67/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4622 - accuracy: 0.8591 - val_loss: 0.5377 - val_accuracy: 0.8142
Epoch 68/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4536 - accuracy: 0.8591 - val_loss: 0.5351 - val_accuracy: 0.8142
Epoch 69/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4534 - accuracy: 0.8591 - val_loss: 0.5337 - val_accuracy: 0.8142
Epoch 70/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4501 - accuracy: 0.8591 - val_loss: 0.5326 - val_accuracy: 0.8142
Epoch 71/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4498 - accuracy: 0.8591 - val_loss: 0.5324 - val_accuracy: 0.8142
Epoch 72/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4529 - accuracy: 0.8591 - val_loss: 0.5315 - val_accuracy: 0.8142
Epoch 73/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4492 - accuracy: 0.8591 - val_loss: 0.5307 - val_accuracy: 0.8142
Epoch 74/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4562 - accuracy: 0.8591 - val_loss: 0.5304 - val_accuracy: 0.8142
Epoch 75/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4436 - accuracy: 0.8591 - val_loss: 0.5304 - val_accuracy: 0.8142
Epoch 76/100
6/6 [==============================] - 0s 11ms/step - loss: 0.4400 - accuracy: 0.8591 - val_loss: 0.5302 - val_accuracy: 0.8142
Epoch 77/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4499 - accuracy: 0.8591 - val_loss: 0.5292 - val_accuracy: 0.8142
Epoch 78/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4454 - accuracy: 0.8591 - val_loss: 0.5289 - val_accuracy: 0.8142
Epoch 79/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4571 - accuracy: 0.8591 - val_loss: 0.5286 - val_accuracy: 0.8142
Epoch 80/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4425 - accuracy: 0.8591 - val_loss: 0.5286 - val_accuracy: 0.8142
Epoch 81/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4406 - accuracy: 0.8591 - val_loss: 0.5289 - val_accuracy: 0.8142
Epoch 82/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4442 - accuracy: 0.8591 - val_loss: 0.5289 - val_accuracy: 0.8142
Epoch 83/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4421 - accuracy: 0.8591 - val_loss: 0.5285 - val_accuracy: 0.8142
Epoch 84/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4502 - accuracy: 0.8591 - val_loss: 0.5282 - val_accuracy: 0.8142
Epoch 85/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4482 - accuracy: 0.8591 - val_loss: 0.5282 - val_accuracy: 0.8142
Epoch 86/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4453 - accuracy: 0.8591 - val_loss: 0.5280 - val_accuracy: 0.8142
Epoch 87/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4428 - accuracy: 0.8591 - val_loss: 0.5282 - val_accuracy: 0.8142
Epoch 88/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4455 - accuracy: 0.8591 - val_loss: 0.5277 - val_accuracy: 0.8142
Epoch 89/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4477 - accuracy: 0.8591 - val_loss: 0.5277 - val_accuracy: 0.8142
Epoch 90/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4447 - accuracy: 0.8591 - val_loss: 0.5273 - val_accuracy: 0.8142
Epoch 91/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4453 - accuracy: 0.8591 - val_loss: 0.5272 - val_accuracy: 0.8142
Epoch 92/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4368 - accuracy: 0.8591 - val_loss: 0.5270 - val_accuracy: 0.8142
Epoch 93/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4439 - accuracy: 0.8591 - val_loss: 0.5272 - val_accuracy: 0.8142
Epoch 94/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4433 - accuracy: 0.8591 - val_loss: 0.5272 - val_accuracy: 0.8142
Epoch 95/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4445 - accuracy: 0.8591 - val_loss: 0.5269 - val_accuracy: 0.8142
Epoch 96/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4464 - accuracy: 0.8591 - val_loss: 0.5267 - val_accuracy: 0.8142
Epoch 97/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4488 - accuracy: 0.8591 - val_loss: 0.5268 - val_accuracy: 0.8142
Epoch 98/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4569 - accuracy: 0.8591 - val_loss: 0.5267 - val_accuracy: 0.8142
Epoch 99/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4497 - accuracy: 0.8591 - val_loss: 0.5257 - val_accuracy: 0.8142
Epoch 100/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4431 - accuracy: 0.8591 - val_loss: 0.5258 - val_accuracy: 0.8142
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 32, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 128
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
6/6 [==============================] - 1s 46ms/step - loss: 7.7010 - accuracy: 0.2421 - val_loss: 7.4174 - val_accuracy: 0.2732
Epoch 2/100
6/6 [==============================] - 0s 9ms/step - loss: 7.4220 - accuracy: 0.2449 - val_loss: 7.1408 - val_accuracy: 0.2896
Epoch 3/100
6/6 [==============================] - 0s 9ms/step - loss: 7.1121 - accuracy: 0.2613 - val_loss: 6.8730 - val_accuracy: 0.3388
Epoch 4/100
6/6 [==============================] - 0s 9ms/step - loss: 6.8570 - accuracy: 0.3133 - val_loss: 6.6171 - val_accuracy: 0.3989
Epoch 5/100
6/6 [==============================] - 0s 9ms/step - loss: 6.5862 - accuracy: 0.3338 - val_loss: 6.3703 - val_accuracy: 0.4098
Epoch 6/100
6/6 [==============================] - 0s 9ms/step - loss: 6.3379 - accuracy: 0.3584 - val_loss: 6.1322 - val_accuracy: 0.4208
Epoch 7/100
6/6 [==============================] - 0s 9ms/step - loss: 6.1090 - accuracy: 0.4008 - val_loss: 5.9036 - val_accuracy: 0.4754
Epoch 8/100
6/6 [==============================] - 0s 8ms/step - loss: 5.8724 - accuracy: 0.4309 - val_loss: 5.6820 - val_accuracy: 0.5191
Epoch 9/100
6/6 [==============================] - 0s 9ms/step - loss: 5.6398 - accuracy: 0.4692 - val_loss: 5.4693 - val_accuracy: 0.5410
Epoch 10/100
6/6 [==============================] - 0s 10ms/step - loss: 5.4622 - accuracy: 0.5212 - val_loss: 5.2616 - val_accuracy: 0.5628
Epoch 11/100
6/6 [==============================] - 0s 9ms/step - loss: 5.2500 - accuracy: 0.5253 - val_loss: 5.0609 - val_accuracy: 0.6066
Epoch 12/100
6/6 [==============================] - 0s 10ms/step - loss: 5.0439 - accuracy: 0.5732 - val_loss: 4.8675 - val_accuracy: 0.6503
Epoch 13/100
6/6 [==============================] - 0s 9ms/step - loss: 4.8395 - accuracy: 0.6060 - val_loss: 4.6776 - val_accuracy: 0.7158
Epoch 14/100
6/6 [==============================] - 0s 10ms/step - loss: 4.6311 - accuracy: 0.6607 - val_loss: 4.4972 - val_accuracy: 0.7541
Epoch 15/100
6/6 [==============================] - 0s 10ms/step - loss: 4.4532 - accuracy: 0.6689 - val_loss: 4.3230 - val_accuracy: 0.7760
Epoch 16/100
6/6 [==============================] - 0s 9ms/step - loss: 4.2751 - accuracy: 0.7182 - val_loss: 4.1535 - val_accuracy: 0.7923
Epoch 17/100
6/6 [==============================] - 0s 10ms/step - loss: 4.1249 - accuracy: 0.7209 - val_loss: 3.9872 - val_accuracy: 0.8033
Epoch 18/100
6/6 [==============================] - 0s 9ms/step - loss: 3.9291 - accuracy: 0.7633 - val_loss: 3.8247 - val_accuracy: 0.8033
Epoch 19/100
6/6 [==============================] - 0s 9ms/step - loss: 3.7881 - accuracy: 0.7592 - val_loss: 3.6688 - val_accuracy: 0.8142
Epoch 20/100
6/6 [==============================] - 0s 9ms/step - loss: 3.6193 - accuracy: 0.7839 - val_loss: 3.5195 - val_accuracy: 0.8197
Epoch 21/100
6/6 [==============================] - 0s 10ms/step - loss: 3.4917 - accuracy: 0.7880 - val_loss: 3.3728 - val_accuracy: 0.8306
Epoch 22/100
6/6 [==============================] - 0s 9ms/step - loss: 3.3414 - accuracy: 0.7989 - val_loss: 3.2340 - val_accuracy: 0.8306
Epoch 23/100
6/6 [==============================] - 0s 9ms/step - loss: 3.2072 - accuracy: 0.8098 - val_loss: 3.0994 - val_accuracy: 0.8306
Epoch 24/100
6/6 [==============================] - 0s 10ms/step - loss: 3.0630 - accuracy: 0.8140 - val_loss: 2.9673 - val_accuracy: 0.8361
Epoch 25/100
6/6 [==============================] - 0s 9ms/step - loss: 2.9328 - accuracy: 0.8331 - val_loss: 2.8390 - val_accuracy: 0.8361
Epoch 26/100
6/6 [==============================] - 0s 9ms/step - loss: 2.8082 - accuracy: 0.8276 - val_loss: 2.7157 - val_accuracy: 0.8415
Epoch 27/100
6/6 [==============================] - 0s 9ms/step - loss: 2.6785 - accuracy: 0.8482 - val_loss: 2.5981 - val_accuracy: 0.8415
Epoch 28/100
6/6 [==============================] - 0s 10ms/step - loss: 2.5566 - accuracy: 0.8399 - val_loss: 2.4821 - val_accuracy: 0.8415
Epoch 29/100
6/6 [==============================] - 0s 8ms/step - loss: 2.4424 - accuracy: 0.8440 - val_loss: 2.3706 - val_accuracy: 0.8415
Epoch 30/100
6/6 [==============================] - 0s 11ms/step - loss: 2.3489 - accuracy: 0.8372 - val_loss: 2.2629 - val_accuracy: 0.8415
Epoch 31/100
6/6 [==============================] - 0s 9ms/step - loss: 2.2351 - accuracy: 0.8427 - val_loss: 2.1573 - val_accuracy: 0.8415
Epoch 32/100
6/6 [==============================] - 0s 9ms/step - loss: 2.1293 - accuracy: 0.8454 - val_loss: 2.0530 - val_accuracy: 0.8415
Epoch 33/100
6/6 [==============================] - 0s 9ms/step - loss: 2.0227 - accuracy: 0.8509 - val_loss: 1.9524 - val_accuracy: 0.8415
Epoch 34/100
6/6 [==============================] - 0s 9ms/step - loss: 1.9197 - accuracy: 0.8509 - val_loss: 1.8551 - val_accuracy: 0.8415
Epoch 35/100
6/6 [==============================] - 0s 9ms/step - loss: 1.8222 - accuracy: 0.8509 - val_loss: 1.7606 - val_accuracy: 0.8415
Epoch 36/100
6/6 [==============================] - 0s 10ms/step - loss: 1.7296 - accuracy: 0.8509 - val_loss: 1.6697 - val_accuracy: 0.8415
Epoch 37/100
6/6 [==============================] - 0s 9ms/step - loss: 1.6501 - accuracy: 0.8509 - val_loss: 1.5819 - val_accuracy: 0.8415
Epoch 38/100
6/6 [==============================] - 0s 10ms/step - loss: 1.5540 - accuracy: 0.8495 - val_loss: 1.4972 - val_accuracy: 0.8415
Epoch 39/100
6/6 [==============================] - 0s 9ms/step - loss: 1.4747 - accuracy: 0.8509 - val_loss: 1.4151 - val_accuracy: 0.8415
Epoch 40/100
6/6 [==============================] - 0s 9ms/step - loss: 1.3854 - accuracy: 0.8509 - val_loss: 1.3363 - val_accuracy: 0.8415
Epoch 41/100
6/6 [==============================] - 0s 9ms/step - loss: 1.3234 - accuracy: 0.8523 - val_loss: 1.2599 - val_accuracy: 0.8415
Epoch 42/100
6/6 [==============================] - 0s 9ms/step - loss: 1.2278 - accuracy: 0.8509 - val_loss: 1.1860 - val_accuracy: 0.8415
Epoch 43/100
6/6 [==============================] - 0s 9ms/step - loss: 1.1728 - accuracy: 0.8495 - val_loss: 1.1183 - val_accuracy: 0.8415
Epoch 44/100
6/6 [==============================] - 0s 9ms/step - loss: 1.0922 - accuracy: 0.8523 - val_loss: 1.0554 - val_accuracy: 0.8415
Epoch 45/100
6/6 [==============================] - 0s 9ms/step - loss: 1.0387 - accuracy: 0.8509 - val_loss: 0.9944 - val_accuracy: 0.8415
Epoch 46/100
6/6 [==============================] - 0s 10ms/step - loss: 0.9746 - accuracy: 0.8523 - val_loss: 0.9376 - val_accuracy: 0.8415
Epoch 47/100
6/6 [==============================] - 0s 10ms/step - loss: 0.9196 - accuracy: 0.8523 - val_loss: 0.8831 - val_accuracy: 0.8415
Epoch 48/100
6/6 [==============================] - 0s 10ms/step - loss: 0.8724 - accuracy: 0.8509 - val_loss: 0.8320 - val_accuracy: 0.8415
Epoch 49/100
6/6 [==============================] - 0s 10ms/step - loss: 0.8210 - accuracy: 0.8523 - val_loss: 0.7851 - val_accuracy: 0.8415
Epoch 50/100
6/6 [==============================] - 0s 9ms/step - loss: 0.7787 - accuracy: 0.8523 - val_loss: 0.7432 - val_accuracy: 0.8415
Epoch 51/100
6/6 [==============================] - 0s 10ms/step - loss: 0.7319 - accuracy: 0.8523 - val_loss: 0.7074 - val_accuracy: 0.8415
Epoch 52/100
6/6 [==============================] - 0s 9ms/step - loss: 0.7079 - accuracy: 0.8523 - val_loss: 0.6728 - val_accuracy: 0.8415
Epoch 53/100
6/6 [==============================] - 0s 9ms/step - loss: 0.6669 - accuracy: 0.8523 - val_loss: 0.6418 - val_accuracy: 0.8415
Epoch 54/100
6/6 [==============================] - 0s 8ms/step - loss: 0.6369 - accuracy: 0.8523 - val_loss: 0.6169 - val_accuracy: 0.8415
Epoch 55/100
6/6 [==============================] - 0s 9ms/step - loss: 0.6045 - accuracy: 0.8523 - val_loss: 0.5934 - val_accuracy: 0.8415
Epoch 56/100
6/6 [==============================] - 0s 8ms/step - loss: 0.5888 - accuracy: 0.8523 - val_loss: 0.5737 - val_accuracy: 0.8415
Epoch 57/100
6/6 [==============================] - 0s 10ms/step - loss: 0.5628 - accuracy: 0.8523 - val_loss: 0.5569 - val_accuracy: 0.8415
Epoch 58/100
6/6 [==============================] - 0s 11ms/step - loss: 0.5521 - accuracy: 0.8523 - val_loss: 0.5413 - val_accuracy: 0.8415
Epoch 59/100
6/6 [==============================] - 0s 11ms/step - loss: 0.5344 - accuracy: 0.8523 - val_loss: 0.5298 - val_accuracy: 0.8415
Epoch 60/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5261 - accuracy: 0.8523 - val_loss: 0.5209 - val_accuracy: 0.8415
Epoch 61/100
6/6 [==============================] - 0s 10ms/step - loss: 0.5216 - accuracy: 0.8523 - val_loss: 0.5118 - val_accuracy: 0.8415
Epoch 62/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5055 - accuracy: 0.8523 - val_loss: 0.5064 - val_accuracy: 0.8415
Epoch 63/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5037 - accuracy: 0.8523 - val_loss: 0.5010 - val_accuracy: 0.8415
Epoch 64/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4875 - accuracy: 0.8523 - val_loss: 0.4959 - val_accuracy: 0.8415
Epoch 65/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4929 - accuracy: 0.8523 - val_loss: 0.4915 - val_accuracy: 0.8415
Epoch 66/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4716 - accuracy: 0.8523 - val_loss: 0.4893 - val_accuracy: 0.8415
Epoch 67/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4824 - accuracy: 0.8523 - val_loss: 0.4866 - val_accuracy: 0.8415
Epoch 68/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4807 - accuracy: 0.8523 - val_loss: 0.4850 - val_accuracy: 0.8415
Epoch 69/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4794 - accuracy: 0.8523 - val_loss: 0.4836 - val_accuracy: 0.8415
Epoch 70/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4845 - accuracy: 0.8523 - val_loss: 0.4818 - val_accuracy: 0.8415
Epoch 71/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4855 - accuracy: 0.8523 - val_loss: 0.4804 - val_accuracy: 0.8415
Epoch 72/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4899 - accuracy: 0.8523 - val_loss: 0.4792 - val_accuracy: 0.8415
Epoch 73/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4719 - accuracy: 0.8523 - val_loss: 0.4781 - val_accuracy: 0.8415
Epoch 74/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4785 - accuracy: 0.8523 - val_loss: 0.4773 - val_accuracy: 0.8415
Epoch 75/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4716 - accuracy: 0.8523 - val_loss: 0.4766 - val_accuracy: 0.8415
Epoch 76/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4732 - accuracy: 0.8523 - val_loss: 0.4757 - val_accuracy: 0.8415
Epoch 77/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4712 - accuracy: 0.8523 - val_loss: 0.4747 - val_accuracy: 0.8415
Epoch 78/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4722 - accuracy: 0.8523 - val_loss: 0.4738 - val_accuracy: 0.8415
Epoch 79/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4615 - accuracy: 0.8523 - val_loss: 0.4734 - val_accuracy: 0.8415
Epoch 80/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4731 - accuracy: 0.8523 - val_loss: 0.4729 - val_accuracy: 0.8415
Epoch 81/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4702 - accuracy: 0.8523 - val_loss: 0.4728 - val_accuracy: 0.8415
Epoch 82/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4603 - accuracy: 0.8523 - val_loss: 0.4721 - val_accuracy: 0.8415
Epoch 83/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4694 - accuracy: 0.8523 - val_loss: 0.4715 - val_accuracy: 0.8415
Epoch 84/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4687 - accuracy: 0.8523 - val_loss: 0.4716 - val_accuracy: 0.8415
Epoch 85/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4746 - accuracy: 0.8523 - val_loss: 0.4717 - val_accuracy: 0.8415
Epoch 86/100
6/6 [==============================] - 0s 11ms/step - loss: 0.4743 - accuracy: 0.8523 - val_loss: 0.4710 - val_accuracy: 0.8415
Epoch 87/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4726 - accuracy: 0.8523 - val_loss: 0.4706 - val_accuracy: 0.8415
Epoch 88/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4742 - accuracy: 0.8523 - val_loss: 0.4700 - val_accuracy: 0.8415
Epoch 89/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4708 - accuracy: 0.8523 - val_loss: 0.4699 - val_accuracy: 0.8415
Epoch 90/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4669 - accuracy: 0.8523 - val_loss: 0.4700 - val_accuracy: 0.8415
Epoch 91/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4624 - accuracy: 0.8523 - val_loss: 0.4694 - val_accuracy: 0.8415
Epoch 92/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4743 - accuracy: 0.8523 - val_loss: 0.4695 - val_accuracy: 0.8415
Epoch 93/100
6/6 [==============================] - 0s 11ms/step - loss: 0.4608 - accuracy: 0.8523 - val_loss: 0.4690 - val_accuracy: 0.8415
Epoch 94/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4612 - accuracy: 0.8523 - val_loss: 0.4689 - val_accuracy: 0.8415
Epoch 95/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4743 - accuracy: 0.8523 - val_loss: 0.4690 - val_accuracy: 0.8415
Epoch 96/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4658 - accuracy: 0.8523 - val_loss: 0.4684 - val_accuracy: 0.8415
Epoch 97/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4662 - accuracy: 0.8523 - val_loss: 0.4683 - val_accuracy: 0.8415
Epoch 98/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4673 - accuracy: 0.8523 - val_loss: 0.4679 - val_accuracy: 0.8415
Epoch 99/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4728 - accuracy: 0.8523 - val_loss: 0.4679 - val_accuracy: 0.8415
Epoch 100/100
6/6 [==============================] - 0s 12ms/step - loss: 0.4698 - accuracy: 0.8523 - val_loss: 0.4674 - val_accuracy: 0.8415
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 32, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 128
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
6/6 [==============================] - 1s 47ms/step - loss: 7.3238 - accuracy: 0.5376 - val_loss: 7.0874 - val_accuracy: 0.6120
Epoch 2/100
6/6 [==============================] - 0s 10ms/step - loss: 7.0574 - accuracy: 0.5404 - val_loss: 6.8442 - val_accuracy: 0.6667
Epoch 3/100
6/6 [==============================] - 0s 9ms/step - loss: 6.8034 - accuracy: 0.6074 - val_loss: 6.6071 - val_accuracy: 0.7268
Epoch 4/100
6/6 [==============================] - 0s 9ms/step - loss: 6.5778 - accuracy: 0.6170 - val_loss: 6.3789 - val_accuracy: 0.7705
Epoch 5/100
6/6 [==============================] - 0s 9ms/step - loss: 6.3257 - accuracy: 0.6566 - val_loss: 6.1596 - val_accuracy: 0.7923
Epoch 6/100
6/6 [==============================] - 0s 9ms/step - loss: 6.1220 - accuracy: 0.7004 - val_loss: 5.9478 - val_accuracy: 0.7978
Epoch 7/100
6/6 [==============================] - 0s 9ms/step - loss: 5.9115 - accuracy: 0.7141 - val_loss: 5.7414 - val_accuracy: 0.8087
Epoch 8/100
6/6 [==============================] - 0s 10ms/step - loss: 5.7233 - accuracy: 0.7401 - val_loss: 5.5397 - val_accuracy: 0.8197
Epoch 9/100
6/6 [==============================] - 0s 10ms/step - loss: 5.5169 - accuracy: 0.7565 - val_loss: 5.3426 - val_accuracy: 0.8306
Epoch 10/100
6/6 [==============================] - 0s 9ms/step - loss: 5.3011 - accuracy: 0.7770 - val_loss: 5.1527 - val_accuracy: 0.8306
Epoch 11/100
6/6 [==============================] - 0s 10ms/step - loss: 5.1116 - accuracy: 0.7784 - val_loss: 4.9664 - val_accuracy: 0.8361
Epoch 12/100
6/6 [==============================] - 0s 10ms/step - loss: 4.9227 - accuracy: 0.7934 - val_loss: 4.7832 - val_accuracy: 0.8415
Epoch 13/100
6/6 [==============================] - 0s 9ms/step - loss: 4.7416 - accuracy: 0.8222 - val_loss: 4.6067 - val_accuracy: 0.8415
Epoch 14/100
6/6 [==============================] - 0s 9ms/step - loss: 4.5611 - accuracy: 0.8098 - val_loss: 4.4340 - val_accuracy: 0.8525
Epoch 15/100
6/6 [==============================] - 0s 10ms/step - loss: 4.3898 - accuracy: 0.8235 - val_loss: 4.2657 - val_accuracy: 0.8415
Epoch 16/100
6/6 [==============================] - 0s 10ms/step - loss: 4.1985 - accuracy: 0.8427 - val_loss: 4.0995 - val_accuracy: 0.8415
Epoch 17/100
6/6 [==============================] - 0s 10ms/step - loss: 4.0442 - accuracy: 0.8358 - val_loss: 3.9391 - val_accuracy: 0.8470
Epoch 18/100
6/6 [==============================] - 0s 11ms/step - loss: 3.8939 - accuracy: 0.8304 - val_loss: 3.7795 - val_accuracy: 0.8470
Epoch 19/100
6/6 [==============================] - 0s 10ms/step - loss: 3.7153 - accuracy: 0.8440 - val_loss: 3.6221 - val_accuracy: 0.8470
Epoch 20/100
6/6 [==============================] - 0s 10ms/step - loss: 3.5762 - accuracy: 0.8372 - val_loss: 3.4696 - val_accuracy: 0.8470
Epoch 21/100
6/6 [==============================] - 0s 10ms/step - loss: 3.4279 - accuracy: 0.8495 - val_loss: 3.3222 - val_accuracy: 0.8470
Epoch 22/100
6/6 [==============================] - 0s 10ms/step - loss: 3.2643 - accuracy: 0.8482 - val_loss: 3.1781 - val_accuracy: 0.8470
Epoch 23/100
6/6 [==============================] - 0s 9ms/step - loss: 3.1332 - accuracy: 0.8536 - val_loss: 3.0377 - val_accuracy: 0.8470
Epoch 24/100
6/6 [==============================] - 0s 10ms/step - loss: 2.9853 - accuracy: 0.8495 - val_loss: 2.8996 - val_accuracy: 0.8470
Epoch 25/100
6/6 [==============================] - 0s 12ms/step - loss: 2.8563 - accuracy: 0.8536 - val_loss: 2.7640 - val_accuracy: 0.8470
Epoch 26/100
6/6 [==============================] - 0s 8ms/step - loss: 2.7109 - accuracy: 0.8509 - val_loss: 2.6333 - val_accuracy: 0.8470
Epoch 27/100
6/6 [==============================] - 0s 7ms/step - loss: 2.5908 - accuracy: 0.8523 - val_loss: 2.5033 - val_accuracy: 0.8470
Epoch 28/100
6/6 [==============================] - 0s 9ms/step - loss: 2.4712 - accuracy: 0.8495 - val_loss: 2.3765 - val_accuracy: 0.8470
Epoch 29/100
6/6 [==============================] - 0s 12ms/step - loss: 2.3254 - accuracy: 0.8523 - val_loss: 2.2510 - val_accuracy: 0.8470
Epoch 30/100
6/6 [==============================] - 0s 10ms/step - loss: 2.2086 - accuracy: 0.8509 - val_loss: 2.1313 - val_accuracy: 0.8470
Epoch 31/100
6/6 [==============================] - 0s 10ms/step - loss: 2.0778 - accuracy: 0.8523 - val_loss: 2.0182 - val_accuracy: 0.8470
Epoch 32/100
6/6 [==============================] - 0s 8ms/step - loss: 1.9842 - accuracy: 0.8523 - val_loss: 1.9123 - val_accuracy: 0.8470
Epoch 33/100
6/6 [==============================] - 0s 8ms/step - loss: 1.8875 - accuracy: 0.8509 - val_loss: 1.8090 - val_accuracy: 0.8470
Epoch 34/100
6/6 [==============================] - 0s 7ms/step - loss: 1.7736 - accuracy: 0.8509 - val_loss: 1.7069 - val_accuracy: 0.8470
Epoch 35/100
6/6 [==============================] - 0s 9ms/step - loss: 1.6790 - accuracy: 0.8509 - val_loss: 1.6137 - val_accuracy: 0.8470
Epoch 36/100
6/6 [==============================] - 0s 8ms/step - loss: 1.5812 - accuracy: 0.8509 - val_loss: 1.5261 - val_accuracy: 0.8470
Epoch 37/100
6/6 [==============================] - 0s 12ms/step - loss: 1.4940 - accuracy: 0.8509 - val_loss: 1.4392 - val_accuracy: 0.8470
Epoch 38/100
6/6 [==============================] - 0s 12ms/step - loss: 1.4135 - accuracy: 0.8509 - val_loss: 1.3579 - val_accuracy: 0.8470
Epoch 39/100
6/6 [==============================] - 0s 8ms/step - loss: 1.3462 - accuracy: 0.8509 - val_loss: 1.2820 - val_accuracy: 0.8470
Epoch 40/100
6/6 [==============================] - 0s 7ms/step - loss: 1.2523 - accuracy: 0.8509 - val_loss: 1.2085 - val_accuracy: 0.8470
Epoch 41/100
6/6 [==============================] - 0s 8ms/step - loss: 1.1977 - accuracy: 0.8509 - val_loss: 1.1424 - val_accuracy: 0.8470
Epoch 42/100
6/6 [==============================] - 0s 11ms/step - loss: 1.1282 - accuracy: 0.8509 - val_loss: 1.0762 - val_accuracy: 0.8470
Epoch 43/100
6/6 [==============================] - 0s 11ms/step - loss: 1.0556 - accuracy: 0.8509 - val_loss: 1.0156 - val_accuracy: 0.8470
Epoch 44/100
6/6 [==============================] - 0s 8ms/step - loss: 0.9978 - accuracy: 0.8509 - val_loss: 0.9578 - val_accuracy: 0.8470
Epoch 45/100
6/6 [==============================] - 0s 7ms/step - loss: 0.9448 - accuracy: 0.8509 - val_loss: 0.9063 - val_accuracy: 0.8470
Epoch 46/100
6/6 [==============================] - 0s 9ms/step - loss: 0.8913 - accuracy: 0.8509 - val_loss: 0.8574 - val_accuracy: 0.8470
Epoch 47/100
6/6 [==============================] - 0s 11ms/step - loss: 0.8482 - accuracy: 0.8509 - val_loss: 0.8125 - val_accuracy: 0.8470
Epoch 48/100
6/6 [==============================] - 0s 7ms/step - loss: 0.8017 - accuracy: 0.8509 - val_loss: 0.7700 - val_accuracy: 0.8470
Epoch 49/100
6/6 [==============================] - 0s 10ms/step - loss: 0.7605 - accuracy: 0.8509 - val_loss: 0.7316 - val_accuracy: 0.8470
Epoch 50/100
6/6 [==============================] - 0s 9ms/step - loss: 0.7137 - accuracy: 0.8509 - val_loss: 0.6955 - val_accuracy: 0.8470
Epoch 51/100
6/6 [==============================] - 0s 7ms/step - loss: 0.6864 - accuracy: 0.8509 - val_loss: 0.6634 - val_accuracy: 0.8470
Epoch 52/100
6/6 [==============================] - 0s 9ms/step - loss: 0.6649 - accuracy: 0.8509 - val_loss: 0.6334 - val_accuracy: 0.8470
Epoch 53/100
6/6 [==============================] - 0s 10ms/step - loss: 0.6281 - accuracy: 0.8509 - val_loss: 0.6068 - val_accuracy: 0.8470
Epoch 54/100
6/6 [==============================] - 0s 8ms/step - loss: 0.6021 - accuracy: 0.8509 - val_loss: 0.5827 - val_accuracy: 0.8470
Epoch 55/100
6/6 [==============================] - 0s 8ms/step - loss: 0.5832 - accuracy: 0.8509 - val_loss: 0.5609 - val_accuracy: 0.8470
Epoch 56/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5633 - accuracy: 0.8509 - val_loss: 0.5404 - val_accuracy: 0.8470
Epoch 57/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5375 - accuracy: 0.8509 - val_loss: 0.5246 - val_accuracy: 0.8470
Epoch 58/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5283 - accuracy: 0.8509 - val_loss: 0.5097 - val_accuracy: 0.8470
Epoch 59/100
6/6 [==============================] - 0s 10ms/step - loss: 0.5111 - accuracy: 0.8509 - val_loss: 0.4987 - val_accuracy: 0.8470
Epoch 60/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4971 - accuracy: 0.8509 - val_loss: 0.4882 - val_accuracy: 0.8470
Epoch 61/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4899 - accuracy: 0.8509 - val_loss: 0.4810 - val_accuracy: 0.8470
Epoch 62/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4840 - accuracy: 0.8509 - val_loss: 0.4772 - val_accuracy: 0.8470
Epoch 63/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4841 - accuracy: 0.8509 - val_loss: 0.4717 - val_accuracy: 0.8470
Epoch 64/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4667 - accuracy: 0.8509 - val_loss: 0.4696 - val_accuracy: 0.8470
Epoch 65/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4668 - accuracy: 0.8509 - val_loss: 0.4674 - val_accuracy: 0.8470
Epoch 66/100
6/6 [==============================] - 0s 11ms/step - loss: 0.4666 - accuracy: 0.8509 - val_loss: 0.4650 - val_accuracy: 0.8470
Epoch 67/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4667 - accuracy: 0.8509 - val_loss: 0.4646 - val_accuracy: 0.8470
Epoch 68/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4710 - accuracy: 0.8509 - val_loss: 0.4634 - val_accuracy: 0.8470
Epoch 69/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4689 - accuracy: 0.8509 - val_loss: 0.4628 - val_accuracy: 0.8470
Epoch 70/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4586 - accuracy: 0.8509 - val_loss: 0.4623 - val_accuracy: 0.8470
Epoch 71/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4653 - accuracy: 0.8509 - val_loss: 0.4621 - val_accuracy: 0.8470
Epoch 72/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4706 - accuracy: 0.8509 - val_loss: 0.4614 - val_accuracy: 0.8470
Epoch 73/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4766 - accuracy: 0.8509 - val_loss: 0.4612 - val_accuracy: 0.8470
Epoch 74/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4772 - accuracy: 0.8509 - val_loss: 0.4605 - val_accuracy: 0.8470
Epoch 75/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4607 - accuracy: 0.8509 - val_loss: 0.4602 - val_accuracy: 0.8470
Epoch 76/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4621 - accuracy: 0.8509 - val_loss: 0.4597 - val_accuracy: 0.8470
Epoch 77/100
6/6 [==============================] - 0s 11ms/step - loss: 0.4611 - accuracy: 0.8509 - val_loss: 0.4599 - val_accuracy: 0.8470
Epoch 78/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4653 - accuracy: 0.8509 - val_loss: 0.4595 - val_accuracy: 0.8470
Epoch 79/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4711 - accuracy: 0.8509 - val_loss: 0.4593 - val_accuracy: 0.8470
Epoch 80/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4669 - accuracy: 0.8509 - val_loss: 0.4588 - val_accuracy: 0.8470
Epoch 81/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4678 - accuracy: 0.8509 - val_loss: 0.4588 - val_accuracy: 0.8470
Epoch 82/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4557 - accuracy: 0.8509 - val_loss: 0.4583 - val_accuracy: 0.8470
Epoch 83/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4624 - accuracy: 0.8509 - val_loss: 0.4584 - val_accuracy: 0.8470
Epoch 84/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4647 - accuracy: 0.8509 - val_loss: 0.4578 - val_accuracy: 0.8470
Epoch 85/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4669 - accuracy: 0.8509 - val_loss: 0.4579 - val_accuracy: 0.8470
Epoch 86/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4582 - accuracy: 0.8509 - val_loss: 0.4575 - val_accuracy: 0.8470
Epoch 87/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4585 - accuracy: 0.8509 - val_loss: 0.4574 - val_accuracy: 0.8470
Epoch 88/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4639 - accuracy: 0.8509 - val_loss: 0.4575 - val_accuracy: 0.8470
Epoch 89/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4648 - accuracy: 0.8509 - val_loss: 0.4576 - val_accuracy: 0.8470
Epoch 90/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4651 - accuracy: 0.8509 - val_loss: 0.4574 - val_accuracy: 0.8470
Epoch 91/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4603 - accuracy: 0.8509 - val_loss: 0.4573 - val_accuracy: 0.8470
Epoch 92/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4636 - accuracy: 0.8509 - val_loss: 0.4568 - val_accuracy: 0.8470
Epoch 93/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4609 - accuracy: 0.8509 - val_loss: 0.4570 - val_accuracy: 0.8470
Epoch 94/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4547 - accuracy: 0.8509 - val_loss: 0.4569 - val_accuracy: 0.8470
Epoch 95/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4672 - accuracy: 0.8509 - val_loss: 0.4566 - val_accuracy: 0.8470
Epoch 96/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4669 - accuracy: 0.8509 - val_loss: 0.4568 - val_accuracy: 0.8470
Epoch 97/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4633 - accuracy: 0.8509 - val_loss: 0.4566 - val_accuracy: 0.8470
Epoch 98/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4573 - accuracy: 0.8509 - val_loss: 0.4563 - val_accuracy: 0.8470
Epoch 99/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4682 - accuracy: 0.8509 - val_loss: 0.4561 - val_accuracy: 0.8470
Epoch 100/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4634 - accuracy: 0.8509 - val_loss: 0.4560 - val_accuracy: 0.8470
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 32, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 128
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
6/6 [==============================] - 1s 48ms/step - loss: 8.1522 - accuracy: 0.1997 - val_loss: 7.8747 - val_accuracy: 0.2186
Epoch 2/100
6/6 [==============================] - 0s 10ms/step - loss: 7.8719 - accuracy: 0.2285 - val_loss: 7.5852 - val_accuracy: 0.2678
Epoch 3/100
6/6 [==============================] - 0s 10ms/step - loss: 7.5706 - accuracy: 0.2927 - val_loss: 7.3084 - val_accuracy: 0.3333
Epoch 4/100
6/6 [==============================] - 0s 9ms/step - loss: 7.3066 - accuracy: 0.3529 - val_loss: 7.0408 - val_accuracy: 0.3770
Epoch 5/100
6/6 [==============================] - 0s 10ms/step - loss: 7.0508 - accuracy: 0.3803 - val_loss: 6.7834 - val_accuracy: 0.3934
Epoch 6/100
6/6 [==============================] - 0s 11ms/step - loss: 6.7919 - accuracy: 0.4090 - val_loss: 6.5379 - val_accuracy: 0.4863
Epoch 7/100
6/6 [==============================] - 0s 10ms/step - loss: 6.5561 - accuracy: 0.4583 - val_loss: 6.3048 - val_accuracy: 0.5519
Epoch 8/100
6/6 [==============================] - 0s 7ms/step - loss: 6.3145 - accuracy: 0.5075 - val_loss: 6.0786 - val_accuracy: 0.6066
Epoch 9/100
6/6 [==============================] - 0s 9ms/step - loss: 6.1101 - accuracy: 0.5595 - val_loss: 5.8611 - val_accuracy: 0.6831
Epoch 10/100
6/6 [==============================] - 0s 11ms/step - loss: 5.9129 - accuracy: 0.5732 - val_loss: 5.6534 - val_accuracy: 0.7650
Epoch 11/100
6/6 [==============================] - 0s 8ms/step - loss: 5.6910 - accuracy: 0.6293 - val_loss: 5.4537 - val_accuracy: 0.7978
Epoch 12/100
6/6 [==============================] - 0s 9ms/step - loss: 5.4911 - accuracy: 0.6594 - val_loss: 5.2583 - val_accuracy: 0.8306
Epoch 13/100
6/6 [==============================] - 0s 10ms/step - loss: 5.3145 - accuracy: 0.6703 - val_loss: 5.0690 - val_accuracy: 0.8415
Epoch 14/100
6/6 [==============================] - 0s 7ms/step - loss: 5.0988 - accuracy: 0.7209 - val_loss: 4.8851 - val_accuracy: 0.8689
Epoch 15/100
6/6 [==============================] - 0s 10ms/step - loss: 4.9237 - accuracy: 0.7360 - val_loss: 4.7065 - val_accuracy: 0.8689
Epoch 16/100
6/6 [==============================] - 0s 10ms/step - loss: 4.7404 - accuracy: 0.7661 - val_loss: 4.5311 - val_accuracy: 0.8852
Epoch 17/100
6/6 [==============================] - 0s 10ms/step - loss: 4.5637 - accuracy: 0.7839 - val_loss: 4.3578 - val_accuracy: 0.8852
Epoch 18/100
6/6 [==============================] - 0s 11ms/step - loss: 4.3764 - accuracy: 0.7825 - val_loss: 4.1901 - val_accuracy: 0.8852
Epoch 19/100
6/6 [==============================] - 0s 10ms/step - loss: 4.2034 - accuracy: 0.8140 - val_loss: 4.0260 - val_accuracy: 0.8852
Epoch 20/100
6/6 [==============================] - 0s 10ms/step - loss: 4.0544 - accuracy: 0.7948 - val_loss: 3.8659 - val_accuracy: 0.8852
Epoch 21/100
6/6 [==============================] - 0s 7ms/step - loss: 3.9002 - accuracy: 0.8085 - val_loss: 3.7084 - val_accuracy: 0.8852
Epoch 22/100
6/6 [==============================] - 0s 7ms/step - loss: 3.7354 - accuracy: 0.8249 - val_loss: 3.5535 - val_accuracy: 0.8852
Epoch 23/100
6/6 [==============================] - 0s 10ms/step - loss: 3.5743 - accuracy: 0.8345 - val_loss: 3.4036 - val_accuracy: 0.8852
Epoch 24/100
6/6 [==============================] - 0s 10ms/step - loss: 3.4330 - accuracy: 0.8181 - val_loss: 3.2579 - val_accuracy: 0.8852
Epoch 25/100
6/6 [==============================] - 0s 10ms/step - loss: 3.2821 - accuracy: 0.8331 - val_loss: 3.1145 - val_accuracy: 0.8852
Epoch 26/100
6/6 [==============================] - 0s 10ms/step - loss: 3.1455 - accuracy: 0.8372 - val_loss: 2.9771 - val_accuracy: 0.8852
Epoch 27/100
6/6 [==============================] - 0s 9ms/step - loss: 2.9953 - accuracy: 0.8386 - val_loss: 2.8401 - val_accuracy: 0.8852
Epoch 28/100
6/6 [==============================] - 0s 9ms/step - loss: 2.8642 - accuracy: 0.8372 - val_loss: 2.7077 - val_accuracy: 0.8852
Epoch 29/100
6/6 [==============================] - 0s 9ms/step - loss: 2.7360 - accuracy: 0.8413 - val_loss: 2.5812 - val_accuracy: 0.8852
Epoch 30/100
6/6 [==============================] - 0s 13ms/step - loss: 2.5951 - accuracy: 0.8413 - val_loss: 2.4585 - val_accuracy: 0.8852
Epoch 31/100
6/6 [==============================] - 0s 10ms/step - loss: 2.4906 - accuracy: 0.8399 - val_loss: 2.3400 - val_accuracy: 0.8852
Epoch 32/100
6/6 [==============================] - 0s 9ms/step - loss: 2.3573 - accuracy: 0.8413 - val_loss: 2.2252 - val_accuracy: 0.8852
Epoch 33/100
6/6 [==============================] - 0s 10ms/step - loss: 2.2445 - accuracy: 0.8413 - val_loss: 2.1155 - val_accuracy: 0.8852
Epoch 34/100
6/6 [==============================] - 0s 8ms/step - loss: 2.1462 - accuracy: 0.8399 - val_loss: 2.0067 - val_accuracy: 0.8852
Epoch 35/100
6/6 [==============================] - 0s 7ms/step - loss: 2.0345 - accuracy: 0.8399 - val_loss: 1.9018 - val_accuracy: 0.8852
Epoch 36/100
6/6 [==============================] - 0s 10ms/step - loss: 1.9319 - accuracy: 0.8413 - val_loss: 1.7990 - val_accuracy: 0.8852
Epoch 37/100
6/6 [==============================] - 0s 11ms/step - loss: 1.8333 - accuracy: 0.8399 - val_loss: 1.7016 - val_accuracy: 0.8852
Epoch 38/100
6/6 [==============================] - 0s 7ms/step - loss: 1.7364 - accuracy: 0.8413 - val_loss: 1.6054 - val_accuracy: 0.8852
Epoch 39/100
6/6 [==============================] - 0s 6ms/step - loss: 1.6374 - accuracy: 0.8413 - val_loss: 1.5112 - val_accuracy: 0.8852
Epoch 40/100
6/6 [==============================] - 0s 7ms/step - loss: 1.5492 - accuracy: 0.8413 - val_loss: 1.4213 - val_accuracy: 0.8852
Epoch 41/100
6/6 [==============================] - 0s 10ms/step - loss: 1.4599 - accuracy: 0.8413 - val_loss: 1.3394 - val_accuracy: 0.8852
Epoch 42/100
6/6 [==============================] - 0s 9ms/step - loss: 1.3773 - accuracy: 0.8413 - val_loss: 1.2632 - val_accuracy: 0.8852
Epoch 43/100
6/6 [==============================] - 0s 9ms/step - loss: 1.2935 - accuracy: 0.8413 - val_loss: 1.1885 - val_accuracy: 0.8852
Epoch 44/100
6/6 [==============================] - 0s 8ms/step - loss: 1.2332 - accuracy: 0.8413 - val_loss: 1.1192 - val_accuracy: 0.8852
Epoch 45/100
6/6 [==============================] - 0s 9ms/step - loss: 1.1643 - accuracy: 0.8413 - val_loss: 1.0525 - val_accuracy: 0.8852
Epoch 46/100
6/6 [==============================] - 0s 9ms/step - loss: 1.1018 - accuracy: 0.8413 - val_loss: 0.9889 - val_accuracy: 0.8852
Epoch 47/100
6/6 [==============================] - 0s 9ms/step - loss: 1.0341 - accuracy: 0.8413 - val_loss: 0.9298 - val_accuracy: 0.8852
Epoch 48/100
6/6 [==============================] - 0s 8ms/step - loss: 0.9647 - accuracy: 0.8413 - val_loss: 0.8756 - val_accuracy: 0.8852
Epoch 49/100
6/6 [==============================] - 0s 8ms/step - loss: 0.9302 - accuracy: 0.8413 - val_loss: 0.8236 - val_accuracy: 0.8852
Epoch 50/100
6/6 [==============================] - 0s 10ms/step - loss: 0.8800 - accuracy: 0.8413 - val_loss: 0.7736 - val_accuracy: 0.8852
Epoch 51/100
6/6 [==============================] - 0s 11ms/step - loss: 0.8291 - accuracy: 0.8413 - val_loss: 0.7282 - val_accuracy: 0.8852
Epoch 52/100
6/6 [==============================] - 0s 9ms/step - loss: 0.7839 - accuracy: 0.8413 - val_loss: 0.6836 - val_accuracy: 0.8852
Epoch 53/100
6/6 [==============================] - 0s 10ms/step - loss: 0.7457 - accuracy: 0.8413 - val_loss: 0.6448 - val_accuracy: 0.8852
Epoch 54/100
6/6 [==============================] - 0s 10ms/step - loss: 0.7142 - accuracy: 0.8413 - val_loss: 0.6101 - val_accuracy: 0.8852
Epoch 55/100
6/6 [==============================] - 0s 9ms/step - loss: 0.6798 - accuracy: 0.8413 - val_loss: 0.5772 - val_accuracy: 0.8852
Epoch 56/100
6/6 [==============================] - 0s 9ms/step - loss: 0.6462 - accuracy: 0.8413 - val_loss: 0.5454 - val_accuracy: 0.8852
Epoch 57/100
6/6 [==============================] - 0s 10ms/step - loss: 0.6217 - accuracy: 0.8413 - val_loss: 0.5193 - val_accuracy: 0.8852
Epoch 58/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5970 - accuracy: 0.8413 - val_loss: 0.4990 - val_accuracy: 0.8852
Epoch 59/100
6/6 [==============================] - 0s 10ms/step - loss: 0.5815 - accuracy: 0.8413 - val_loss: 0.4772 - val_accuracy: 0.8852
Epoch 60/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5565 - accuracy: 0.8413 - val_loss: 0.4607 - val_accuracy: 0.8852
Epoch 61/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5332 - accuracy: 0.8413 - val_loss: 0.4461 - val_accuracy: 0.8852
Epoch 62/100
6/6 [==============================] - 0s 8ms/step - loss: 0.5315 - accuracy: 0.8413 - val_loss: 0.4334 - val_accuracy: 0.8852
Epoch 63/100
6/6 [==============================] - 0s 10ms/step - loss: 0.5254 - accuracy: 0.8413 - val_loss: 0.4268 - val_accuracy: 0.8852
Epoch 64/100
6/6 [==============================] - 0s 8ms/step - loss: 0.5103 - accuracy: 0.8413 - val_loss: 0.4200 - val_accuracy: 0.8852
Epoch 65/100
6/6 [==============================] - 0s 11ms/step - loss: 0.5106 - accuracy: 0.8413 - val_loss: 0.4147 - val_accuracy: 0.8852
Epoch 66/100
6/6 [==============================] - 0s 8ms/step - loss: 0.5171 - accuracy: 0.8413 - val_loss: 0.4122 - val_accuracy: 0.8852
Epoch 67/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4964 - accuracy: 0.8413 - val_loss: 0.4102 - val_accuracy: 0.8852
Epoch 68/100
6/6 [==============================] - 0s 7ms/step - loss: 0.5025 - accuracy: 0.8413 - val_loss: 0.4089 - val_accuracy: 0.8852
Epoch 69/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4901 - accuracy: 0.8413 - val_loss: 0.4073 - val_accuracy: 0.8852
Epoch 70/100
6/6 [==============================] - 0s 10ms/step - loss: 0.5016 - accuracy: 0.8413 - val_loss: 0.4057 - val_accuracy: 0.8852
Epoch 71/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4925 - accuracy: 0.8413 - val_loss: 0.4047 - val_accuracy: 0.8852
Epoch 72/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4960 - accuracy: 0.8413 - val_loss: 0.4039 - val_accuracy: 0.8852
Epoch 73/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4846 - accuracy: 0.8413 - val_loss: 0.4035 - val_accuracy: 0.8852
Epoch 74/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4937 - accuracy: 0.8413 - val_loss: 0.4027 - val_accuracy: 0.8852
Epoch 75/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4944 - accuracy: 0.8413 - val_loss: 0.4024 - val_accuracy: 0.8852
Epoch 76/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4849 - accuracy: 0.8413 - val_loss: 0.4015 - val_accuracy: 0.8852
Epoch 77/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4887 - accuracy: 0.8413 - val_loss: 0.4010 - val_accuracy: 0.8852
Epoch 78/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4852 - accuracy: 0.8413 - val_loss: 0.4003 - val_accuracy: 0.8852
Epoch 79/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4872 - accuracy: 0.8413 - val_loss: 0.4000 - val_accuracy: 0.8852
Epoch 80/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4933 - accuracy: 0.8413 - val_loss: 0.3992 - val_accuracy: 0.8852
Epoch 81/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4824 - accuracy: 0.8413 - val_loss: 0.3997 - val_accuracy: 0.8852
Epoch 82/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4886 - accuracy: 0.8413 - val_loss: 0.3992 - val_accuracy: 0.8852
Epoch 83/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4826 - accuracy: 0.8413 - val_loss: 0.3991 - val_accuracy: 0.8852
Epoch 84/100
6/6 [==============================] - 0s 11ms/step - loss: 0.4918 - accuracy: 0.8413 - val_loss: 0.3988 - val_accuracy: 0.8852
Epoch 85/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4823 - accuracy: 0.8413 - val_loss: 0.3986 - val_accuracy: 0.8852
Epoch 86/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4839 - accuracy: 0.8413 - val_loss: 0.3986 - val_accuracy: 0.8852
Epoch 87/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4842 - accuracy: 0.8413 - val_loss: 0.3981 - val_accuracy: 0.8852
Epoch 88/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4823 - accuracy: 0.8413 - val_loss: 0.3978 - val_accuracy: 0.8852
Epoch 89/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4972 - accuracy: 0.8413 - val_loss: 0.3980 - val_accuracy: 0.8852
Epoch 90/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4828 - accuracy: 0.8413 - val_loss: 0.3969 - val_accuracy: 0.8852
Epoch 91/100
6/6 [==============================] - 0s 11ms/step - loss: 0.4844 - accuracy: 0.8413 - val_loss: 0.3968 - val_accuracy: 0.8852
Epoch 92/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4797 - accuracy: 0.8413 - val_loss: 0.3962 - val_accuracy: 0.8852
Epoch 93/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4862 - accuracy: 0.8413 - val_loss: 0.3966 - val_accuracy: 0.8852
Epoch 94/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4878 - accuracy: 0.8413 - val_loss: 0.3962 - val_accuracy: 0.8852
Epoch 95/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4772 - accuracy: 0.8413 - val_loss: 0.3959 - val_accuracy: 0.8852
Epoch 96/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4872 - accuracy: 0.8413 - val_loss: 0.3960 - val_accuracy: 0.8852
Epoch 97/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4863 - accuracy: 0.8413 - val_loss: 0.3961 - val_accuracy: 0.8852
Epoch 98/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4840 - accuracy: 0.8413 - val_loss: 0.3962 - val_accuracy: 0.8852
Epoch 99/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4869 - accuracy: 0.8413 - val_loss: 0.3962 - val_accuracy: 0.8852
Epoch 100/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4842 - accuracy: 0.8413 - val_loss: 0.3958 - val_accuracy: 0.8852
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 32, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 128
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
6/6 [==============================] - 1s 47ms/step - loss: 8.3512 - accuracy: 0.2322 - val_loss: 8.1376 - val_accuracy: 0.2527
Epoch 2/100
6/6 [==============================] - 0s 10ms/step - loss: 8.0367 - accuracy: 0.2814 - val_loss: 7.8453 - val_accuracy: 0.3187
Epoch 3/100
6/6 [==============================] - 0s 10ms/step - loss: 7.7615 - accuracy: 0.3019 - val_loss: 7.5608 - val_accuracy: 0.3571
Epoch 4/100
6/6 [==============================] - 0s 10ms/step - loss: 7.4850 - accuracy: 0.3320 - val_loss: 7.2858 - val_accuracy: 0.3956
Epoch 5/100
6/6 [==============================] - 0s 9ms/step - loss: 7.2600 - accuracy: 0.3497 - val_loss: 7.0217 - val_accuracy: 0.4615
Epoch 6/100
6/6 [==============================] - 0s 10ms/step - loss: 6.9462 - accuracy: 0.4331 - val_loss: 6.7682 - val_accuracy: 0.4780
Epoch 7/100
6/6 [==============================] - 0s 10ms/step - loss: 6.6985 - accuracy: 0.4426 - val_loss: 6.5223 - val_accuracy: 0.5440
Epoch 8/100
6/6 [==============================] - 0s 9ms/step - loss: 6.4454 - accuracy: 0.4822 - val_loss: 6.2849 - val_accuracy: 0.5659
Epoch 9/100
6/6 [==============================] - 0s 10ms/step - loss: 6.2171 - accuracy: 0.5055 - val_loss: 6.0539 - val_accuracy: 0.6044
Epoch 10/100
6/6 [==============================] - 0s 10ms/step - loss: 6.0123 - accuracy: 0.5437 - val_loss: 5.8312 - val_accuracy: 0.6429
Epoch 11/100
6/6 [==============================] - 0s 10ms/step - loss: 5.7790 - accuracy: 0.5970 - val_loss: 5.6172 - val_accuracy: 0.6593
Epoch 12/100
6/6 [==============================] - 0s 11ms/step - loss: 5.5724 - accuracy: 0.6038 - val_loss: 5.4106 - val_accuracy: 0.6978
Epoch 13/100
6/6 [==============================] - 0s 9ms/step - loss: 5.3569 - accuracy: 0.6434 - val_loss: 5.2088 - val_accuracy: 0.7088
Epoch 14/100
6/6 [==============================] - 0s 10ms/step - loss: 5.1581 - accuracy: 0.6612 - val_loss: 5.0150 - val_accuracy: 0.7143
Epoch 15/100
6/6 [==============================] - 0s 12ms/step - loss: 4.9571 - accuracy: 0.6899 - val_loss: 4.8257 - val_accuracy: 0.7253
Epoch 16/100
6/6 [==============================] - 0s 9ms/step - loss: 4.7923 - accuracy: 0.7008 - val_loss: 4.6430 - val_accuracy: 0.7473
Epoch 17/100
6/6 [==============================] - 0s 11ms/step - loss: 4.5990 - accuracy: 0.7213 - val_loss: 4.4636 - val_accuracy: 0.7637
Epoch 18/100
6/6 [==============================] - 0s 10ms/step - loss: 4.4253 - accuracy: 0.7336 - val_loss: 4.2891 - val_accuracy: 0.7692
Epoch 19/100
6/6 [==============================] - 0s 9ms/step - loss: 4.2655 - accuracy: 0.7486 - val_loss: 4.1234 - val_accuracy: 0.7912
Epoch 20/100
6/6 [==============================] - 0s 10ms/step - loss: 4.0935 - accuracy: 0.7678 - val_loss: 3.9640 - val_accuracy: 0.8077
Epoch 21/100
6/6 [==============================] - 0s 10ms/step - loss: 3.9334 - accuracy: 0.7801 - val_loss: 3.8063 - val_accuracy: 0.8242
Epoch 22/100
6/6 [==============================] - 0s 9ms/step - loss: 3.7905 - accuracy: 0.7801 - val_loss: 3.6518 - val_accuracy: 0.8462
Epoch 23/100
6/6 [==============================] - 0s 10ms/step - loss: 3.6251 - accuracy: 0.7978 - val_loss: 3.4996 - val_accuracy: 0.8571
Epoch 24/100
6/6 [==============================] - 0s 10ms/step - loss: 3.4706 - accuracy: 0.8074 - val_loss: 3.3504 - val_accuracy: 0.8516
Epoch 25/100
6/6 [==============================] - 0s 8ms/step - loss: 3.3244 - accuracy: 0.8115 - val_loss: 3.2074 - val_accuracy: 0.8516
Epoch 26/100
6/6 [==============================] - 0s 7ms/step - loss: 3.1846 - accuracy: 0.8183 - val_loss: 3.0661 - val_accuracy: 0.8516
Epoch 27/100
6/6 [==============================] - 0s 8ms/step - loss: 3.0321 - accuracy: 0.8306 - val_loss: 2.9320 - val_accuracy: 0.8516
Epoch 28/100
6/6 [==============================] - 0s 9ms/step - loss: 2.9061 - accuracy: 0.8333 - val_loss: 2.7979 - val_accuracy: 0.8516
Epoch 29/100
6/6 [==============================] - 0s 10ms/step - loss: 2.7791 - accuracy: 0.8320 - val_loss: 2.6656 - val_accuracy: 0.8516
Epoch 30/100
6/6 [==============================] - 0s 7ms/step - loss: 2.6382 - accuracy: 0.8429 - val_loss: 2.5362 - val_accuracy: 0.8571
Epoch 31/100
6/6 [==============================] - 0s 9ms/step - loss: 2.5098 - accuracy: 0.8388 - val_loss: 2.4123 - val_accuracy: 0.8571
Epoch 32/100
6/6 [==============================] - 0s 10ms/step - loss: 2.3947 - accuracy: 0.8443 - val_loss: 2.2907 - val_accuracy: 0.8626
Epoch 33/100
6/6 [==============================] - 0s 9ms/step - loss: 2.2654 - accuracy: 0.8443 - val_loss: 2.1731 - val_accuracy: 0.8626
Epoch 34/100
6/6 [==============================] - 0s 9ms/step - loss: 2.1509 - accuracy: 0.8443 - val_loss: 2.0556 - val_accuracy: 0.8626
Epoch 35/100
6/6 [==============================] - 0s 10ms/step - loss: 2.0333 - accuracy: 0.8497 - val_loss: 1.9447 - val_accuracy: 0.8626
Epoch 36/100
6/6 [==============================] - 0s 10ms/step - loss: 1.9403 - accuracy: 0.8470 - val_loss: 1.8378 - val_accuracy: 0.8626
Epoch 37/100
6/6 [==============================] - 0s 10ms/step - loss: 1.8256 - accuracy: 0.8484 - val_loss: 1.7378 - val_accuracy: 0.8626
Epoch 38/100
6/6 [==============================] - 0s 10ms/step - loss: 1.7285 - accuracy: 0.8443 - val_loss: 1.6383 - val_accuracy: 0.8626
Epoch 39/100
6/6 [==============================] - 0s 11ms/step - loss: 1.6229 - accuracy: 0.8484 - val_loss: 1.5434 - val_accuracy: 0.8626
Epoch 40/100
6/6 [==============================] - 0s 9ms/step - loss: 1.5337 - accuracy: 0.8470 - val_loss: 1.4532 - val_accuracy: 0.8626
Epoch 41/100
6/6 [==============================] - 0s 8ms/step - loss: 1.4522 - accuracy: 0.8456 - val_loss: 1.3669 - val_accuracy: 0.8626
Epoch 42/100
6/6 [==============================] - 0s 10ms/step - loss: 1.3606 - accuracy: 0.8484 - val_loss: 1.2843 - val_accuracy: 0.8626
Epoch 43/100
6/6 [==============================] - 0s 10ms/step - loss: 1.2909 - accuracy: 0.8470 - val_loss: 1.2062 - val_accuracy: 0.8626
Epoch 44/100
6/6 [==============================] - 0s 7ms/step - loss: 1.2099 - accuracy: 0.8470 - val_loss: 1.1300 - val_accuracy: 0.8626
Epoch 45/100
6/6 [==============================] - 0s 8ms/step - loss: 1.1334 - accuracy: 0.8470 - val_loss: 1.0617 - val_accuracy: 0.8626
Epoch 46/100
6/6 [==============================] - 0s 10ms/step - loss: 1.0653 - accuracy: 0.8484 - val_loss: 0.9973 - val_accuracy: 0.8626
Epoch 47/100
6/6 [==============================] - 0s 9ms/step - loss: 1.0046 - accuracy: 0.8470 - val_loss: 0.9377 - val_accuracy: 0.8626
Epoch 48/100
6/6 [==============================] - 0s 11ms/step - loss: 0.9552 - accuracy: 0.8470 - val_loss: 0.8808 - val_accuracy: 0.8626
Epoch 49/100
6/6 [==============================] - 0s 7ms/step - loss: 0.8929 - accuracy: 0.8470 - val_loss: 0.8304 - val_accuracy: 0.8626
Epoch 50/100
6/6 [==============================] - 0s 9ms/step - loss: 0.8402 - accuracy: 0.8470 - val_loss: 0.7813 - val_accuracy: 0.8626
Epoch 51/100
6/6 [==============================] - 0s 10ms/step - loss: 0.7869 - accuracy: 0.8470 - val_loss: 0.7386 - val_accuracy: 0.8626
Epoch 52/100
6/6 [==============================] - 0s 10ms/step - loss: 0.7523 - accuracy: 0.8470 - val_loss: 0.6969 - val_accuracy: 0.8626
Epoch 53/100
6/6 [==============================] - 0s 8ms/step - loss: 0.7210 - accuracy: 0.8470 - val_loss: 0.6568 - val_accuracy: 0.8626
Epoch 54/100
6/6 [==============================] - 0s 10ms/step - loss: 0.6714 - accuracy: 0.8470 - val_loss: 0.6255 - val_accuracy: 0.8626
Epoch 55/100
6/6 [==============================] - 0s 9ms/step - loss: 0.6439 - accuracy: 0.8470 - val_loss: 0.5952 - val_accuracy: 0.8626
Epoch 56/100
6/6 [==============================] - 0s 18ms/step - loss: 0.6206 - accuracy: 0.8470 - val_loss: 0.5704 - val_accuracy: 0.8626
Epoch 57/100
6/6 [==============================] - 0s 11ms/step - loss: 0.5970 - accuracy: 0.8470 - val_loss: 0.5481 - val_accuracy: 0.8626
Epoch 58/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5652 - accuracy: 0.8470 - val_loss: 0.5289 - val_accuracy: 0.8626
Epoch 59/100
6/6 [==============================] - 0s 10ms/step - loss: 0.5578 - accuracy: 0.8470 - val_loss: 0.5113 - val_accuracy: 0.8626
Epoch 60/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5457 - accuracy: 0.8470 - val_loss: 0.4973 - val_accuracy: 0.8626
Epoch 61/100
6/6 [==============================] - 0s 8ms/step - loss: 0.5369 - accuracy: 0.8470 - val_loss: 0.4858 - val_accuracy: 0.8626
Epoch 62/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5136 - accuracy: 0.8470 - val_loss: 0.4755 - val_accuracy: 0.8626
Epoch 63/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5297 - accuracy: 0.8470 - val_loss: 0.4684 - val_accuracy: 0.8626
Epoch 64/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5070 - accuracy: 0.8470 - val_loss: 0.4614 - val_accuracy: 0.8626
Epoch 65/100
6/6 [==============================] - 0s 7ms/step - loss: 0.5004 - accuracy: 0.8470 - val_loss: 0.4580 - val_accuracy: 0.8626
Epoch 66/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5093 - accuracy: 0.8470 - val_loss: 0.4554 - val_accuracy: 0.8626
Epoch 67/100
6/6 [==============================] - 0s 9ms/step - loss: 0.5015 - accuracy: 0.8470 - val_loss: 0.4527 - val_accuracy: 0.8626
Epoch 68/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4858 - accuracy: 0.8470 - val_loss: 0.4502 - val_accuracy: 0.8626
Epoch 69/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4936 - accuracy: 0.8470 - val_loss: 0.4484 - val_accuracy: 0.8626
Epoch 70/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4853 - accuracy: 0.8470 - val_loss: 0.4465 - val_accuracy: 0.8626
Epoch 71/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4836 - accuracy: 0.8470 - val_loss: 0.4441 - val_accuracy: 0.8626
Epoch 72/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4836 - accuracy: 0.8470 - val_loss: 0.4425 - val_accuracy: 0.8626
Epoch 73/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4732 - accuracy: 0.8470 - val_loss: 0.4407 - val_accuracy: 0.8626
Epoch 74/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4774 - accuracy: 0.8470 - val_loss: 0.4392 - val_accuracy: 0.8626
Epoch 75/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4853 - accuracy: 0.8470 - val_loss: 0.4379 - val_accuracy: 0.8626
Epoch 76/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4738 - accuracy: 0.8470 - val_loss: 0.4369 - val_accuracy: 0.8626
Epoch 77/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4763 - accuracy: 0.8470 - val_loss: 0.4365 - val_accuracy: 0.8626
Epoch 78/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4806 - accuracy: 0.8470 - val_loss: 0.4361 - val_accuracy: 0.8626
Epoch 79/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4838 - accuracy: 0.8470 - val_loss: 0.4355 - val_accuracy: 0.8626
Epoch 80/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4855 - accuracy: 0.8470 - val_loss: 0.4352 - val_accuracy: 0.8626
Epoch 81/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4818 - accuracy: 0.8470 - val_loss: 0.4354 - val_accuracy: 0.8626
Epoch 82/100
6/6 [==============================] - 0s 12ms/step - loss: 0.4798 - accuracy: 0.8470 - val_loss: 0.4352 - val_accuracy: 0.8626
Epoch 83/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4737 - accuracy: 0.8470 - val_loss: 0.4352 - val_accuracy: 0.8626
Epoch 84/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4754 - accuracy: 0.8470 - val_loss: 0.4343 - val_accuracy: 0.8626
Epoch 85/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4705 - accuracy: 0.8470 - val_loss: 0.4342 - val_accuracy: 0.8626
Epoch 86/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4761 - accuracy: 0.8470 - val_loss: 0.4337 - val_accuracy: 0.8626
Epoch 87/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4771 - accuracy: 0.8470 - val_loss: 0.4337 - val_accuracy: 0.8626
Epoch 88/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4860 - accuracy: 0.8470 - val_loss: 0.4337 - val_accuracy: 0.8626
Epoch 89/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4768 - accuracy: 0.8470 - val_loss: 0.4333 - val_accuracy: 0.8626
Epoch 90/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4842 - accuracy: 0.8470 - val_loss: 0.4329 - val_accuracy: 0.8626
Epoch 91/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4685 - accuracy: 0.8470 - val_loss: 0.4330 - val_accuracy: 0.8626
Epoch 92/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4679 - accuracy: 0.8470 - val_loss: 0.4330 - val_accuracy: 0.8626
Epoch 93/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4739 - accuracy: 0.8470 - val_loss: 0.4330 - val_accuracy: 0.8626
Epoch 94/100
6/6 [==============================] - 0s 7ms/step - loss: 0.4751 - accuracy: 0.8470 - val_loss: 0.4326 - val_accuracy: 0.8626
Epoch 95/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4683 - accuracy: 0.8470 - val_loss: 0.4319 - val_accuracy: 0.8626
Epoch 96/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4715 - accuracy: 0.8470 - val_loss: 0.4320 - val_accuracy: 0.8626
Epoch 97/100
6/6 [==============================] - 0s 10ms/step - loss: 0.4759 - accuracy: 0.8470 - val_loss: 0.4320 - val_accuracy: 0.8626
Epoch 98/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4781 - accuracy: 0.8470 - val_loss: 0.4319 - val_accuracy: 0.8626
Epoch 99/100
6/6 [==============================] - 0s 8ms/step - loss: 0.4720 - accuracy: 0.8470 - val_loss: 0.4319 - val_accuracy: 0.8626
Epoch 100/100
6/6 [==============================] - 0s 9ms/step - loss: 0.4865 - accuracy: 0.8470 - val_loss: 0.4321 - val_accuracy: 0.8626
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 1ms/step
Experiment number: 8
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 128, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 111ms/step - loss: 2.7059 - accuracy: 0.4145 - val_loss: 2.6693 - val_accuracy: 0.4426
Epoch 2/100
3/3 [==============================] - 0s 25ms/step - loss: 2.6757 - accuracy: 0.4679 - val_loss: 2.6574 - val_accuracy: 0.4536
Epoch 3/100
3/3 [==============================] - 0s 20ms/step - loss: 2.6875 - accuracy: 0.4446 - val_loss: 2.6457 - val_accuracy: 0.4536
Epoch 4/100
3/3 [==============================] - 0s 21ms/step - loss: 2.6780 - accuracy: 0.4542 - val_loss: 2.6340 - val_accuracy: 0.4754
Epoch 5/100
3/3 [==============================] - 0s 19ms/step - loss: 2.6561 - accuracy: 0.4569 - val_loss: 2.6225 - val_accuracy: 0.4754
Epoch 6/100
3/3 [==============================] - 0s 23ms/step - loss: 2.6421 - accuracy: 0.4870 - val_loss: 2.6110 - val_accuracy: 0.4918
Epoch 7/100
3/3 [==============================] - 0s 16ms/step - loss: 2.6377 - accuracy: 0.4870 - val_loss: 2.5997 - val_accuracy: 0.5191
Epoch 8/100
3/3 [==============================] - 0s 19ms/step - loss: 2.6404 - accuracy: 0.4870 - val_loss: 2.5885 - val_accuracy: 0.5355
Epoch 9/100
3/3 [==============================] - 0s 17ms/step - loss: 2.6192 - accuracy: 0.4952 - val_loss: 2.5774 - val_accuracy: 0.5574
Epoch 10/100
3/3 [==============================] - 0s 18ms/step - loss: 2.6124 - accuracy: 0.5048 - val_loss: 2.5664 - val_accuracy: 0.5683
Epoch 11/100
3/3 [==============================] - 0s 16ms/step - loss: 2.6026 - accuracy: 0.5212 - val_loss: 2.5556 - val_accuracy: 0.5792
Epoch 12/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5877 - accuracy: 0.5349 - val_loss: 2.5448 - val_accuracy: 0.5956
Epoch 13/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5787 - accuracy: 0.5431 - val_loss: 2.5341 - val_accuracy: 0.6066
Epoch 14/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5591 - accuracy: 0.5554 - val_loss: 2.5236 - val_accuracy: 0.6284
Epoch 15/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5538 - accuracy: 0.5663 - val_loss: 2.5132 - val_accuracy: 0.6393
Epoch 16/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5464 - accuracy: 0.5841 - val_loss: 2.5029 - val_accuracy: 0.6503
Epoch 17/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5230 - accuracy: 0.6074 - val_loss: 2.4927 - val_accuracy: 0.6776
Epoch 18/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5220 - accuracy: 0.6115 - val_loss: 2.4826 - val_accuracy: 0.6995
Epoch 19/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5127 - accuracy: 0.6156 - val_loss: 2.4726 - val_accuracy: 0.7158
Epoch 20/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5070 - accuracy: 0.6238 - val_loss: 2.4627 - val_accuracy: 0.7322
Epoch 21/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4950 - accuracy: 0.6347 - val_loss: 2.4529 - val_accuracy: 0.7213
Epoch 22/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4650 - accuracy: 0.6607 - val_loss: 2.4432 - val_accuracy: 0.7268
Epoch 23/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4675 - accuracy: 0.6539 - val_loss: 2.4337 - val_accuracy: 0.7322
Epoch 24/100
3/3 [==============================] - 0s 33ms/step - loss: 2.4479 - accuracy: 0.6758 - val_loss: 2.4243 - val_accuracy: 0.7541
Epoch 25/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4510 - accuracy: 0.6457 - val_loss: 2.4149 - val_accuracy: 0.7596
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4348 - accuracy: 0.6840 - val_loss: 2.4056 - val_accuracy: 0.7705
Epoch 27/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4365 - accuracy: 0.6867 - val_loss: 2.3965 - val_accuracy: 0.7760
Epoch 28/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4223 - accuracy: 0.6990 - val_loss: 2.3875 - val_accuracy: 0.7869
Epoch 29/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4219 - accuracy: 0.6785 - val_loss: 2.3785 - val_accuracy: 0.7869
Epoch 30/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3999 - accuracy: 0.7127 - val_loss: 2.3696 - val_accuracy: 0.7923
Epoch 31/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3811 - accuracy: 0.7114 - val_loss: 2.3609 - val_accuracy: 0.7869
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3928 - accuracy: 0.6990 - val_loss: 2.3522 - val_accuracy: 0.7869
Epoch 33/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3709 - accuracy: 0.7373 - val_loss: 2.3436 - val_accuracy: 0.8033
Epoch 34/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3644 - accuracy: 0.7524 - val_loss: 2.3351 - val_accuracy: 0.7978
Epoch 35/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3567 - accuracy: 0.7319 - val_loss: 2.3266 - val_accuracy: 0.7978
Epoch 36/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3425 - accuracy: 0.7510 - val_loss: 2.3183 - val_accuracy: 0.7978
Epoch 37/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3385 - accuracy: 0.7319 - val_loss: 2.3100 - val_accuracy: 0.8087
Epoch 38/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3285 - accuracy: 0.7524 - val_loss: 2.3018 - val_accuracy: 0.8087
Epoch 39/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3315 - accuracy: 0.7469 - val_loss: 2.2937 - val_accuracy: 0.8087
Epoch 40/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3171 - accuracy: 0.7469 - val_loss: 2.2857 - val_accuracy: 0.8087
Epoch 41/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3087 - accuracy: 0.7647 - val_loss: 2.2777 - val_accuracy: 0.8142
Epoch 42/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3082 - accuracy: 0.7729 - val_loss: 2.2699 - val_accuracy: 0.8087
Epoch 43/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2784 - accuracy: 0.7893 - val_loss: 2.2620 - val_accuracy: 0.8087
Epoch 44/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2938 - accuracy: 0.7743 - val_loss: 2.2543 - val_accuracy: 0.8197
Epoch 45/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2725 - accuracy: 0.7839 - val_loss: 2.2466 - val_accuracy: 0.8197
Epoch 46/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2679 - accuracy: 0.7770 - val_loss: 2.2391 - val_accuracy: 0.8197
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2590 - accuracy: 0.7811 - val_loss: 2.2315 - val_accuracy: 0.8197
Epoch 48/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2539 - accuracy: 0.8098 - val_loss: 2.2241 - val_accuracy: 0.8251
Epoch 49/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2454 - accuracy: 0.8057 - val_loss: 2.2168 - val_accuracy: 0.8251
Epoch 50/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2261 - accuracy: 0.8140 - val_loss: 2.2094 - val_accuracy: 0.8251
Epoch 51/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2281 - accuracy: 0.7975 - val_loss: 2.2022 - val_accuracy: 0.8251
Epoch 52/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2180 - accuracy: 0.8030 - val_loss: 2.1950 - val_accuracy: 0.8251
Epoch 53/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2118 - accuracy: 0.8249 - val_loss: 2.1879 - val_accuracy: 0.8251
Epoch 54/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2115 - accuracy: 0.7975 - val_loss: 2.1808 - val_accuracy: 0.8197
Epoch 55/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1978 - accuracy: 0.8345 - val_loss: 2.1738 - val_accuracy: 0.8197
Epoch 56/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1931 - accuracy: 0.8167 - val_loss: 2.1669 - val_accuracy: 0.8197
Epoch 57/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1694 - accuracy: 0.8358 - val_loss: 2.1600 - val_accuracy: 0.8197
Epoch 58/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1717 - accuracy: 0.8304 - val_loss: 2.1532 - val_accuracy: 0.8197
Epoch 59/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1704 - accuracy: 0.8263 - val_loss: 2.1465 - val_accuracy: 0.8197
Epoch 60/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1634 - accuracy: 0.8290 - val_loss: 2.1397 - val_accuracy: 0.8142
Epoch 61/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1501 - accuracy: 0.8167 - val_loss: 2.1331 - val_accuracy: 0.8142
Epoch 62/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1460 - accuracy: 0.8222 - val_loss: 2.1265 - val_accuracy: 0.8197
Epoch 63/100
3/3 [==============================] - 0s 23ms/step - loss: 2.1429 - accuracy: 0.8468 - val_loss: 2.1199 - val_accuracy: 0.8142
Epoch 64/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1282 - accuracy: 0.8386 - val_loss: 2.1134 - val_accuracy: 0.8142
Epoch 65/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1219 - accuracy: 0.8399 - val_loss: 2.1070 - val_accuracy: 0.8142
Epoch 66/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1206 - accuracy: 0.8495 - val_loss: 2.1006 - val_accuracy: 0.8142
Epoch 67/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1196 - accuracy: 0.8235 - val_loss: 2.0943 - val_accuracy: 0.8142
Epoch 68/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1123 - accuracy: 0.8372 - val_loss: 2.0880 - val_accuracy: 0.8142
Epoch 69/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1066 - accuracy: 0.8235 - val_loss: 2.0817 - val_accuracy: 0.8142
Epoch 70/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0911 - accuracy: 0.8372 - val_loss: 2.0754 - val_accuracy: 0.8142
Epoch 71/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0852 - accuracy: 0.8427 - val_loss: 2.0693 - val_accuracy: 0.8142
Epoch 72/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0885 - accuracy: 0.8399 - val_loss: 2.0631 - val_accuracy: 0.8142
Epoch 73/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0670 - accuracy: 0.8550 - val_loss: 2.0570 - val_accuracy: 0.8142
Epoch 74/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0744 - accuracy: 0.8304 - val_loss: 2.0509 - val_accuracy: 0.8142
Epoch 75/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0659 - accuracy: 0.8495 - val_loss: 2.0449 - val_accuracy: 0.8142
Epoch 76/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0636 - accuracy: 0.8495 - val_loss: 2.0389 - val_accuracy: 0.8142
Epoch 77/100
3/3 [==============================] - 0s 18ms/step - loss: 2.0406 - accuracy: 0.8440 - val_loss: 2.0329 - val_accuracy: 0.8142
Epoch 78/100
3/3 [==============================] - 0s 18ms/step - loss: 2.0524 - accuracy: 0.8427 - val_loss: 2.0270 - val_accuracy: 0.8142
Epoch 79/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0430 - accuracy: 0.8454 - val_loss: 2.0211 - val_accuracy: 0.8142
Epoch 80/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0363 - accuracy: 0.8427 - val_loss: 2.0153 - val_accuracy: 0.8142
Epoch 81/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0128 - accuracy: 0.8454 - val_loss: 2.0094 - val_accuracy: 0.8142
Epoch 82/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0263 - accuracy: 0.8468 - val_loss: 2.0037 - val_accuracy: 0.8142
Epoch 83/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0172 - accuracy: 0.8495 - val_loss: 1.9979 - val_accuracy: 0.8142
Epoch 84/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0042 - accuracy: 0.8550 - val_loss: 1.9922 - val_accuracy: 0.8142
Epoch 85/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9928 - accuracy: 0.8495 - val_loss: 1.9866 - val_accuracy: 0.8142
Epoch 86/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9970 - accuracy: 0.8399 - val_loss: 1.9809 - val_accuracy: 0.8142
Epoch 87/100
3/3 [==============================] - 0s 41ms/step - loss: 1.9837 - accuracy: 0.8550 - val_loss: 1.9753 - val_accuracy: 0.8142
Epoch 88/100
3/3 [==============================] - 0s 23ms/step - loss: 1.9801 - accuracy: 0.8523 - val_loss: 1.9698 - val_accuracy: 0.8142
Epoch 89/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9850 - accuracy: 0.8386 - val_loss: 1.9642 - val_accuracy: 0.8142
Epoch 90/100
3/3 [==============================] - 0s 22ms/step - loss: 1.9713 - accuracy: 0.8564 - val_loss: 1.9587 - val_accuracy: 0.8142
Epoch 91/100
3/3 [==============================] - 0s 22ms/step - loss: 1.9553 - accuracy: 0.8564 - val_loss: 1.9532 - val_accuracy: 0.8142
Epoch 92/100
3/3 [==============================] - 0s 22ms/step - loss: 1.9607 - accuracy: 0.8509 - val_loss: 1.9478 - val_accuracy: 0.8142
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9572 - accuracy: 0.8591 - val_loss: 1.9424 - val_accuracy: 0.8142
Epoch 94/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9438 - accuracy: 0.8550 - val_loss: 1.9370 - val_accuracy: 0.8142
Epoch 95/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9393 - accuracy: 0.8495 - val_loss: 1.9316 - val_accuracy: 0.8142
Epoch 96/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9322 - accuracy: 0.8577 - val_loss: 1.9263 - val_accuracy: 0.8142
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9332 - accuracy: 0.8605 - val_loss: 1.9209 - val_accuracy: 0.8142
Epoch 98/100
3/3 [==============================] - 0s 19ms/step - loss: 1.9262 - accuracy: 0.8605 - val_loss: 1.9156 - val_accuracy: 0.8142
Epoch 99/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9310 - accuracy: 0.8550 - val_loss: 1.9103 - val_accuracy: 0.8142
Epoch 100/100
3/3 [==============================] - 0s 26ms/step - loss: 1.9093 - accuracy: 0.8605 - val_loss: 1.9051 - val_accuracy: 0.8142
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 128, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 115ms/step - loss: 2.8085 - accuracy: 0.3680 - val_loss: 2.7400 - val_accuracy: 0.4208
Epoch 2/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8137 - accuracy: 0.3584 - val_loss: 2.7275 - val_accuracy: 0.4208
Epoch 3/100
3/3 [==============================] - 0s 20ms/step - loss: 2.7888 - accuracy: 0.3707 - val_loss: 2.7152 - val_accuracy: 0.4426
Epoch 4/100
3/3 [==============================] - 0s 20ms/step - loss: 2.7772 - accuracy: 0.4131 - val_loss: 2.7029 - val_accuracy: 0.4590
Epoch 5/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7594 - accuracy: 0.4159 - val_loss: 2.6908 - val_accuracy: 0.4699
Epoch 6/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7432 - accuracy: 0.4323 - val_loss: 2.6788 - val_accuracy: 0.4918
Epoch 7/100
3/3 [==============================] - 0s 20ms/step - loss: 2.7513 - accuracy: 0.4227 - val_loss: 2.6668 - val_accuracy: 0.5137
Epoch 8/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7380 - accuracy: 0.4596 - val_loss: 2.6550 - val_accuracy: 0.5519
Epoch 9/100
3/3 [==============================] - 0s 21ms/step - loss: 2.7171 - accuracy: 0.4528 - val_loss: 2.6433 - val_accuracy: 0.5519
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 2.7013 - accuracy: 0.4843 - val_loss: 2.6316 - val_accuracy: 0.5574
Epoch 11/100
3/3 [==============================] - 0s 21ms/step - loss: 2.6949 - accuracy: 0.5075 - val_loss: 2.6201 - val_accuracy: 0.5847
Epoch 12/100
3/3 [==============================] - 0s 22ms/step - loss: 2.6899 - accuracy: 0.4555 - val_loss: 2.6087 - val_accuracy: 0.5956
Epoch 13/100
3/3 [==============================] - 0s 25ms/step - loss: 2.6681 - accuracy: 0.4884 - val_loss: 2.5974 - val_accuracy: 0.5956
Epoch 14/100
3/3 [==============================] - 0s 23ms/step - loss: 2.6677 - accuracy: 0.5034 - val_loss: 2.5862 - val_accuracy: 0.6066
Epoch 15/100
3/3 [==============================] - 0s 17ms/step - loss: 2.6402 - accuracy: 0.5157 - val_loss: 2.5751 - val_accuracy: 0.6066
Epoch 16/100
3/3 [==============================] - 0s 18ms/step - loss: 2.6377 - accuracy: 0.5157 - val_loss: 2.5641 - val_accuracy: 0.6120
Epoch 17/100
3/3 [==============================] - 0s 20ms/step - loss: 2.6411 - accuracy: 0.5226 - val_loss: 2.5532 - val_accuracy: 0.6339
Epoch 18/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5926 - accuracy: 0.5404 - val_loss: 2.5424 - val_accuracy: 0.6393
Epoch 19/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5897 - accuracy: 0.5691 - val_loss: 2.5318 - val_accuracy: 0.6503
Epoch 20/100
3/3 [==============================] - 0s 22ms/step - loss: 2.5941 - accuracy: 0.5540 - val_loss: 2.5212 - val_accuracy: 0.6667
Epoch 21/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5797 - accuracy: 0.5663 - val_loss: 2.5107 - val_accuracy: 0.6831
Epoch 22/100
3/3 [==============================] - 0s 31ms/step - loss: 2.5680 - accuracy: 0.5540 - val_loss: 2.5003 - val_accuracy: 0.6940
Epoch 23/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5611 - accuracy: 0.5964 - val_loss: 2.4901 - val_accuracy: 0.7158
Epoch 24/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5430 - accuracy: 0.6088 - val_loss: 2.4799 - val_accuracy: 0.7377
Epoch 25/100
3/3 [==============================] - 0s 22ms/step - loss: 2.5433 - accuracy: 0.5663 - val_loss: 2.4699 - val_accuracy: 0.7432
Epoch 26/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5102 - accuracy: 0.6416 - val_loss: 2.4599 - val_accuracy: 0.7486
Epoch 27/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5005 - accuracy: 0.6430 - val_loss: 2.4501 - val_accuracy: 0.7432
Epoch 28/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4986 - accuracy: 0.6347 - val_loss: 2.4403 - val_accuracy: 0.7486
Epoch 29/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4893 - accuracy: 0.6334 - val_loss: 2.4307 - val_accuracy: 0.7541
Epoch 30/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4796 - accuracy: 0.6457 - val_loss: 2.4212 - val_accuracy: 0.7760
Epoch 31/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4529 - accuracy: 0.6648 - val_loss: 2.4117 - val_accuracy: 0.7869
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4570 - accuracy: 0.6607 - val_loss: 2.4024 - val_accuracy: 0.7814
Epoch 33/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4527 - accuracy: 0.6799 - val_loss: 2.3931 - val_accuracy: 0.7923
Epoch 34/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4416 - accuracy: 0.6731 - val_loss: 2.3840 - val_accuracy: 0.7923
Epoch 35/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4192 - accuracy: 0.6922 - val_loss: 2.3750 - val_accuracy: 0.7869
Epoch 36/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4259 - accuracy: 0.6908 - val_loss: 2.3660 - val_accuracy: 0.7923
Epoch 37/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4215 - accuracy: 0.7004 - val_loss: 2.3571 - val_accuracy: 0.8033
Epoch 38/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3944 - accuracy: 0.7100 - val_loss: 2.3483 - val_accuracy: 0.8142
Epoch 39/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4033 - accuracy: 0.7127 - val_loss: 2.3395 - val_accuracy: 0.8142
Epoch 40/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3776 - accuracy: 0.7237 - val_loss: 2.3309 - val_accuracy: 0.8197
Epoch 41/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3639 - accuracy: 0.7360 - val_loss: 2.3224 - val_accuracy: 0.8251
Epoch 42/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3770 - accuracy: 0.7073 - val_loss: 2.3139 - val_accuracy: 0.8142
Epoch 43/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3445 - accuracy: 0.7401 - val_loss: 2.3055 - val_accuracy: 0.8142
Epoch 44/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3397 - accuracy: 0.7360 - val_loss: 2.2972 - val_accuracy: 0.8142
Epoch 45/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3458 - accuracy: 0.7442 - val_loss: 2.2890 - val_accuracy: 0.8142
Epoch 46/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3354 - accuracy: 0.7510 - val_loss: 2.2808 - val_accuracy: 0.8142
Epoch 47/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3258 - accuracy: 0.7551 - val_loss: 2.2728 - val_accuracy: 0.8142
Epoch 48/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3037 - accuracy: 0.7606 - val_loss: 2.2647 - val_accuracy: 0.8142
Epoch 49/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3017 - accuracy: 0.7565 - val_loss: 2.2568 - val_accuracy: 0.8251
Epoch 50/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2943 - accuracy: 0.7729 - val_loss: 2.2489 - val_accuracy: 0.8251
Epoch 51/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3010 - accuracy: 0.7538 - val_loss: 2.2411 - val_accuracy: 0.8361
Epoch 52/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2804 - accuracy: 0.7661 - val_loss: 2.2334 - val_accuracy: 0.8361
Epoch 53/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2737 - accuracy: 0.7893 - val_loss: 2.2257 - val_accuracy: 0.8415
Epoch 54/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2641 - accuracy: 0.7866 - val_loss: 2.2182 - val_accuracy: 0.8415
Epoch 55/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2626 - accuracy: 0.7770 - val_loss: 2.2106 - val_accuracy: 0.8415
Epoch 56/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2451 - accuracy: 0.7907 - val_loss: 2.2032 - val_accuracy: 0.8415
Epoch 57/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2367 - accuracy: 0.7852 - val_loss: 2.1958 - val_accuracy: 0.8415
Epoch 58/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2316 - accuracy: 0.8003 - val_loss: 2.1885 - val_accuracy: 0.8415
Epoch 59/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2160 - accuracy: 0.7989 - val_loss: 2.1813 - val_accuracy: 0.8415
Epoch 60/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2087 - accuracy: 0.7962 - val_loss: 2.1741 - val_accuracy: 0.8415
Epoch 61/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2245 - accuracy: 0.7962 - val_loss: 2.1670 - val_accuracy: 0.8415
Epoch 62/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2032 - accuracy: 0.7811 - val_loss: 2.1599 - val_accuracy: 0.8415
Epoch 63/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2019 - accuracy: 0.8085 - val_loss: 2.1529 - val_accuracy: 0.8415
Epoch 64/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1944 - accuracy: 0.8016 - val_loss: 2.1459 - val_accuracy: 0.8415
Epoch 65/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1879 - accuracy: 0.7989 - val_loss: 2.1390 - val_accuracy: 0.8415
Epoch 66/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1757 - accuracy: 0.8085 - val_loss: 2.1321 - val_accuracy: 0.8415
Epoch 67/100
3/3 [==============================] - 0s 24ms/step - loss: 2.1768 - accuracy: 0.8126 - val_loss: 2.1253 - val_accuracy: 0.8415
Epoch 68/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1544 - accuracy: 0.8112 - val_loss: 2.1186 - val_accuracy: 0.8415
Epoch 69/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1508 - accuracy: 0.8140 - val_loss: 2.1119 - val_accuracy: 0.8415
Epoch 70/100
3/3 [==============================] - 0s 23ms/step - loss: 2.1451 - accuracy: 0.8112 - val_loss: 2.1052 - val_accuracy: 0.8415
Epoch 71/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1407 - accuracy: 0.8153 - val_loss: 2.0986 - val_accuracy: 0.8415
Epoch 72/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1280 - accuracy: 0.8181 - val_loss: 2.0920 - val_accuracy: 0.8415
Epoch 73/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1184 - accuracy: 0.8153 - val_loss: 2.0855 - val_accuracy: 0.8415
Epoch 74/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1241 - accuracy: 0.8194 - val_loss: 2.0791 - val_accuracy: 0.8415
Epoch 75/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1167 - accuracy: 0.8167 - val_loss: 2.0727 - val_accuracy: 0.8415
Epoch 76/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1149 - accuracy: 0.8181 - val_loss: 2.0663 - val_accuracy: 0.8415
Epoch 77/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0937 - accuracy: 0.8276 - val_loss: 2.0600 - val_accuracy: 0.8415
Epoch 78/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1048 - accuracy: 0.8181 - val_loss: 2.0537 - val_accuracy: 0.8415
Epoch 79/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0752 - accuracy: 0.8468 - val_loss: 2.0475 - val_accuracy: 0.8415
Epoch 80/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0818 - accuracy: 0.8304 - val_loss: 2.0413 - val_accuracy: 0.8415
Epoch 81/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0776 - accuracy: 0.8317 - val_loss: 2.0351 - val_accuracy: 0.8415
Epoch 82/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0588 - accuracy: 0.8386 - val_loss: 2.0291 - val_accuracy: 0.8415
Epoch 83/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0504 - accuracy: 0.8304 - val_loss: 2.0230 - val_accuracy: 0.8415
Epoch 84/100
3/3 [==============================] - 0s 18ms/step - loss: 2.0515 - accuracy: 0.8345 - val_loss: 2.0170 - val_accuracy: 0.8415
Epoch 85/100
3/3 [==============================] - 0s 24ms/step - loss: 2.0488 - accuracy: 0.8358 - val_loss: 2.0111 - val_accuracy: 0.8415
Epoch 86/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0339 - accuracy: 0.8372 - val_loss: 2.0052 - val_accuracy: 0.8415
Epoch 87/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0391 - accuracy: 0.8249 - val_loss: 1.9993 - val_accuracy: 0.8415
Epoch 88/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0273 - accuracy: 0.8468 - val_loss: 1.9935 - val_accuracy: 0.8415
Epoch 89/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0230 - accuracy: 0.8345 - val_loss: 1.9877 - val_accuracy: 0.8415
Epoch 90/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0198 - accuracy: 0.8386 - val_loss: 1.9819 - val_accuracy: 0.8415
Epoch 91/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0083 - accuracy: 0.8413 - val_loss: 1.9761 - val_accuracy: 0.8415
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0025 - accuracy: 0.8358 - val_loss: 1.9704 - val_accuracy: 0.8415
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0007 - accuracy: 0.8440 - val_loss: 1.9648 - val_accuracy: 0.8415
Epoch 94/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9820 - accuracy: 0.8495 - val_loss: 1.9591 - val_accuracy: 0.8415
Epoch 95/100
3/3 [==============================] - 0s 19ms/step - loss: 1.9805 - accuracy: 0.8317 - val_loss: 1.9535 - val_accuracy: 0.8415
Epoch 96/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9887 - accuracy: 0.8413 - val_loss: 1.9480 - val_accuracy: 0.8415
Epoch 97/100
3/3 [==============================] - 0s 19ms/step - loss: 1.9804 - accuracy: 0.8331 - val_loss: 1.9424 - val_accuracy: 0.8415
Epoch 98/100
3/3 [==============================] - 0s 19ms/step - loss: 1.9630 - accuracy: 0.8386 - val_loss: 1.9369 - val_accuracy: 0.8415
Epoch 99/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9676 - accuracy: 0.8399 - val_loss: 1.9314 - val_accuracy: 0.8415
Epoch 100/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9625 - accuracy: 0.8427 - val_loss: 1.9260 - val_accuracy: 0.8415
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 128, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 115ms/step - loss: 2.6255 - accuracy: 0.5787 - val_loss: 2.5904 - val_accuracy: 0.7268
Epoch 2/100
3/3 [==============================] - 0s 17ms/step - loss: 2.6000 - accuracy: 0.6101 - val_loss: 2.5796 - val_accuracy: 0.7268
Epoch 3/100
3/3 [==============================] - 0s 18ms/step - loss: 2.6102 - accuracy: 0.6033 - val_loss: 2.5689 - val_accuracy: 0.7322
Epoch 4/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5961 - accuracy: 0.6197 - val_loss: 2.5584 - val_accuracy: 0.7486
Epoch 5/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5703 - accuracy: 0.6183 - val_loss: 2.5479 - val_accuracy: 0.7486
Epoch 6/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5651 - accuracy: 0.6539 - val_loss: 2.5376 - val_accuracy: 0.7541
Epoch 7/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5385 - accuracy: 0.6758 - val_loss: 2.5272 - val_accuracy: 0.7650
Epoch 8/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5507 - accuracy: 0.6553 - val_loss: 2.5170 - val_accuracy: 0.7705
Epoch 9/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5402 - accuracy: 0.6607 - val_loss: 2.5069 - val_accuracy: 0.7923
Epoch 10/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5204 - accuracy: 0.6731 - val_loss: 2.4969 - val_accuracy: 0.8033
Epoch 11/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5093 - accuracy: 0.6689 - val_loss: 2.4869 - val_accuracy: 0.8033
Epoch 12/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5001 - accuracy: 0.6908 - val_loss: 2.4771 - val_accuracy: 0.7978
Epoch 13/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4864 - accuracy: 0.7073 - val_loss: 2.4673 - val_accuracy: 0.8087
Epoch 14/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4898 - accuracy: 0.7100 - val_loss: 2.4577 - val_accuracy: 0.8087
Epoch 15/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4590 - accuracy: 0.7168 - val_loss: 2.4481 - val_accuracy: 0.8087
Epoch 16/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4452 - accuracy: 0.7360 - val_loss: 2.4386 - val_accuracy: 0.8142
Epoch 17/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4511 - accuracy: 0.7168 - val_loss: 2.4293 - val_accuracy: 0.8142
Epoch 18/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4205 - accuracy: 0.7442 - val_loss: 2.4200 - val_accuracy: 0.8197
Epoch 19/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4311 - accuracy: 0.7305 - val_loss: 2.4108 - val_accuracy: 0.8306
Epoch 20/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4219 - accuracy: 0.7456 - val_loss: 2.4017 - val_accuracy: 0.8361
Epoch 21/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4234 - accuracy: 0.7415 - val_loss: 2.3926 - val_accuracy: 0.8361
Epoch 22/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4161 - accuracy: 0.7415 - val_loss: 2.3837 - val_accuracy: 0.8306
Epoch 23/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3812 - accuracy: 0.7811 - val_loss: 2.3748 - val_accuracy: 0.8361
Epoch 24/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3783 - accuracy: 0.7497 - val_loss: 2.3661 - val_accuracy: 0.8361
Epoch 25/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3623 - accuracy: 0.7839 - val_loss: 2.3574 - val_accuracy: 0.8361
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3633 - accuracy: 0.7620 - val_loss: 2.3488 - val_accuracy: 0.8361
Epoch 27/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3629 - accuracy: 0.7784 - val_loss: 2.3403 - val_accuracy: 0.8361
Epoch 28/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3352 - accuracy: 0.7852 - val_loss: 2.3318 - val_accuracy: 0.8306
Epoch 29/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3504 - accuracy: 0.7647 - val_loss: 2.3235 - val_accuracy: 0.8361
Epoch 30/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3190 - accuracy: 0.8057 - val_loss: 2.3152 - val_accuracy: 0.8415
Epoch 31/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3282 - accuracy: 0.7825 - val_loss: 2.3070 - val_accuracy: 0.8361
Epoch 32/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3134 - accuracy: 0.7866 - val_loss: 2.2989 - val_accuracy: 0.8361
Epoch 33/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3091 - accuracy: 0.7798 - val_loss: 2.2909 - val_accuracy: 0.8361
Epoch 34/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3044 - accuracy: 0.8030 - val_loss: 2.2829 - val_accuracy: 0.8361
Epoch 35/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2992 - accuracy: 0.7852 - val_loss: 2.2750 - val_accuracy: 0.8415
Epoch 36/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2832 - accuracy: 0.7866 - val_loss: 2.2672 - val_accuracy: 0.8415
Epoch 37/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2665 - accuracy: 0.8167 - val_loss: 2.2594 - val_accuracy: 0.8415
Epoch 38/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2762 - accuracy: 0.8016 - val_loss: 2.2517 - val_accuracy: 0.8415
Epoch 39/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2644 - accuracy: 0.8030 - val_loss: 2.2440 - val_accuracy: 0.8415
Epoch 40/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2576 - accuracy: 0.8098 - val_loss: 2.2364 - val_accuracy: 0.8415
Epoch 41/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2423 - accuracy: 0.8194 - val_loss: 2.2289 - val_accuracy: 0.8415
Epoch 42/100
3/3 [==============================] - 0s 28ms/step - loss: 2.2365 - accuracy: 0.8263 - val_loss: 2.2215 - val_accuracy: 0.8415
Epoch 43/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2097 - accuracy: 0.8345 - val_loss: 2.2141 - val_accuracy: 0.8415
Epoch 44/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2335 - accuracy: 0.8057 - val_loss: 2.2068 - val_accuracy: 0.8415
Epoch 45/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2133 - accuracy: 0.8153 - val_loss: 2.1995 - val_accuracy: 0.8415
Epoch 46/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1903 - accuracy: 0.8372 - val_loss: 2.1923 - val_accuracy: 0.8415
Epoch 47/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1982 - accuracy: 0.8208 - val_loss: 2.1852 - val_accuracy: 0.8415
Epoch 48/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1806 - accuracy: 0.8399 - val_loss: 2.1781 - val_accuracy: 0.8415
Epoch 49/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1677 - accuracy: 0.8399 - val_loss: 2.1711 - val_accuracy: 0.8415
Epoch 50/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1766 - accuracy: 0.8249 - val_loss: 2.1641 - val_accuracy: 0.8415
Epoch 51/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1590 - accuracy: 0.8386 - val_loss: 2.1572 - val_accuracy: 0.8415
Epoch 52/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1705 - accuracy: 0.8317 - val_loss: 2.1503 - val_accuracy: 0.8415
Epoch 53/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1465 - accuracy: 0.8317 - val_loss: 2.1435 - val_accuracy: 0.8415
Epoch 54/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1446 - accuracy: 0.8454 - val_loss: 2.1368 - val_accuracy: 0.8415
Epoch 55/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1296 - accuracy: 0.8440 - val_loss: 2.1301 - val_accuracy: 0.8415
Epoch 56/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1283 - accuracy: 0.8427 - val_loss: 2.1235 - val_accuracy: 0.8415
Epoch 57/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1210 - accuracy: 0.8331 - val_loss: 2.1169 - val_accuracy: 0.8415
Epoch 58/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1084 - accuracy: 0.8399 - val_loss: 2.1103 - val_accuracy: 0.8415
Epoch 59/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1096 - accuracy: 0.8482 - val_loss: 2.1038 - val_accuracy: 0.8415
Epoch 60/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0941 - accuracy: 0.8427 - val_loss: 2.0973 - val_accuracy: 0.8415
Epoch 61/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1078 - accuracy: 0.8317 - val_loss: 2.0909 - val_accuracy: 0.8415
Epoch 62/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0970 - accuracy: 0.8317 - val_loss: 2.0845 - val_accuracy: 0.8415
Epoch 63/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0897 - accuracy: 0.8427 - val_loss: 2.0781 - val_accuracy: 0.8415
Epoch 64/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0763 - accuracy: 0.8399 - val_loss: 2.0718 - val_accuracy: 0.8415
Epoch 65/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0604 - accuracy: 0.8399 - val_loss: 2.0655 - val_accuracy: 0.8415
Epoch 66/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0714 - accuracy: 0.8317 - val_loss: 2.0593 - val_accuracy: 0.8415
Epoch 67/100
3/3 [==============================] - 0s 18ms/step - loss: 2.0654 - accuracy: 0.8372 - val_loss: 2.0531 - val_accuracy: 0.8415
Epoch 68/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0564 - accuracy: 0.8523 - val_loss: 2.0469 - val_accuracy: 0.8415
Epoch 69/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0397 - accuracy: 0.8495 - val_loss: 2.0408 - val_accuracy: 0.8415
Epoch 70/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0457 - accuracy: 0.8399 - val_loss: 2.0347 - val_accuracy: 0.8415
Epoch 71/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0313 - accuracy: 0.8536 - val_loss: 2.0287 - val_accuracy: 0.8415
Epoch 72/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0291 - accuracy: 0.8536 - val_loss: 2.0226 - val_accuracy: 0.8415
Epoch 73/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0162 - accuracy: 0.8413 - val_loss: 2.0166 - val_accuracy: 0.8415
Epoch 74/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0232 - accuracy: 0.8495 - val_loss: 2.0107 - val_accuracy: 0.8415
Epoch 75/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0009 - accuracy: 0.8536 - val_loss: 2.0048 - val_accuracy: 0.8415
Epoch 76/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0004 - accuracy: 0.8440 - val_loss: 1.9989 - val_accuracy: 0.8415
Epoch 77/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0041 - accuracy: 0.8468 - val_loss: 1.9931 - val_accuracy: 0.8415
Epoch 78/100
3/3 [==============================] - 0s 24ms/step - loss: 1.9815 - accuracy: 0.8523 - val_loss: 1.9873 - val_accuracy: 0.8415
Epoch 79/100
3/3 [==============================] - 0s 19ms/step - loss: 1.9965 - accuracy: 0.8454 - val_loss: 1.9816 - val_accuracy: 0.8415
Epoch 80/100
3/3 [==============================] - 0s 23ms/step - loss: 1.9802 - accuracy: 0.8399 - val_loss: 1.9758 - val_accuracy: 0.8415
Epoch 81/100
3/3 [==============================] - 0s 16ms/step - loss: 1.9798 - accuracy: 0.8386 - val_loss: 1.9701 - val_accuracy: 0.8415
Epoch 82/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9774 - accuracy: 0.8358 - val_loss: 1.9644 - val_accuracy: 0.8415
Epoch 83/100
3/3 [==============================] - 0s 17ms/step - loss: 1.9701 - accuracy: 0.8440 - val_loss: 1.9588 - val_accuracy: 0.8415
Epoch 84/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9592 - accuracy: 0.8386 - val_loss: 1.9531 - val_accuracy: 0.8415
Epoch 85/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9559 - accuracy: 0.8440 - val_loss: 1.9475 - val_accuracy: 0.8415
Epoch 86/100
3/3 [==============================] - 0s 19ms/step - loss: 1.9384 - accuracy: 0.8495 - val_loss: 1.9419 - val_accuracy: 0.8415
Epoch 87/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9406 - accuracy: 0.8482 - val_loss: 1.9364 - val_accuracy: 0.8415
Epoch 88/100
3/3 [==============================] - 0s 18ms/step - loss: 1.9427 - accuracy: 0.8482 - val_loss: 1.9309 - val_accuracy: 0.8415
Epoch 89/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9254 - accuracy: 0.8564 - val_loss: 1.9254 - val_accuracy: 0.8415
Epoch 90/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9285 - accuracy: 0.8427 - val_loss: 1.9200 - val_accuracy: 0.8415
Epoch 91/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9182 - accuracy: 0.8495 - val_loss: 1.9146 - val_accuracy: 0.8415
Epoch 92/100
3/3 [==============================] - 0s 16ms/step - loss: 1.9109 - accuracy: 0.8427 - val_loss: 1.9093 - val_accuracy: 0.8415
Epoch 93/100
3/3 [==============================] - 0s 16ms/step - loss: 1.9067 - accuracy: 0.8495 - val_loss: 1.9039 - val_accuracy: 0.8415
Epoch 94/100
3/3 [==============================] - 0s 19ms/step - loss: 1.9100 - accuracy: 0.8523 - val_loss: 1.8986 - val_accuracy: 0.8415
Epoch 95/100
3/3 [==============================] - 0s 18ms/step - loss: 1.8857 - accuracy: 0.8509 - val_loss: 1.8933 - val_accuracy: 0.8415
Epoch 96/100
3/3 [==============================] - 0s 17ms/step - loss: 1.8841 - accuracy: 0.8495 - val_loss: 1.8880 - val_accuracy: 0.8415
Epoch 97/100
3/3 [==============================] - 0s 23ms/step - loss: 1.8843 - accuracy: 0.8495 - val_loss: 1.8827 - val_accuracy: 0.8470
Epoch 98/100
3/3 [==============================] - 0s 18ms/step - loss: 1.8816 - accuracy: 0.8536 - val_loss: 1.8775 - val_accuracy: 0.8470
Epoch 99/100
3/3 [==============================] - 0s 22ms/step - loss: 1.8643 - accuracy: 0.8482 - val_loss: 1.8723 - val_accuracy: 0.8470
Epoch 100/100
3/3 [==============================] - 0s 22ms/step - loss: 1.8626 - accuracy: 0.8591 - val_loss: 1.8671 - val_accuracy: 0.8470
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 128, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 115ms/step - loss: 2.7702 - accuracy: 0.4802 - val_loss: 2.6970 - val_accuracy: 0.5410
Epoch 2/100
3/3 [==============================] - 0s 20ms/step - loss: 2.7538 - accuracy: 0.4870 - val_loss: 2.6850 - val_accuracy: 0.5519
Epoch 3/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7419 - accuracy: 0.4788 - val_loss: 2.6731 - val_accuracy: 0.5628
Epoch 4/100
3/3 [==============================] - 0s 20ms/step - loss: 2.7483 - accuracy: 0.4843 - val_loss: 2.6614 - val_accuracy: 0.5792
Epoch 5/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7146 - accuracy: 0.5253 - val_loss: 2.6497 - val_accuracy: 0.6011
Epoch 6/100
3/3 [==============================] - 0s 16ms/step - loss: 2.7076 - accuracy: 0.5404 - val_loss: 2.6381 - val_accuracy: 0.6011
Epoch 7/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7010 - accuracy: 0.5185 - val_loss: 2.6267 - val_accuracy: 0.6120
Epoch 8/100
3/3 [==============================] - 0s 24ms/step - loss: 2.6882 - accuracy: 0.5404 - val_loss: 2.6154 - val_accuracy: 0.6175
Epoch 9/100
3/3 [==============================] - 0s 19ms/step - loss: 2.6815 - accuracy: 0.5253 - val_loss: 2.6042 - val_accuracy: 0.6230
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 2.6562 - accuracy: 0.5581 - val_loss: 2.5931 - val_accuracy: 0.6503
Epoch 11/100
3/3 [==============================] - 0s 22ms/step - loss: 2.6538 - accuracy: 0.5527 - val_loss: 2.5821 - val_accuracy: 0.6667
Epoch 12/100
3/3 [==============================] - 0s 21ms/step - loss: 2.6429 - accuracy: 0.5540 - val_loss: 2.5712 - val_accuracy: 0.6831
Epoch 13/100
3/3 [==============================] - 0s 18ms/step - loss: 2.6275 - accuracy: 0.5992 - val_loss: 2.5604 - val_accuracy: 0.6995
Epoch 14/100
3/3 [==============================] - 0s 20ms/step - loss: 2.6295 - accuracy: 0.5746 - val_loss: 2.5497 - val_accuracy: 0.7104
Epoch 15/100
3/3 [==============================] - 0s 28ms/step - loss: 2.6019 - accuracy: 0.5910 - val_loss: 2.5391 - val_accuracy: 0.7213
Epoch 16/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5917 - accuracy: 0.6265 - val_loss: 2.5287 - val_accuracy: 0.7322
Epoch 17/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5818 - accuracy: 0.6129 - val_loss: 2.5183 - val_accuracy: 0.7432
Epoch 18/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5621 - accuracy: 0.6320 - val_loss: 2.5080 - val_accuracy: 0.7486
Epoch 19/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5715 - accuracy: 0.6279 - val_loss: 2.4978 - val_accuracy: 0.7650
Epoch 20/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5430 - accuracy: 0.6293 - val_loss: 2.4877 - val_accuracy: 0.7650
Epoch 21/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5362 - accuracy: 0.6484 - val_loss: 2.4778 - val_accuracy: 0.7760
Epoch 22/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5384 - accuracy: 0.6293 - val_loss: 2.4679 - val_accuracy: 0.7869
Epoch 23/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5248 - accuracy: 0.6306 - val_loss: 2.4581 - val_accuracy: 0.8033
Epoch 24/100
3/3 [==============================] - 0s 26ms/step - loss: 2.5159 - accuracy: 0.6744 - val_loss: 2.4484 - val_accuracy: 0.8033
Epoch 25/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5080 - accuracy: 0.6717 - val_loss: 2.4389 - val_accuracy: 0.8087
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4907 - accuracy: 0.6580 - val_loss: 2.4294 - val_accuracy: 0.8251
Epoch 27/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4907 - accuracy: 0.6758 - val_loss: 2.4200 - val_accuracy: 0.8251
Epoch 28/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4673 - accuracy: 0.7086 - val_loss: 2.4107 - val_accuracy: 0.8251
Epoch 29/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4637 - accuracy: 0.7018 - val_loss: 2.4014 - val_accuracy: 0.8361
Epoch 30/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4665 - accuracy: 0.6990 - val_loss: 2.3923 - val_accuracy: 0.8361
Epoch 31/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4362 - accuracy: 0.7346 - val_loss: 2.3833 - val_accuracy: 0.8470
Epoch 32/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4311 - accuracy: 0.7237 - val_loss: 2.3744 - val_accuracy: 0.8470
Epoch 33/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4219 - accuracy: 0.7155 - val_loss: 2.3655 - val_accuracy: 0.8470
Epoch 34/100
3/3 [==============================] - 0s 22ms/step - loss: 2.4348 - accuracy: 0.7373 - val_loss: 2.3568 - val_accuracy: 0.8525
Epoch 35/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4089 - accuracy: 0.7237 - val_loss: 2.3481 - val_accuracy: 0.8525
Epoch 36/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3855 - accuracy: 0.7469 - val_loss: 2.3395 - val_accuracy: 0.8525
Epoch 37/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3959 - accuracy: 0.7401 - val_loss: 2.3310 - val_accuracy: 0.8579
Epoch 38/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3825 - accuracy: 0.7428 - val_loss: 2.3226 - val_accuracy: 0.8634
Epoch 39/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3803 - accuracy: 0.7483 - val_loss: 2.3142 - val_accuracy: 0.8634
Epoch 40/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3811 - accuracy: 0.7497 - val_loss: 2.3059 - val_accuracy: 0.8634
Epoch 41/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3520 - accuracy: 0.7661 - val_loss: 2.2977 - val_accuracy: 0.8634
Epoch 42/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3470 - accuracy: 0.7688 - val_loss: 2.2897 - val_accuracy: 0.8634
Epoch 43/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3490 - accuracy: 0.7743 - val_loss: 2.2817 - val_accuracy: 0.8689
Epoch 44/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3212 - accuracy: 0.7798 - val_loss: 2.2737 - val_accuracy: 0.8689
Epoch 45/100
3/3 [==============================] - 0s 14ms/step - loss: 2.3168 - accuracy: 0.7729 - val_loss: 2.2659 - val_accuracy: 0.8689
Epoch 46/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3151 - accuracy: 0.7702 - val_loss: 2.2581 - val_accuracy: 0.8689
Epoch 47/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3210 - accuracy: 0.7880 - val_loss: 2.2504 - val_accuracy: 0.8743
Epoch 48/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3059 - accuracy: 0.7756 - val_loss: 2.2427 - val_accuracy: 0.8743
Epoch 49/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2808 - accuracy: 0.7989 - val_loss: 2.2351 - val_accuracy: 0.8743
Epoch 50/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2851 - accuracy: 0.7825 - val_loss: 2.2276 - val_accuracy: 0.8743
Epoch 51/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2767 - accuracy: 0.7880 - val_loss: 2.2201 - val_accuracy: 0.8743
Epoch 52/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2831 - accuracy: 0.7756 - val_loss: 2.2127 - val_accuracy: 0.8743
Epoch 53/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2493 - accuracy: 0.8085 - val_loss: 2.2053 - val_accuracy: 0.8743
Epoch 54/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2702 - accuracy: 0.7907 - val_loss: 2.1981 - val_accuracy: 0.8743
Epoch 55/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2598 - accuracy: 0.7989 - val_loss: 2.1909 - val_accuracy: 0.8852
Epoch 56/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2395 - accuracy: 0.7989 - val_loss: 2.1837 - val_accuracy: 0.8852
Epoch 57/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2295 - accuracy: 0.8071 - val_loss: 2.1766 - val_accuracy: 0.8852
Epoch 58/100
3/3 [==============================] - 0s 15ms/step - loss: 2.2323 - accuracy: 0.8003 - val_loss: 2.1696 - val_accuracy: 0.8852
Epoch 59/100
3/3 [==============================] - 0s 41ms/step - loss: 2.2337 - accuracy: 0.7989 - val_loss: 2.1626 - val_accuracy: 0.8852
Epoch 60/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2107 - accuracy: 0.8140 - val_loss: 2.1557 - val_accuracy: 0.8852
Epoch 61/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2261 - accuracy: 0.7975 - val_loss: 2.1488 - val_accuracy: 0.8852
Epoch 62/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1915 - accuracy: 0.8153 - val_loss: 2.1420 - val_accuracy: 0.8852
Epoch 63/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1876 - accuracy: 0.8112 - val_loss: 2.1353 - val_accuracy: 0.8852
Epoch 64/100
3/3 [==============================] - 0s 24ms/step - loss: 2.1920 - accuracy: 0.8126 - val_loss: 2.1285 - val_accuracy: 0.8852
Epoch 65/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1766 - accuracy: 0.8098 - val_loss: 2.1219 - val_accuracy: 0.8852
Epoch 66/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1607 - accuracy: 0.8263 - val_loss: 2.1153 - val_accuracy: 0.8852
Epoch 67/100
3/3 [==============================] - 0s 25ms/step - loss: 2.1576 - accuracy: 0.8167 - val_loss: 2.1087 - val_accuracy: 0.8852
Epoch 68/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1524 - accuracy: 0.8235 - val_loss: 2.1022 - val_accuracy: 0.8852
Epoch 69/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1560 - accuracy: 0.8140 - val_loss: 2.0957 - val_accuracy: 0.8852
Epoch 70/100
3/3 [==============================] - 0s 24ms/step - loss: 2.1382 - accuracy: 0.8235 - val_loss: 2.0893 - val_accuracy: 0.8852
Epoch 71/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1356 - accuracy: 0.8126 - val_loss: 2.0830 - val_accuracy: 0.8852
Epoch 72/100
3/3 [==============================] - 0s 15ms/step - loss: 2.1220 - accuracy: 0.8208 - val_loss: 2.0767 - val_accuracy: 0.8852
Epoch 73/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1241 - accuracy: 0.8167 - val_loss: 2.0704 - val_accuracy: 0.8852
Epoch 74/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1164 - accuracy: 0.8290 - val_loss: 2.0641 - val_accuracy: 0.8852
Epoch 75/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1011 - accuracy: 0.8290 - val_loss: 2.0579 - val_accuracy: 0.8852
Epoch 76/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1045 - accuracy: 0.8249 - val_loss: 2.0518 - val_accuracy: 0.8852
Epoch 77/100
3/3 [==============================] - 0s 27ms/step - loss: 2.0971 - accuracy: 0.8263 - val_loss: 2.0456 - val_accuracy: 0.8852
Epoch 78/100
3/3 [==============================] - 0s 25ms/step - loss: 2.0902 - accuracy: 0.8222 - val_loss: 2.0396 - val_accuracy: 0.8852
Epoch 79/100
3/3 [==============================] - 0s 24ms/step - loss: 2.0888 - accuracy: 0.8317 - val_loss: 2.0336 - val_accuracy: 0.8852
Epoch 80/100
3/3 [==============================] - 0s 29ms/step - loss: 2.0874 - accuracy: 0.8235 - val_loss: 2.0276 - val_accuracy: 0.8852
Epoch 81/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0629 - accuracy: 0.8263 - val_loss: 2.0216 - val_accuracy: 0.8852
Epoch 82/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0714 - accuracy: 0.8331 - val_loss: 2.0157 - val_accuracy: 0.8852
Epoch 83/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0663 - accuracy: 0.8208 - val_loss: 2.0098 - val_accuracy: 0.8852
Epoch 84/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0481 - accuracy: 0.8276 - val_loss: 2.0040 - val_accuracy: 0.8852
Epoch 85/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0382 - accuracy: 0.8304 - val_loss: 1.9982 - val_accuracy: 0.8852
Epoch 86/100
3/3 [==============================] - 0s 24ms/step - loss: 2.0488 - accuracy: 0.8317 - val_loss: 1.9924 - val_accuracy: 0.8852
Epoch 87/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0304 - accuracy: 0.8372 - val_loss: 1.9867 - val_accuracy: 0.8852
Epoch 88/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0222 - accuracy: 0.8345 - val_loss: 1.9810 - val_accuracy: 0.8852
Epoch 89/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0197 - accuracy: 0.8263 - val_loss: 1.9753 - val_accuracy: 0.8852
Epoch 90/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0210 - accuracy: 0.8317 - val_loss: 1.9697 - val_accuracy: 0.8852
Epoch 91/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0188 - accuracy: 0.8386 - val_loss: 1.9641 - val_accuracy: 0.8852
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0126 - accuracy: 0.8331 - val_loss: 1.9585 - val_accuracy: 0.8852
Epoch 93/100
3/3 [==============================] - 0s 17ms/step - loss: 1.9994 - accuracy: 0.8331 - val_loss: 1.9529 - val_accuracy: 0.8852
Epoch 94/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9995 - accuracy: 0.8358 - val_loss: 1.9474 - val_accuracy: 0.8852
Epoch 95/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9797 - accuracy: 0.8345 - val_loss: 1.9419 - val_accuracy: 0.8852
Epoch 96/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9935 - accuracy: 0.8358 - val_loss: 1.9364 - val_accuracy: 0.8852
Epoch 97/100
3/3 [==============================] - 0s 17ms/step - loss: 1.9851 - accuracy: 0.8372 - val_loss: 1.9310 - val_accuracy: 0.8852
Epoch 98/100
3/3 [==============================] - 0s 23ms/step - loss: 1.9791 - accuracy: 0.8317 - val_loss: 1.9255 - val_accuracy: 0.8852
Epoch 99/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9720 - accuracy: 0.8345 - val_loss: 1.9202 - val_accuracy: 0.8852
Epoch 100/100
3/3 [==============================] - 0s 23ms/step - loss: 1.9705 - accuracy: 0.8331 - val_loss: 1.9149 - val_accuracy: 0.8852
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 128, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None}
Batch size: 256
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
3/3 [==============================] - 1s 117ms/step - loss: 2.8987 - accuracy: 0.2213 - val_loss: 2.8512 - val_accuracy: 0.1813
Epoch 2/100
3/3 [==============================] - 0s 23ms/step - loss: 2.8882 - accuracy: 0.2514 - val_loss: 2.8380 - val_accuracy: 0.1923
Epoch 3/100
3/3 [==============================] - 0s 19ms/step - loss: 2.8576 - accuracy: 0.2609 - val_loss: 2.8249 - val_accuracy: 0.2088
Epoch 4/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8433 - accuracy: 0.2623 - val_loss: 2.8120 - val_accuracy: 0.2363
Epoch 5/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8403 - accuracy: 0.2773 - val_loss: 2.7991 - val_accuracy: 0.2363
Epoch 6/100
3/3 [==============================] - 0s 20ms/step - loss: 2.8218 - accuracy: 0.2855 - val_loss: 2.7863 - val_accuracy: 0.2418
Epoch 7/100
3/3 [==============================] - 0s 19ms/step - loss: 2.8168 - accuracy: 0.2992 - val_loss: 2.7736 - val_accuracy: 0.2527
Epoch 8/100
3/3 [==============================] - 0s 20ms/step - loss: 2.8045 - accuracy: 0.2910 - val_loss: 2.7610 - val_accuracy: 0.2582
Epoch 9/100
3/3 [==============================] - 0s 20ms/step - loss: 2.7908 - accuracy: 0.3101 - val_loss: 2.7485 - val_accuracy: 0.2747
Epoch 10/100
3/3 [==============================] - 0s 24ms/step - loss: 2.7774 - accuracy: 0.3374 - val_loss: 2.7361 - val_accuracy: 0.2912
Epoch 11/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7844 - accuracy: 0.3306 - val_loss: 2.7238 - val_accuracy: 0.2967
Epoch 12/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7365 - accuracy: 0.3497 - val_loss: 2.7116 - val_accuracy: 0.3297
Epoch 13/100
3/3 [==============================] - 0s 20ms/step - loss: 2.7354 - accuracy: 0.3579 - val_loss: 2.6995 - val_accuracy: 0.3516
Epoch 14/100
3/3 [==============================] - 0s 21ms/step - loss: 2.7509 - accuracy: 0.3169 - val_loss: 2.6875 - val_accuracy: 0.3626
Epoch 15/100
3/3 [==============================] - 0s 19ms/step - loss: 2.7072 - accuracy: 0.3784 - val_loss: 2.6756 - val_accuracy: 0.3626
Epoch 16/100
3/3 [==============================] - 0s 20ms/step - loss: 2.7207 - accuracy: 0.3702 - val_loss: 2.6638 - val_accuracy: 0.3791
Epoch 17/100
3/3 [==============================] - 0s 19ms/step - loss: 2.6851 - accuracy: 0.4044 - val_loss: 2.6520 - val_accuracy: 0.4011
Epoch 18/100
3/3 [==============================] - 0s 17ms/step - loss: 2.6751 - accuracy: 0.4139 - val_loss: 2.6404 - val_accuracy: 0.4231
Epoch 19/100
3/3 [==============================] - 0s 20ms/step - loss: 2.6600 - accuracy: 0.4331 - val_loss: 2.6289 - val_accuracy: 0.4341
Epoch 20/100
3/3 [==============================] - 0s 23ms/step - loss: 2.6646 - accuracy: 0.4385 - val_loss: 2.6175 - val_accuracy: 0.4396
Epoch 21/100
3/3 [==============================] - 0s 21ms/step - loss: 2.6418 - accuracy: 0.4290 - val_loss: 2.6062 - val_accuracy: 0.4505
Epoch 22/100
3/3 [==============================] - 0s 20ms/step - loss: 2.6163 - accuracy: 0.4699 - val_loss: 2.5950 - val_accuracy: 0.4835
Epoch 23/100
3/3 [==============================] - 0s 23ms/step - loss: 2.6212 - accuracy: 0.4604 - val_loss: 2.5839 - val_accuracy: 0.5055
Epoch 24/100
3/3 [==============================] - 0s 19ms/step - loss: 2.6012 - accuracy: 0.4959 - val_loss: 2.5729 - val_accuracy: 0.5220
Epoch 25/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5987 - accuracy: 0.4945 - val_loss: 2.5620 - val_accuracy: 0.5385
Epoch 26/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5854 - accuracy: 0.4891 - val_loss: 2.5512 - val_accuracy: 0.5659
Epoch 27/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5953 - accuracy: 0.4863 - val_loss: 2.5405 - val_accuracy: 0.6099
Epoch 28/100
3/3 [==============================] - 0s 22ms/step - loss: 2.5752 - accuracy: 0.4959 - val_loss: 2.5298 - val_accuracy: 0.6154
Epoch 29/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5512 - accuracy: 0.5232 - val_loss: 2.5193 - val_accuracy: 0.6374
Epoch 30/100
3/3 [==============================] - 0s 22ms/step - loss: 2.5577 - accuracy: 0.5027 - val_loss: 2.5088 - val_accuracy: 0.6484
Epoch 31/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5292 - accuracy: 0.5505 - val_loss: 2.4985 - val_accuracy: 0.6758
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5186 - accuracy: 0.5587 - val_loss: 2.4883 - val_accuracy: 0.6923
Epoch 33/100
3/3 [==============================] - 0s 26ms/step - loss: 2.5027 - accuracy: 0.5997 - val_loss: 2.4781 - val_accuracy: 0.7033
Epoch 34/100
3/3 [==============================] - 0s 24ms/step - loss: 2.5045 - accuracy: 0.5697 - val_loss: 2.4681 - val_accuracy: 0.7088
Epoch 35/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5002 - accuracy: 0.5697 - val_loss: 2.4581 - val_accuracy: 0.7198
Epoch 36/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4871 - accuracy: 0.5820 - val_loss: 2.4482 - val_accuracy: 0.7253
Epoch 37/100
3/3 [==============================] - 0s 27ms/step - loss: 2.4769 - accuracy: 0.5997 - val_loss: 2.4384 - val_accuracy: 0.7363
Epoch 38/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4616 - accuracy: 0.6202 - val_loss: 2.4287 - val_accuracy: 0.7363
Epoch 39/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4532 - accuracy: 0.5929 - val_loss: 2.4191 - val_accuracy: 0.7527
Epoch 40/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4410 - accuracy: 0.6544 - val_loss: 2.4096 - val_accuracy: 0.7582
Epoch 41/100
3/3 [==============================] - 0s 22ms/step - loss: 2.4378 - accuracy: 0.6503 - val_loss: 2.4002 - val_accuracy: 0.7582
Epoch 42/100
3/3 [==============================] - 0s 22ms/step - loss: 2.4274 - accuracy: 0.6284 - val_loss: 2.3908 - val_accuracy: 0.7747
Epoch 43/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4238 - accuracy: 0.6257 - val_loss: 2.3816 - val_accuracy: 0.7857
Epoch 44/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3966 - accuracy: 0.6694 - val_loss: 2.3724 - val_accuracy: 0.7857
Epoch 45/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3883 - accuracy: 0.6954 - val_loss: 2.3634 - val_accuracy: 0.7912
Epoch 46/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3900 - accuracy: 0.6885 - val_loss: 2.3544 - val_accuracy: 0.7967
Epoch 47/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3807 - accuracy: 0.6708 - val_loss: 2.3455 - val_accuracy: 0.7967
Epoch 48/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3828 - accuracy: 0.6639 - val_loss: 2.3367 - val_accuracy: 0.7967
Epoch 49/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3612 - accuracy: 0.7049 - val_loss: 2.3279 - val_accuracy: 0.7967
Epoch 50/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3590 - accuracy: 0.6831 - val_loss: 2.3192 - val_accuracy: 0.7967
Epoch 51/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3433 - accuracy: 0.7172 - val_loss: 2.3106 - val_accuracy: 0.8022
Epoch 52/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3390 - accuracy: 0.7145 - val_loss: 2.3021 - val_accuracy: 0.8132
Epoch 53/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3272 - accuracy: 0.7295 - val_loss: 2.2936 - val_accuracy: 0.8132
Epoch 54/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3239 - accuracy: 0.7514 - val_loss: 2.2852 - val_accuracy: 0.8132
Epoch 55/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3159 - accuracy: 0.7350 - val_loss: 2.2769 - val_accuracy: 0.8187
Epoch 56/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3108 - accuracy: 0.7281 - val_loss: 2.2686 - val_accuracy: 0.8187
Epoch 57/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2897 - accuracy: 0.7363 - val_loss: 2.2604 - val_accuracy: 0.8242
Epoch 58/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2824 - accuracy: 0.7609 - val_loss: 2.2523 - val_accuracy: 0.8297
Epoch 59/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2790 - accuracy: 0.7459 - val_loss: 2.2442 - val_accuracy: 0.8297
Epoch 60/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2675 - accuracy: 0.7637 - val_loss: 2.2363 - val_accuracy: 0.8297
Epoch 61/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2587 - accuracy: 0.7514 - val_loss: 2.2283 - val_accuracy: 0.8297
Epoch 62/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2634 - accuracy: 0.7623 - val_loss: 2.2205 - val_accuracy: 0.8407
Epoch 63/100
3/3 [==============================] - 0s 23ms/step - loss: 2.2509 - accuracy: 0.7568 - val_loss: 2.2127 - val_accuracy: 0.8407
Epoch 64/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2384 - accuracy: 0.7746 - val_loss: 2.2050 - val_accuracy: 0.8407
Epoch 65/100
3/3 [==============================] - 0s 20ms/step - loss: 2.2334 - accuracy: 0.7541 - val_loss: 2.1973 - val_accuracy: 0.8462
Epoch 66/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2097 - accuracy: 0.8074 - val_loss: 2.1897 - val_accuracy: 0.8571
Epoch 67/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2272 - accuracy: 0.7760 - val_loss: 2.1821 - val_accuracy: 0.8571
Epoch 68/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2163 - accuracy: 0.7855 - val_loss: 2.1747 - val_accuracy: 0.8571
Epoch 69/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2094 - accuracy: 0.7555 - val_loss: 2.1672 - val_accuracy: 0.8571
Epoch 70/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1936 - accuracy: 0.8019 - val_loss: 2.1599 - val_accuracy: 0.8571
Epoch 71/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1839 - accuracy: 0.8087 - val_loss: 2.1526 - val_accuracy: 0.8571
Epoch 72/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1839 - accuracy: 0.7910 - val_loss: 2.1453 - val_accuracy: 0.8571
Epoch 73/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1705 - accuracy: 0.8019 - val_loss: 2.1381 - val_accuracy: 0.8571
Epoch 74/100
3/3 [==============================] - 0s 24ms/step - loss: 2.1660 - accuracy: 0.7992 - val_loss: 2.1310 - val_accuracy: 0.8626
Epoch 75/100
3/3 [==============================] - 0s 25ms/step - loss: 2.1393 - accuracy: 0.8156 - val_loss: 2.1239 - val_accuracy: 0.8681
Epoch 76/100
3/3 [==============================] - 0s 27ms/step - loss: 2.1613 - accuracy: 0.7964 - val_loss: 2.1168 - val_accuracy: 0.8681
Epoch 77/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1354 - accuracy: 0.8128 - val_loss: 2.1098 - val_accuracy: 0.8626
Epoch 78/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1448 - accuracy: 0.7883 - val_loss: 2.1029 - val_accuracy: 0.8736
Epoch 79/100
3/3 [==============================] - 0s 16ms/step - loss: 2.1268 - accuracy: 0.8060 - val_loss: 2.0960 - val_accuracy: 0.8736
Epoch 80/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1147 - accuracy: 0.8074 - val_loss: 2.0891 - val_accuracy: 0.8681
Epoch 81/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1068 - accuracy: 0.8224 - val_loss: 2.0822 - val_accuracy: 0.8681
Epoch 82/100
3/3 [==============================] - 0s 16ms/step - loss: 2.1138 - accuracy: 0.8156 - val_loss: 2.0755 - val_accuracy: 0.8681
Epoch 83/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0916 - accuracy: 0.8238 - val_loss: 2.0687 - val_accuracy: 0.8681
Epoch 84/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0966 - accuracy: 0.8128 - val_loss: 2.0621 - val_accuracy: 0.8681
Epoch 85/100
3/3 [==============================] - 0s 16ms/step - loss: 2.0848 - accuracy: 0.8265 - val_loss: 2.0554 - val_accuracy: 0.8681
Epoch 86/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0756 - accuracy: 0.8292 - val_loss: 2.0488 - val_accuracy: 0.8681
Epoch 87/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0722 - accuracy: 0.8224 - val_loss: 2.0423 - val_accuracy: 0.8681
Epoch 88/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0603 - accuracy: 0.8333 - val_loss: 2.0358 - val_accuracy: 0.8681
Epoch 89/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0572 - accuracy: 0.8320 - val_loss: 2.0293 - val_accuracy: 0.8681
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0561 - accuracy: 0.8292 - val_loss: 2.0229 - val_accuracy: 0.8681
Epoch 91/100
3/3 [==============================] - 0s 25ms/step - loss: 2.0482 - accuracy: 0.8415 - val_loss: 2.0165 - val_accuracy: 0.8681
Epoch 92/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0349 - accuracy: 0.8224 - val_loss: 2.0102 - val_accuracy: 0.8681
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0326 - accuracy: 0.8279 - val_loss: 2.0039 - val_accuracy: 0.8681
Epoch 94/100
3/3 [==============================] - 0s 16ms/step - loss: 2.0219 - accuracy: 0.8443 - val_loss: 1.9976 - val_accuracy: 0.8681
Epoch 95/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0173 - accuracy: 0.8443 - val_loss: 1.9914 - val_accuracy: 0.8681
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 2.0163 - accuracy: 0.8415 - val_loss: 1.9852 - val_accuracy: 0.8681
Epoch 97/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0129 - accuracy: 0.8224 - val_loss: 1.9791 - val_accuracy: 0.8681
Epoch 98/100
3/3 [==============================] - 0s 17ms/step - loss: 1.9993 - accuracy: 0.8347 - val_loss: 1.9730 - val_accuracy: 0.8681
Epoch 99/100
3/3 [==============================] - 0s 20ms/step - loss: 1.9990 - accuracy: 0.8374 - val_loss: 1.9669 - val_accuracy: 0.8681
Epoch 100/100
3/3 [==============================] - 0s 40ms/step - loss: 1.9927 - accuracy: 0.8415 - val_loss: 1.9609 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Experiment number: 9
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 223ms/step - loss: 1.4101 - accuracy: 0.3762 - val_loss: 1.1326 - val_accuracy: 0.4754
Epoch 2/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2232 - accuracy: 0.4651 - val_loss: 1.0242 - val_accuracy: 0.5628
Epoch 3/100
2/2 [==============================] - 0s 30ms/step - loss: 1.1437 - accuracy: 0.5472 - val_loss: 0.9471 - val_accuracy: 0.6175
Epoch 4/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0811 - accuracy: 0.5869 - val_loss: 0.8951 - val_accuracy: 0.6503
Epoch 5/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9788 - accuracy: 0.6293 - val_loss: 0.8535 - val_accuracy: 0.6776
Epoch 6/100
2/2 [==============================] - 0s 44ms/step - loss: 0.9355 - accuracy: 0.6813 - val_loss: 0.8175 - val_accuracy: 0.7158
Epoch 7/100
2/2 [==============================] - 0s 44ms/step - loss: 0.9423 - accuracy: 0.6840 - val_loss: 0.7899 - val_accuracy: 0.7377
Epoch 8/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8889 - accuracy: 0.6949 - val_loss: 0.7663 - val_accuracy: 0.7760
Epoch 9/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8711 - accuracy: 0.6922 - val_loss: 0.7469 - val_accuracy: 0.7869
Epoch 10/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8194 - accuracy: 0.7264 - val_loss: 0.7289 - val_accuracy: 0.7923
Epoch 11/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7865 - accuracy: 0.7510 - val_loss: 0.7137 - val_accuracy: 0.8033
Epoch 12/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8471 - accuracy: 0.7428 - val_loss: 0.7000 - val_accuracy: 0.8033
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7564 - accuracy: 0.7661 - val_loss: 0.6890 - val_accuracy: 0.8087
Epoch 14/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7758 - accuracy: 0.7661 - val_loss: 0.6787 - val_accuracy: 0.8197
Epoch 15/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7673 - accuracy: 0.7729 - val_loss: 0.6688 - val_accuracy: 0.8197
Epoch 16/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7609 - accuracy: 0.7784 - val_loss: 0.6612 - val_accuracy: 0.8251
Epoch 17/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7618 - accuracy: 0.7784 - val_loss: 0.6530 - val_accuracy: 0.8251
Epoch 18/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7705 - accuracy: 0.7770 - val_loss: 0.6453 - val_accuracy: 0.8251
Epoch 19/100
2/2 [==============================] - 0s 48ms/step - loss: 0.7193 - accuracy: 0.8057 - val_loss: 0.6381 - val_accuracy: 0.8251
Epoch 20/100
2/2 [==============================] - 0s 58ms/step - loss: 0.7128 - accuracy: 0.8126 - val_loss: 0.6310 - val_accuracy: 0.8251
Epoch 21/100
2/2 [==============================] - 0s 44ms/step - loss: 0.7210 - accuracy: 0.7907 - val_loss: 0.6254 - val_accuracy: 0.8251
Epoch 22/100
2/2 [==============================] - 0s 52ms/step - loss: 0.6879 - accuracy: 0.8098 - val_loss: 0.6197 - val_accuracy: 0.8306
Epoch 23/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7192 - accuracy: 0.7880 - val_loss: 0.6144 - val_accuracy: 0.8306
Epoch 24/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6792 - accuracy: 0.8181 - val_loss: 0.6094 - val_accuracy: 0.8306
Epoch 25/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6889 - accuracy: 0.8071 - val_loss: 0.6050 - val_accuracy: 0.8251
Epoch 26/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6777 - accuracy: 0.8098 - val_loss: 0.6005 - val_accuracy: 0.8251
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6202 - accuracy: 0.8317 - val_loss: 0.5973 - val_accuracy: 0.8251
Epoch 28/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6940 - accuracy: 0.8167 - val_loss: 0.5934 - val_accuracy: 0.8251
Epoch 29/100
2/2 [==============================] - 0s 44ms/step - loss: 0.6389 - accuracy: 0.8276 - val_loss: 0.5899 - val_accuracy: 0.8251
Epoch 30/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6393 - accuracy: 0.8331 - val_loss: 0.5872 - val_accuracy: 0.8251
Epoch 31/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6336 - accuracy: 0.8427 - val_loss: 0.5843 - val_accuracy: 0.8251
Epoch 32/100
2/2 [==============================] - 0s 54ms/step - loss: 0.6353 - accuracy: 0.8358 - val_loss: 0.5816 - val_accuracy: 0.8306
Epoch 33/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6278 - accuracy: 0.8399 - val_loss: 0.5788 - val_accuracy: 0.8306
Epoch 34/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6285 - accuracy: 0.8331 - val_loss: 0.5755 - val_accuracy: 0.8361
Epoch 35/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6687 - accuracy: 0.8140 - val_loss: 0.5727 - val_accuracy: 0.8361
Epoch 36/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6414 - accuracy: 0.8194 - val_loss: 0.5695 - val_accuracy: 0.8361
Epoch 37/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6197 - accuracy: 0.8276 - val_loss: 0.5663 - val_accuracy: 0.8361
Epoch 38/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6290 - accuracy: 0.8263 - val_loss: 0.5642 - val_accuracy: 0.8306
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5969 - accuracy: 0.8468 - val_loss: 0.5623 - val_accuracy: 0.8306
Epoch 40/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5959 - accuracy: 0.8372 - val_loss: 0.5597 - val_accuracy: 0.8306
Epoch 41/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6094 - accuracy: 0.8276 - val_loss: 0.5575 - val_accuracy: 0.8306
Epoch 42/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6153 - accuracy: 0.8427 - val_loss: 0.5548 - val_accuracy: 0.8306
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5905 - accuracy: 0.8304 - val_loss: 0.5523 - val_accuracy: 0.8361
Epoch 44/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6000 - accuracy: 0.8345 - val_loss: 0.5507 - val_accuracy: 0.8361
Epoch 45/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5941 - accuracy: 0.8331 - val_loss: 0.5488 - val_accuracy: 0.8361
Epoch 46/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5844 - accuracy: 0.8304 - val_loss: 0.5470 - val_accuracy: 0.8361
Epoch 47/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5873 - accuracy: 0.8386 - val_loss: 0.5445 - val_accuracy: 0.8361
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5667 - accuracy: 0.8413 - val_loss: 0.5429 - val_accuracy: 0.8306
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5818 - accuracy: 0.8495 - val_loss: 0.5402 - val_accuracy: 0.8306
Epoch 50/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5794 - accuracy: 0.8427 - val_loss: 0.5382 - val_accuracy: 0.8251
Epoch 51/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5800 - accuracy: 0.8468 - val_loss: 0.5368 - val_accuracy: 0.8251
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5452 - accuracy: 0.8482 - val_loss: 0.5354 - val_accuracy: 0.8251
Epoch 53/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5502 - accuracy: 0.8482 - val_loss: 0.5337 - val_accuracy: 0.8251
Epoch 54/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5531 - accuracy: 0.8468 - val_loss: 0.5325 - val_accuracy: 0.8251
Epoch 55/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5358 - accuracy: 0.8618 - val_loss: 0.5314 - val_accuracy: 0.8251
Epoch 56/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5372 - accuracy: 0.8564 - val_loss: 0.5297 - val_accuracy: 0.8251
Epoch 57/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5604 - accuracy: 0.8577 - val_loss: 0.5278 - val_accuracy: 0.8251
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5486 - accuracy: 0.8427 - val_loss: 0.5264 - val_accuracy: 0.8251
Epoch 59/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5353 - accuracy: 0.8577 - val_loss: 0.5251 - val_accuracy: 0.8251
Epoch 60/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5090 - accuracy: 0.8577 - val_loss: 0.5238 - val_accuracy: 0.8251
Epoch 61/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5226 - accuracy: 0.8509 - val_loss: 0.5225 - val_accuracy: 0.8251
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5397 - accuracy: 0.8454 - val_loss: 0.5210 - val_accuracy: 0.8251
Epoch 63/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5512 - accuracy: 0.8509 - val_loss: 0.5199 - val_accuracy: 0.8251
Epoch 64/100
2/2 [==============================] - 0s 29ms/step - loss: 0.5503 - accuracy: 0.8605 - val_loss: 0.5188 - val_accuracy: 0.8306
Epoch 65/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5032 - accuracy: 0.8659 - val_loss: 0.5174 - val_accuracy: 0.8251
Epoch 66/100
2/2 [==============================] - 0s 50ms/step - loss: 0.5326 - accuracy: 0.8536 - val_loss: 0.5164 - val_accuracy: 0.8306
Epoch 67/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5184 - accuracy: 0.8550 - val_loss: 0.5151 - val_accuracy: 0.8251
Epoch 68/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5213 - accuracy: 0.8577 - val_loss: 0.5146 - val_accuracy: 0.8306
Epoch 69/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5382 - accuracy: 0.8523 - val_loss: 0.5133 - val_accuracy: 0.8306
Epoch 70/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5372 - accuracy: 0.8509 - val_loss: 0.5122 - val_accuracy: 0.8251
Epoch 71/100
2/2 [==============================] - 0s 51ms/step - loss: 0.4972 - accuracy: 0.8591 - val_loss: 0.5107 - val_accuracy: 0.8306
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5202 - accuracy: 0.8577 - val_loss: 0.5093 - val_accuracy: 0.8306
Epoch 73/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5337 - accuracy: 0.8536 - val_loss: 0.5079 - val_accuracy: 0.8306
Epoch 74/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5296 - accuracy: 0.8605 - val_loss: 0.5062 - val_accuracy: 0.8306
Epoch 75/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5106 - accuracy: 0.8509 - val_loss: 0.5046 - val_accuracy: 0.8306
Epoch 76/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5135 - accuracy: 0.8495 - val_loss: 0.5042 - val_accuracy: 0.8306
Epoch 77/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5022 - accuracy: 0.8577 - val_loss: 0.5037 - val_accuracy: 0.8306
Epoch 78/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5149 - accuracy: 0.8632 - val_loss: 0.5028 - val_accuracy: 0.8306
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5079 - accuracy: 0.8564 - val_loss: 0.5024 - val_accuracy: 0.8306
Epoch 80/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5020 - accuracy: 0.8591 - val_loss: 0.5016 - val_accuracy: 0.8306
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4939 - accuracy: 0.8591 - val_loss: 0.5014 - val_accuracy: 0.8306
Epoch 82/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5158 - accuracy: 0.8482 - val_loss: 0.5007 - val_accuracy: 0.8306
Epoch 83/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5079 - accuracy: 0.8536 - val_loss: 0.4999 - val_accuracy: 0.8306
Epoch 84/100
2/2 [==============================] - 0s 50ms/step - loss: 0.4893 - accuracy: 0.8591 - val_loss: 0.4988 - val_accuracy: 0.8306
Epoch 85/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4800 - accuracy: 0.8810 - val_loss: 0.4977 - val_accuracy: 0.8306
Epoch 86/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4853 - accuracy: 0.8632 - val_loss: 0.4961 - val_accuracy: 0.8306
Epoch 87/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4950 - accuracy: 0.8673 - val_loss: 0.4948 - val_accuracy: 0.8306
Epoch 88/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4834 - accuracy: 0.8605 - val_loss: 0.4943 - val_accuracy: 0.8306
Epoch 89/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5172 - accuracy: 0.8632 - val_loss: 0.4930 - val_accuracy: 0.8306
Epoch 90/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4906 - accuracy: 0.8673 - val_loss: 0.4921 - val_accuracy: 0.8306
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4995 - accuracy: 0.8659 - val_loss: 0.4901 - val_accuracy: 0.8251
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4863 - accuracy: 0.8618 - val_loss: 0.4892 - val_accuracy: 0.8251
Epoch 93/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5035 - accuracy: 0.8591 - val_loss: 0.4884 - val_accuracy: 0.8306
Epoch 94/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5001 - accuracy: 0.8413 - val_loss: 0.4873 - val_accuracy: 0.8251
Epoch 95/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4779 - accuracy: 0.8591 - val_loss: 0.4872 - val_accuracy: 0.8251
Epoch 96/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4792 - accuracy: 0.8687 - val_loss: 0.4868 - val_accuracy: 0.8251
Epoch 97/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4629 - accuracy: 0.8687 - val_loss: 0.4865 - val_accuracy: 0.8306
Epoch 98/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4944 - accuracy: 0.8673 - val_loss: 0.4855 - val_accuracy: 0.8306
Epoch 99/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4890 - accuracy: 0.8673 - val_loss: 0.4844 - val_accuracy: 0.8306
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4888 - accuracy: 0.8618 - val_loss: 0.4833 - val_accuracy: 0.8306
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 220ms/step - loss: 1.3813 - accuracy: 0.3912 - val_loss: 0.9899 - val_accuracy: 0.5792
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1547 - accuracy: 0.4897 - val_loss: 0.9001 - val_accuracy: 0.6448
Epoch 3/100
2/2 [==============================] - 0s 43ms/step - loss: 1.1104 - accuracy: 0.5212 - val_loss: 0.8342 - val_accuracy: 0.6776
Epoch 4/100
2/2 [==============================] - 0s 44ms/step - loss: 1.0063 - accuracy: 0.5663 - val_loss: 0.7858 - val_accuracy: 0.6995
Epoch 5/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9743 - accuracy: 0.5978 - val_loss: 0.7461 - val_accuracy: 0.7268
Epoch 6/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9531 - accuracy: 0.5964 - val_loss: 0.7126 - val_accuracy: 0.7596
Epoch 7/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9156 - accuracy: 0.6197 - val_loss: 0.6864 - val_accuracy: 0.7760
Epoch 8/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8744 - accuracy: 0.6211 - val_loss: 0.6627 - val_accuracy: 0.7869
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8270 - accuracy: 0.6457 - val_loss: 0.6412 - val_accuracy: 0.7814
Epoch 10/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7906 - accuracy: 0.6799 - val_loss: 0.6229 - val_accuracy: 0.7869
Epoch 11/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7903 - accuracy: 0.6785 - val_loss: 0.6065 - val_accuracy: 0.7978
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7910 - accuracy: 0.6922 - val_loss: 0.5919 - val_accuracy: 0.8033
Epoch 13/100
2/2 [==============================] - 0s 46ms/step - loss: 0.7778 - accuracy: 0.6881 - val_loss: 0.5787 - val_accuracy: 0.8087
Epoch 14/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7580 - accuracy: 0.7209 - val_loss: 0.5673 - val_accuracy: 0.8087
Epoch 15/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7337 - accuracy: 0.7319 - val_loss: 0.5566 - val_accuracy: 0.8087
Epoch 16/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7457 - accuracy: 0.7073 - val_loss: 0.5466 - val_accuracy: 0.8142
Epoch 17/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6991 - accuracy: 0.7415 - val_loss: 0.5368 - val_accuracy: 0.8142
Epoch 18/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6951 - accuracy: 0.7264 - val_loss: 0.5286 - val_accuracy: 0.8197
Epoch 19/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6995 - accuracy: 0.7360 - val_loss: 0.5205 - val_accuracy: 0.8306
Epoch 20/100
2/2 [==============================] - 0s 52ms/step - loss: 0.6653 - accuracy: 0.7428 - val_loss: 0.5127 - val_accuracy: 0.8306
Epoch 21/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6686 - accuracy: 0.7620 - val_loss: 0.5059 - val_accuracy: 0.8361
Epoch 22/100
2/2 [==============================] - 0s 44ms/step - loss: 0.6810 - accuracy: 0.7647 - val_loss: 0.4997 - val_accuracy: 0.8470
Epoch 23/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6391 - accuracy: 0.7798 - val_loss: 0.4933 - val_accuracy: 0.8525
Epoch 24/100
2/2 [==============================] - 0s 27ms/step - loss: 0.6441 - accuracy: 0.7798 - val_loss: 0.4876 - val_accuracy: 0.8525
Epoch 25/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6392 - accuracy: 0.7880 - val_loss: 0.4820 - val_accuracy: 0.8579
Epoch 26/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6302 - accuracy: 0.7798 - val_loss: 0.4772 - val_accuracy: 0.8689
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6541 - accuracy: 0.7825 - val_loss: 0.4731 - val_accuracy: 0.8743
Epoch 28/100
2/2 [==============================] - 0s 46ms/step - loss: 0.6142 - accuracy: 0.8016 - val_loss: 0.4686 - val_accuracy: 0.8852
Epoch 29/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6115 - accuracy: 0.7866 - val_loss: 0.4640 - val_accuracy: 0.8798
Epoch 30/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6194 - accuracy: 0.7825 - val_loss: 0.4597 - val_accuracy: 0.8907
Epoch 31/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6131 - accuracy: 0.7962 - val_loss: 0.4558 - val_accuracy: 0.8962
Epoch 32/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6142 - accuracy: 0.7907 - val_loss: 0.4521 - val_accuracy: 0.8962
Epoch 33/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5748 - accuracy: 0.8003 - val_loss: 0.4490 - val_accuracy: 0.8962
Epoch 34/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5850 - accuracy: 0.7975 - val_loss: 0.4458 - val_accuracy: 0.8962
Epoch 35/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5869 - accuracy: 0.8003 - val_loss: 0.4424 - val_accuracy: 0.8962
Epoch 36/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5924 - accuracy: 0.8112 - val_loss: 0.4399 - val_accuracy: 0.9016
Epoch 37/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5841 - accuracy: 0.8085 - val_loss: 0.4371 - val_accuracy: 0.8907
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5790 - accuracy: 0.8304 - val_loss: 0.4346 - val_accuracy: 0.8907
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5896 - accuracy: 0.8126 - val_loss: 0.4322 - val_accuracy: 0.8962
Epoch 40/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5821 - accuracy: 0.8208 - val_loss: 0.4303 - val_accuracy: 0.8962
Epoch 41/100
2/2 [==============================] - 0s 51ms/step - loss: 0.5575 - accuracy: 0.8194 - val_loss: 0.4280 - val_accuracy: 0.8907
Epoch 42/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5459 - accuracy: 0.8331 - val_loss: 0.4257 - val_accuracy: 0.8962
Epoch 43/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5545 - accuracy: 0.8331 - val_loss: 0.4234 - val_accuracy: 0.8962
Epoch 44/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5476 - accuracy: 0.8345 - val_loss: 0.4215 - val_accuracy: 0.8962
Epoch 45/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5462 - accuracy: 0.8304 - val_loss: 0.4195 - val_accuracy: 0.8962
Epoch 46/100
2/2 [==============================] - 0s 27ms/step - loss: 0.5463 - accuracy: 0.8372 - val_loss: 0.4176 - val_accuracy: 0.8962
Epoch 47/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5463 - accuracy: 0.8440 - val_loss: 0.4160 - val_accuracy: 0.8962
Epoch 48/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5487 - accuracy: 0.8358 - val_loss: 0.4146 - val_accuracy: 0.8962
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5452 - accuracy: 0.8372 - val_loss: 0.4130 - val_accuracy: 0.8962
Epoch 50/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5382 - accuracy: 0.8386 - val_loss: 0.4116 - val_accuracy: 0.8907
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5339 - accuracy: 0.8290 - val_loss: 0.4100 - val_accuracy: 0.8907
Epoch 52/100
2/2 [==============================] - 0s 28ms/step - loss: 0.5317 - accuracy: 0.8454 - val_loss: 0.4086 - val_accuracy: 0.8907
Epoch 53/100
2/2 [==============================] - 0s 63ms/step - loss: 0.5463 - accuracy: 0.8331 - val_loss: 0.4079 - val_accuracy: 0.8852
Epoch 54/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5316 - accuracy: 0.8564 - val_loss: 0.4067 - val_accuracy: 0.8907
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5433 - accuracy: 0.8345 - val_loss: 0.4056 - val_accuracy: 0.8907
Epoch 56/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5375 - accuracy: 0.8372 - val_loss: 0.4047 - val_accuracy: 0.8907
Epoch 57/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5443 - accuracy: 0.8399 - val_loss: 0.4041 - val_accuracy: 0.8798
Epoch 58/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5000 - accuracy: 0.8550 - val_loss: 0.4032 - val_accuracy: 0.8798
Epoch 59/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5303 - accuracy: 0.8249 - val_loss: 0.4023 - val_accuracy: 0.8798
Epoch 60/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5265 - accuracy: 0.8509 - val_loss: 0.4014 - val_accuracy: 0.8798
Epoch 61/100
2/2 [==============================] - 0s 61ms/step - loss: 0.4978 - accuracy: 0.8454 - val_loss: 0.4004 - val_accuracy: 0.8798
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5248 - accuracy: 0.8468 - val_loss: 0.3996 - val_accuracy: 0.8798
Epoch 63/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5093 - accuracy: 0.8509 - val_loss: 0.3990 - val_accuracy: 0.8798
Epoch 64/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5051 - accuracy: 0.8427 - val_loss: 0.3979 - val_accuracy: 0.8798
Epoch 65/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5047 - accuracy: 0.8454 - val_loss: 0.3972 - val_accuracy: 0.8798
Epoch 66/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5192 - accuracy: 0.8536 - val_loss: 0.3968 - val_accuracy: 0.8852
Epoch 67/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4979 - accuracy: 0.8468 - val_loss: 0.3960 - val_accuracy: 0.8798
Epoch 68/100
2/2 [==============================] - 0s 74ms/step - loss: 0.4962 - accuracy: 0.8509 - val_loss: 0.3955 - val_accuracy: 0.8798
Epoch 69/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5261 - accuracy: 0.8440 - val_loss: 0.3953 - val_accuracy: 0.8852
Epoch 70/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4896 - accuracy: 0.8454 - val_loss: 0.3949 - val_accuracy: 0.8852
Epoch 71/100
2/2 [==============================] - 0s 52ms/step - loss: 0.4959 - accuracy: 0.8577 - val_loss: 0.3943 - val_accuracy: 0.8852
Epoch 72/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4822 - accuracy: 0.8523 - val_loss: 0.3936 - val_accuracy: 0.8852
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4956 - accuracy: 0.8536 - val_loss: 0.3930 - val_accuracy: 0.8852
Epoch 74/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5018 - accuracy: 0.8536 - val_loss: 0.3927 - val_accuracy: 0.8852
Epoch 75/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4862 - accuracy: 0.8427 - val_loss: 0.3920 - val_accuracy: 0.8852
Epoch 76/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4883 - accuracy: 0.8482 - val_loss: 0.3912 - val_accuracy: 0.8852
Epoch 77/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4763 - accuracy: 0.8564 - val_loss: 0.3907 - val_accuracy: 0.8852
Epoch 78/100
2/2 [==============================] - 0s 28ms/step - loss: 0.4975 - accuracy: 0.8427 - val_loss: 0.3904 - val_accuracy: 0.8852
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4913 - accuracy: 0.8550 - val_loss: 0.3903 - val_accuracy: 0.8852
Epoch 80/100
2/2 [==============================] - 0s 29ms/step - loss: 0.4936 - accuracy: 0.8427 - val_loss: 0.3900 - val_accuracy: 0.8852
Epoch 81/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4954 - accuracy: 0.8536 - val_loss: 0.3901 - val_accuracy: 0.8852
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4737 - accuracy: 0.8523 - val_loss: 0.3899 - val_accuracy: 0.8852
Epoch 83/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4562 - accuracy: 0.8659 - val_loss: 0.3897 - val_accuracy: 0.8852
Epoch 84/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4835 - accuracy: 0.8372 - val_loss: 0.3898 - val_accuracy: 0.8852
Epoch 85/100
2/2 [==============================] - 0s 44ms/step - loss: 0.4752 - accuracy: 0.8687 - val_loss: 0.3893 - val_accuracy: 0.8852
Epoch 86/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4675 - accuracy: 0.8509 - val_loss: 0.3892 - val_accuracy: 0.8852
Epoch 87/100
2/2 [==============================] - 0s 45ms/step - loss: 0.4730 - accuracy: 0.8564 - val_loss: 0.3886 - val_accuracy: 0.8852
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5067 - accuracy: 0.8495 - val_loss: 0.3883 - val_accuracy: 0.8852
Epoch 89/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4869 - accuracy: 0.8536 - val_loss: 0.3875 - val_accuracy: 0.8852
Epoch 90/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4750 - accuracy: 0.8427 - val_loss: 0.3874 - val_accuracy: 0.8852
Epoch 91/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4619 - accuracy: 0.8605 - val_loss: 0.3871 - val_accuracy: 0.8852
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4790 - accuracy: 0.8523 - val_loss: 0.3869 - val_accuracy: 0.8852
Epoch 93/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4670 - accuracy: 0.8468 - val_loss: 0.3866 - val_accuracy: 0.8852
Epoch 94/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4765 - accuracy: 0.8482 - val_loss: 0.3859 - val_accuracy: 0.8852
Epoch 95/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4836 - accuracy: 0.8440 - val_loss: 0.3857 - val_accuracy: 0.8852
Epoch 96/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4680 - accuracy: 0.8564 - val_loss: 0.3853 - val_accuracy: 0.8852
Epoch 97/100
2/2 [==============================] - 0s 29ms/step - loss: 0.4584 - accuracy: 0.8618 - val_loss: 0.3845 - val_accuracy: 0.8852
Epoch 98/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4623 - accuracy: 0.8523 - val_loss: 0.3840 - val_accuracy: 0.8852
Epoch 99/100
2/2 [==============================] - 0s 51ms/step - loss: 0.4819 - accuracy: 0.8482 - val_loss: 0.3841 - val_accuracy: 0.8852
Epoch 100/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4613 - accuracy: 0.8536 - val_loss: 0.3841 - val_accuracy: 0.8852
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 216ms/step - loss: 1.3043 - accuracy: 0.4501 - val_loss: 0.9538 - val_accuracy: 0.5738
Epoch 2/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1351 - accuracy: 0.4884 - val_loss: 0.8789 - val_accuracy: 0.6175
Epoch 3/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0371 - accuracy: 0.5280 - val_loss: 0.8257 - val_accuracy: 0.6721
Epoch 4/100
2/2 [==============================] - 0s 34ms/step - loss: 1.0236 - accuracy: 0.5636 - val_loss: 0.7830 - val_accuracy: 0.6940
Epoch 5/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9315 - accuracy: 0.6033 - val_loss: 0.7493 - val_accuracy: 0.7213
Epoch 6/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8640 - accuracy: 0.6607 - val_loss: 0.7227 - val_accuracy: 0.7377
Epoch 7/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8488 - accuracy: 0.6457 - val_loss: 0.7010 - val_accuracy: 0.7377
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8375 - accuracy: 0.6799 - val_loss: 0.6830 - val_accuracy: 0.7486
Epoch 9/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8133 - accuracy: 0.6772 - val_loss: 0.6663 - val_accuracy: 0.7541
Epoch 10/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8058 - accuracy: 0.6717 - val_loss: 0.6514 - val_accuracy: 0.7541
Epoch 11/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7814 - accuracy: 0.6963 - val_loss: 0.6380 - val_accuracy: 0.7705
Epoch 12/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7349 - accuracy: 0.7237 - val_loss: 0.6272 - val_accuracy: 0.8033
Epoch 13/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7089 - accuracy: 0.7469 - val_loss: 0.6167 - val_accuracy: 0.8033
Epoch 14/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7280 - accuracy: 0.7332 - val_loss: 0.6066 - val_accuracy: 0.8251
Epoch 15/100
2/2 [==============================] - 0s 45ms/step - loss: 0.7134 - accuracy: 0.7319 - val_loss: 0.5975 - val_accuracy: 0.8306
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6652 - accuracy: 0.7497 - val_loss: 0.5907 - val_accuracy: 0.8306
Epoch 17/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6902 - accuracy: 0.7428 - val_loss: 0.5828 - val_accuracy: 0.8361
Epoch 18/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6868 - accuracy: 0.7524 - val_loss: 0.5758 - val_accuracy: 0.8361
Epoch 19/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6641 - accuracy: 0.7729 - val_loss: 0.5693 - val_accuracy: 0.8470
Epoch 20/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6394 - accuracy: 0.7825 - val_loss: 0.5632 - val_accuracy: 0.8470
Epoch 21/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6490 - accuracy: 0.7921 - val_loss: 0.5574 - val_accuracy: 0.8470
Epoch 22/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6260 - accuracy: 0.7756 - val_loss: 0.5521 - val_accuracy: 0.8470
Epoch 23/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6278 - accuracy: 0.7852 - val_loss: 0.5472 - val_accuracy: 0.8470
Epoch 24/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6368 - accuracy: 0.7989 - val_loss: 0.5427 - val_accuracy: 0.8470
Epoch 25/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6570 - accuracy: 0.7839 - val_loss: 0.5383 - val_accuracy: 0.8470
Epoch 26/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6448 - accuracy: 0.7798 - val_loss: 0.5340 - val_accuracy: 0.8470
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6323 - accuracy: 0.7934 - val_loss: 0.5293 - val_accuracy: 0.8470
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5947 - accuracy: 0.8044 - val_loss: 0.5252 - val_accuracy: 0.8470
Epoch 29/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6189 - accuracy: 0.7866 - val_loss: 0.5215 - val_accuracy: 0.8470
Epoch 30/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5984 - accuracy: 0.8153 - val_loss: 0.5179 - val_accuracy: 0.8470
Epoch 31/100
2/2 [==============================] - 0s 29ms/step - loss: 0.6060 - accuracy: 0.8003 - val_loss: 0.5147 - val_accuracy: 0.8525
Epoch 32/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5904 - accuracy: 0.8317 - val_loss: 0.5115 - val_accuracy: 0.8525
Epoch 33/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5913 - accuracy: 0.8208 - val_loss: 0.5086 - val_accuracy: 0.8525
Epoch 34/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5792 - accuracy: 0.8249 - val_loss: 0.5062 - val_accuracy: 0.8525
Epoch 35/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5601 - accuracy: 0.8235 - val_loss: 0.5036 - val_accuracy: 0.8525
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5936 - accuracy: 0.8194 - val_loss: 0.5010 - val_accuracy: 0.8525
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5723 - accuracy: 0.8153 - val_loss: 0.4986 - val_accuracy: 0.8525
Epoch 38/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5571 - accuracy: 0.8235 - val_loss: 0.4967 - val_accuracy: 0.8525
Epoch 39/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5686 - accuracy: 0.8263 - val_loss: 0.4948 - val_accuracy: 0.8525
Epoch 40/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5632 - accuracy: 0.8263 - val_loss: 0.4922 - val_accuracy: 0.8525
Epoch 41/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5269 - accuracy: 0.8482 - val_loss: 0.4898 - val_accuracy: 0.8579
Epoch 42/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5585 - accuracy: 0.8208 - val_loss: 0.4877 - val_accuracy: 0.8579
Epoch 43/100
2/2 [==============================] - 0s 30ms/step - loss: 0.5227 - accuracy: 0.8249 - val_loss: 0.4857 - val_accuracy: 0.8579
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5090 - accuracy: 0.8454 - val_loss: 0.4839 - val_accuracy: 0.8525
Epoch 45/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5262 - accuracy: 0.8509 - val_loss: 0.4820 - val_accuracy: 0.8579
Epoch 46/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5309 - accuracy: 0.8372 - val_loss: 0.4806 - val_accuracy: 0.8579
Epoch 47/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5311 - accuracy: 0.8413 - val_loss: 0.4788 - val_accuracy: 0.8579
Epoch 48/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5362 - accuracy: 0.8317 - val_loss: 0.4772 - val_accuracy: 0.8634
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5231 - accuracy: 0.8482 - val_loss: 0.4760 - val_accuracy: 0.8579
Epoch 50/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5562 - accuracy: 0.8140 - val_loss: 0.4749 - val_accuracy: 0.8525
Epoch 51/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5350 - accuracy: 0.8235 - val_loss: 0.4733 - val_accuracy: 0.8579
Epoch 52/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5179 - accuracy: 0.8399 - val_loss: 0.4720 - val_accuracy: 0.8579
Epoch 53/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5111 - accuracy: 0.8317 - val_loss: 0.4705 - val_accuracy: 0.8579
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5129 - accuracy: 0.8372 - val_loss: 0.4698 - val_accuracy: 0.8579
Epoch 55/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5044 - accuracy: 0.8468 - val_loss: 0.4688 - val_accuracy: 0.8579
Epoch 56/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5064 - accuracy: 0.8454 - val_loss: 0.4674 - val_accuracy: 0.8579
Epoch 57/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5109 - accuracy: 0.8413 - val_loss: 0.4665 - val_accuracy: 0.8634
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5058 - accuracy: 0.8509 - val_loss: 0.4656 - val_accuracy: 0.8579
Epoch 59/100
2/2 [==============================] - 0s 46ms/step - loss: 0.4808 - accuracy: 0.8564 - val_loss: 0.4642 - val_accuracy: 0.8634
Epoch 60/100
2/2 [==============================] - 0s 30ms/step - loss: 0.4937 - accuracy: 0.8454 - val_loss: 0.4627 - val_accuracy: 0.8634
Epoch 61/100
2/2 [==============================] - 0s 44ms/step - loss: 0.4968 - accuracy: 0.8536 - val_loss: 0.4617 - val_accuracy: 0.8634
Epoch 62/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4790 - accuracy: 0.8536 - val_loss: 0.4608 - val_accuracy: 0.8634
Epoch 63/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5009 - accuracy: 0.8345 - val_loss: 0.4597 - val_accuracy: 0.8579
Epoch 64/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5040 - accuracy: 0.8509 - val_loss: 0.4587 - val_accuracy: 0.8525
Epoch 65/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4921 - accuracy: 0.8564 - val_loss: 0.4576 - val_accuracy: 0.8525
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5119 - accuracy: 0.8317 - val_loss: 0.4571 - val_accuracy: 0.8525
Epoch 67/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4778 - accuracy: 0.8536 - val_loss: 0.4563 - val_accuracy: 0.8525
Epoch 68/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4583 - accuracy: 0.8687 - val_loss: 0.4554 - val_accuracy: 0.8525
Epoch 69/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4789 - accuracy: 0.8536 - val_loss: 0.4545 - val_accuracy: 0.8579
Epoch 70/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4796 - accuracy: 0.8618 - val_loss: 0.4535 - val_accuracy: 0.8579
Epoch 71/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4826 - accuracy: 0.8386 - val_loss: 0.4530 - val_accuracy: 0.8634
Epoch 72/100
2/2 [==============================] - 0s 27ms/step - loss: 0.4857 - accuracy: 0.8550 - val_loss: 0.4521 - val_accuracy: 0.8634
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4622 - accuracy: 0.8440 - val_loss: 0.4511 - val_accuracy: 0.8689
Epoch 74/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4811 - accuracy: 0.8523 - val_loss: 0.4502 - val_accuracy: 0.8634
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4862 - accuracy: 0.8509 - val_loss: 0.4493 - val_accuracy: 0.8634
Epoch 76/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4954 - accuracy: 0.8399 - val_loss: 0.4493 - val_accuracy: 0.8579
Epoch 77/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4878 - accuracy: 0.8646 - val_loss: 0.4489 - val_accuracy: 0.8579
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4841 - accuracy: 0.8536 - val_loss: 0.4482 - val_accuracy: 0.8579
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4649 - accuracy: 0.8591 - val_loss: 0.4472 - val_accuracy: 0.8634
Epoch 80/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4679 - accuracy: 0.8482 - val_loss: 0.4459 - val_accuracy: 0.8634
Epoch 81/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4694 - accuracy: 0.8523 - val_loss: 0.4453 - val_accuracy: 0.8634
Epoch 82/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4674 - accuracy: 0.8591 - val_loss: 0.4444 - val_accuracy: 0.8579
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4432 - accuracy: 0.8646 - val_loss: 0.4435 - val_accuracy: 0.8634
Epoch 84/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4629 - accuracy: 0.8564 - val_loss: 0.4426 - val_accuracy: 0.8634
Epoch 85/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4613 - accuracy: 0.8454 - val_loss: 0.4419 - val_accuracy: 0.8634
Epoch 86/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4809 - accuracy: 0.8509 - val_loss: 0.4409 - val_accuracy: 0.8634
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4335 - accuracy: 0.8646 - val_loss: 0.4404 - val_accuracy: 0.8579
Epoch 88/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4752 - accuracy: 0.8536 - val_loss: 0.4395 - val_accuracy: 0.8634
Epoch 89/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4643 - accuracy: 0.8399 - val_loss: 0.4394 - val_accuracy: 0.8634
Epoch 90/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4458 - accuracy: 0.8646 - val_loss: 0.4388 - val_accuracy: 0.8579
Epoch 91/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4404 - accuracy: 0.8687 - val_loss: 0.4384 - val_accuracy: 0.8579
Epoch 92/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4423 - accuracy: 0.8591 - val_loss: 0.4378 - val_accuracy: 0.8579
Epoch 93/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4545 - accuracy: 0.8564 - val_loss: 0.4371 - val_accuracy: 0.8634
Epoch 94/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4670 - accuracy: 0.8564 - val_loss: 0.4365 - val_accuracy: 0.8579
Epoch 95/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4533 - accuracy: 0.8755 - val_loss: 0.4359 - val_accuracy: 0.8579
Epoch 96/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4384 - accuracy: 0.8523 - val_loss: 0.4358 - val_accuracy: 0.8579
Epoch 97/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4520 - accuracy: 0.8591 - val_loss: 0.4351 - val_accuracy: 0.8579
Epoch 98/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4515 - accuracy: 0.8454 - val_loss: 0.4344 - val_accuracy: 0.8579
Epoch 99/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4517 - accuracy: 0.8714 - val_loss: 0.4340 - val_accuracy: 0.8579
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4644 - accuracy: 0.8509 - val_loss: 0.4337 - val_accuracy: 0.8579
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
2/2 [==============================] - 1s 215ms/step - loss: 1.5105 - accuracy: 0.2668 - val_loss: 1.1477 - val_accuracy: 0.4426
Epoch 2/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3468 - accuracy: 0.3502 - val_loss: 1.0532 - val_accuracy: 0.5191
Epoch 3/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2589 - accuracy: 0.4036 - val_loss: 0.9843 - val_accuracy: 0.5683
Epoch 4/100
2/2 [==============================] - 0s 35ms/step - loss: 1.1453 - accuracy: 0.4679 - val_loss: 0.9307 - val_accuracy: 0.6120
Epoch 5/100
2/2 [==============================] - 0s 50ms/step - loss: 1.1347 - accuracy: 0.4501 - val_loss: 0.8893 - val_accuracy: 0.6393
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0502 - accuracy: 0.5363 - val_loss: 0.8561 - val_accuracy: 0.6612
Epoch 7/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0019 - accuracy: 0.5622 - val_loss: 0.8267 - val_accuracy: 0.7158
Epoch 8/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9818 - accuracy: 0.6005 - val_loss: 0.8010 - val_accuracy: 0.7596
Epoch 9/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9868 - accuracy: 0.6197 - val_loss: 0.7782 - val_accuracy: 0.7869
Epoch 10/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9323 - accuracy: 0.6224 - val_loss: 0.7583 - val_accuracy: 0.7923
Epoch 11/100
2/2 [==============================] - 0s 55ms/step - loss: 0.9189 - accuracy: 0.6402 - val_loss: 0.7405 - val_accuracy: 0.8087
Epoch 12/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8843 - accuracy: 0.6717 - val_loss: 0.7248 - val_accuracy: 0.8142
Epoch 13/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8596 - accuracy: 0.6731 - val_loss: 0.7097 - val_accuracy: 0.8197
Epoch 14/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8434 - accuracy: 0.7018 - val_loss: 0.6966 - val_accuracy: 0.8251
Epoch 15/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8232 - accuracy: 0.7155 - val_loss: 0.6828 - val_accuracy: 0.8361
Epoch 16/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8275 - accuracy: 0.7073 - val_loss: 0.6704 - val_accuracy: 0.8579
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8091 - accuracy: 0.7237 - val_loss: 0.6590 - val_accuracy: 0.8634
Epoch 18/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7640 - accuracy: 0.7524 - val_loss: 0.6499 - val_accuracy: 0.8689
Epoch 19/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7714 - accuracy: 0.7469 - val_loss: 0.6410 - val_accuracy: 0.8689
Epoch 20/100
2/2 [==============================] - 0s 29ms/step - loss: 0.7596 - accuracy: 0.7524 - val_loss: 0.6317 - val_accuracy: 0.8689
Epoch 21/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7401 - accuracy: 0.7756 - val_loss: 0.6236 - val_accuracy: 0.8689
Epoch 22/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7136 - accuracy: 0.7688 - val_loss: 0.6144 - val_accuracy: 0.8689
Epoch 23/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7298 - accuracy: 0.7756 - val_loss: 0.6061 - val_accuracy: 0.8689
Epoch 24/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7238 - accuracy: 0.7770 - val_loss: 0.5983 - val_accuracy: 0.8689
Epoch 25/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7188 - accuracy: 0.7880 - val_loss: 0.5913 - val_accuracy: 0.8743
Epoch 26/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7036 - accuracy: 0.7948 - val_loss: 0.5837 - val_accuracy: 0.8689
Epoch 27/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7006 - accuracy: 0.7907 - val_loss: 0.5771 - val_accuracy: 0.8743
Epoch 28/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6725 - accuracy: 0.8003 - val_loss: 0.5712 - val_accuracy: 0.8743
Epoch 29/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6786 - accuracy: 0.7962 - val_loss: 0.5663 - val_accuracy: 0.8798
Epoch 30/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6506 - accuracy: 0.8222 - val_loss: 0.5605 - val_accuracy: 0.8798
Epoch 31/100
2/2 [==============================] - 0s 26ms/step - loss: 0.6645 - accuracy: 0.8098 - val_loss: 0.5556 - val_accuracy: 0.8798
Epoch 32/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6069 - accuracy: 0.8249 - val_loss: 0.5509 - val_accuracy: 0.8852
Epoch 33/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6360 - accuracy: 0.8003 - val_loss: 0.5464 - val_accuracy: 0.8852
Epoch 34/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6275 - accuracy: 0.8263 - val_loss: 0.5423 - val_accuracy: 0.8852
Epoch 35/100
2/2 [==============================] - 0s 45ms/step - loss: 0.6235 - accuracy: 0.8345 - val_loss: 0.5372 - val_accuracy: 0.8852
Epoch 36/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6109 - accuracy: 0.8399 - val_loss: 0.5328 - val_accuracy: 0.8852
Epoch 37/100
2/2 [==============================] - 0s 45ms/step - loss: 0.6171 - accuracy: 0.8317 - val_loss: 0.5291 - val_accuracy: 0.8852
Epoch 38/100
2/2 [==============================] - 0s 59ms/step - loss: 0.6147 - accuracy: 0.8235 - val_loss: 0.5253 - val_accuracy: 0.8852
Epoch 39/100
2/2 [==============================] - 0s 51ms/step - loss: 0.6274 - accuracy: 0.8317 - val_loss: 0.5227 - val_accuracy: 0.8852
Epoch 40/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6078 - accuracy: 0.8304 - val_loss: 0.5190 - val_accuracy: 0.8852
Epoch 41/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6018 - accuracy: 0.8372 - val_loss: 0.5153 - val_accuracy: 0.8852
Epoch 42/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6011 - accuracy: 0.8317 - val_loss: 0.5121 - val_accuracy: 0.8852
Epoch 43/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6047 - accuracy: 0.8427 - val_loss: 0.5078 - val_accuracy: 0.8852
Epoch 44/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5991 - accuracy: 0.8413 - val_loss: 0.5057 - val_accuracy: 0.8852
Epoch 45/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5779 - accuracy: 0.8509 - val_loss: 0.5029 - val_accuracy: 0.8852
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5824 - accuracy: 0.8550 - val_loss: 0.4998 - val_accuracy: 0.8852
Epoch 47/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5577 - accuracy: 0.8495 - val_loss: 0.4971 - val_accuracy: 0.8798
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5715 - accuracy: 0.8440 - val_loss: 0.4948 - val_accuracy: 0.8798
Epoch 49/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5728 - accuracy: 0.8468 - val_loss: 0.4921 - val_accuracy: 0.8798
Epoch 50/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5512 - accuracy: 0.8454 - val_loss: 0.4899 - val_accuracy: 0.8798
Epoch 51/100
2/2 [==============================] - 0s 61ms/step - loss: 0.5511 - accuracy: 0.8495 - val_loss: 0.4869 - val_accuracy: 0.8798
Epoch 52/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5500 - accuracy: 0.8468 - val_loss: 0.4848 - val_accuracy: 0.8798
Epoch 53/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5422 - accuracy: 0.8440 - val_loss: 0.4817 - val_accuracy: 0.8798
Epoch 54/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5679 - accuracy: 0.8482 - val_loss: 0.4790 - val_accuracy: 0.8798
Epoch 55/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5419 - accuracy: 0.8523 - val_loss: 0.4774 - val_accuracy: 0.8798
Epoch 56/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5620 - accuracy: 0.8468 - val_loss: 0.4764 - val_accuracy: 0.8798
Epoch 57/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5247 - accuracy: 0.8591 - val_loss: 0.4751 - val_accuracy: 0.8798
Epoch 58/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5406 - accuracy: 0.8577 - val_loss: 0.4730 - val_accuracy: 0.8798
Epoch 59/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5382 - accuracy: 0.8523 - val_loss: 0.4718 - val_accuracy: 0.8579
Epoch 60/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5408 - accuracy: 0.8468 - val_loss: 0.4694 - val_accuracy: 0.8798
Epoch 61/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5342 - accuracy: 0.8331 - val_loss: 0.4676 - val_accuracy: 0.8743
Epoch 62/100
2/2 [==============================] - 0s 27ms/step - loss: 0.5145 - accuracy: 0.8550 - val_loss: 0.4664 - val_accuracy: 0.8689
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5095 - accuracy: 0.8536 - val_loss: 0.4643 - val_accuracy: 0.8689
Epoch 64/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5308 - accuracy: 0.8386 - val_loss: 0.4629 - val_accuracy: 0.8689
Epoch 65/100
2/2 [==============================] - 0s 30ms/step - loss: 0.5132 - accuracy: 0.8564 - val_loss: 0.4613 - val_accuracy: 0.8689
Epoch 66/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5112 - accuracy: 0.8495 - val_loss: 0.4597 - val_accuracy: 0.8689
Epoch 67/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5097 - accuracy: 0.8618 - val_loss: 0.4581 - val_accuracy: 0.8689
Epoch 68/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5090 - accuracy: 0.8591 - val_loss: 0.4566 - val_accuracy: 0.8689
Epoch 69/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4910 - accuracy: 0.8673 - val_loss: 0.4558 - val_accuracy: 0.8634
Epoch 70/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4858 - accuracy: 0.8605 - val_loss: 0.4550 - val_accuracy: 0.8634
Epoch 71/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5014 - accuracy: 0.8714 - val_loss: 0.4532 - val_accuracy: 0.8634
Epoch 72/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5079 - accuracy: 0.8577 - val_loss: 0.4520 - val_accuracy: 0.8634
Epoch 73/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4907 - accuracy: 0.8536 - val_loss: 0.4512 - val_accuracy: 0.8634
Epoch 74/100
2/2 [==============================] - 0s 30ms/step - loss: 0.4851 - accuracy: 0.8536 - val_loss: 0.4495 - val_accuracy: 0.8634
Epoch 75/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4897 - accuracy: 0.8550 - val_loss: 0.4487 - val_accuracy: 0.8634
Epoch 76/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4848 - accuracy: 0.8646 - val_loss: 0.4472 - val_accuracy: 0.8634
Epoch 77/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4779 - accuracy: 0.8646 - val_loss: 0.4465 - val_accuracy: 0.8634
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4896 - accuracy: 0.8577 - val_loss: 0.4449 - val_accuracy: 0.8634
Epoch 79/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4783 - accuracy: 0.8728 - val_loss: 0.4444 - val_accuracy: 0.8634
Epoch 80/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4836 - accuracy: 0.8536 - val_loss: 0.4431 - val_accuracy: 0.8634
Epoch 81/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4792 - accuracy: 0.8659 - val_loss: 0.4425 - val_accuracy: 0.8634
Epoch 82/100
2/2 [==============================] - 0s 29ms/step - loss: 0.4985 - accuracy: 0.8591 - val_loss: 0.4415 - val_accuracy: 0.8634
Epoch 83/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4714 - accuracy: 0.8646 - val_loss: 0.4412 - val_accuracy: 0.8689
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4730 - accuracy: 0.8605 - val_loss: 0.4404 - val_accuracy: 0.8579
Epoch 85/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4863 - accuracy: 0.8591 - val_loss: 0.4395 - val_accuracy: 0.8689
Epoch 86/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4814 - accuracy: 0.8659 - val_loss: 0.4387 - val_accuracy: 0.8689
Epoch 87/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4858 - accuracy: 0.8605 - val_loss: 0.4382 - val_accuracy: 0.8689
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4824 - accuracy: 0.8605 - val_loss: 0.4385 - val_accuracy: 0.8689
Epoch 89/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4699 - accuracy: 0.8659 - val_loss: 0.4368 - val_accuracy: 0.8689
Epoch 90/100
2/2 [==============================] - 0s 44ms/step - loss: 0.4630 - accuracy: 0.8782 - val_loss: 0.4360 - val_accuracy: 0.8689
Epoch 91/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4516 - accuracy: 0.8618 - val_loss: 0.4354 - val_accuracy: 0.8689
Epoch 92/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4703 - accuracy: 0.8673 - val_loss: 0.4358 - val_accuracy: 0.8579
Epoch 93/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4545 - accuracy: 0.8714 - val_loss: 0.4350 - val_accuracy: 0.8525
Epoch 94/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4668 - accuracy: 0.8673 - val_loss: 0.4343 - val_accuracy: 0.8525
Epoch 95/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4749 - accuracy: 0.8605 - val_loss: 0.4341 - val_accuracy: 0.8525
Epoch 96/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4492 - accuracy: 0.8700 - val_loss: 0.4335 - val_accuracy: 0.8579
Epoch 97/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4518 - accuracy: 0.8632 - val_loss: 0.4329 - val_accuracy: 0.8579
Epoch 98/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4464 - accuracy: 0.8700 - val_loss: 0.4335 - val_accuracy: 0.8579
Epoch 99/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4596 - accuracy: 0.8673 - val_loss: 0.4332 - val_accuracy: 0.8579
Epoch 100/100
2/2 [==============================] - 0s 29ms/step - loss: 0.4350 - accuracy: 0.8769 - val_loss: 0.4321 - val_accuracy: 0.8579
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.99}
Batch size: 512
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
2/2 [==============================] - 1s 245ms/step - loss: 1.6885 - accuracy: 0.2527 - val_loss: 1.3705 - val_accuracy: 0.3022
Epoch 2/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4307 - accuracy: 0.3238 - val_loss: 1.2372 - val_accuracy: 0.3956
Epoch 3/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3529 - accuracy: 0.3484 - val_loss: 1.1509 - val_accuracy: 0.4505
Epoch 4/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2269 - accuracy: 0.4085 - val_loss: 1.0856 - val_accuracy: 0.4945
Epoch 5/100
2/2 [==============================] - 0s 46ms/step - loss: 1.1871 - accuracy: 0.4508 - val_loss: 1.0334 - val_accuracy: 0.5604
Epoch 6/100
2/2 [==============================] - 0s 32ms/step - loss: 1.1149 - accuracy: 0.4686 - val_loss: 0.9874 - val_accuracy: 0.5989
Epoch 7/100
2/2 [==============================] - 0s 46ms/step - loss: 1.0802 - accuracy: 0.5164 - val_loss: 0.9499 - val_accuracy: 0.6209
Epoch 8/100
2/2 [==============================] - 0s 45ms/step - loss: 1.0252 - accuracy: 0.5628 - val_loss: 0.9168 - val_accuracy: 0.6484
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0378 - accuracy: 0.5505 - val_loss: 0.8886 - val_accuracy: 0.6758
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0158 - accuracy: 0.5847 - val_loss: 0.8628 - val_accuracy: 0.6813
Epoch 11/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9626 - accuracy: 0.6025 - val_loss: 0.8402 - val_accuracy: 0.7033
Epoch 12/100
2/2 [==============================] - 0s 60ms/step - loss: 0.9296 - accuracy: 0.6339 - val_loss: 0.8215 - val_accuracy: 0.7143
Epoch 13/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9214 - accuracy: 0.6626 - val_loss: 0.8020 - val_accuracy: 0.7253
Epoch 14/100
2/2 [==============================] - 0s 52ms/step - loss: 0.9363 - accuracy: 0.6216 - val_loss: 0.7850 - val_accuracy: 0.7418
Epoch 15/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8778 - accuracy: 0.6667 - val_loss: 0.7686 - val_accuracy: 0.7692
Epoch 16/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8827 - accuracy: 0.6817 - val_loss: 0.7538 - val_accuracy: 0.7802
Epoch 17/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8826 - accuracy: 0.6762 - val_loss: 0.7386 - val_accuracy: 0.7967
Epoch 18/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8445 - accuracy: 0.7049 - val_loss: 0.7260 - val_accuracy: 0.7967
Epoch 19/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8208 - accuracy: 0.7199 - val_loss: 0.7145 - val_accuracy: 0.7967
Epoch 20/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8124 - accuracy: 0.7213 - val_loss: 0.7036 - val_accuracy: 0.7912
Epoch 21/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8244 - accuracy: 0.7131 - val_loss: 0.6933 - val_accuracy: 0.7912
Epoch 22/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7950 - accuracy: 0.7514 - val_loss: 0.6841 - val_accuracy: 0.7967
Epoch 23/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7896 - accuracy: 0.7377 - val_loss: 0.6744 - val_accuracy: 0.8242
Epoch 24/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7713 - accuracy: 0.7582 - val_loss: 0.6653 - val_accuracy: 0.8242
Epoch 25/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7465 - accuracy: 0.7568 - val_loss: 0.6574 - val_accuracy: 0.8297
Epoch 26/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7646 - accuracy: 0.7473 - val_loss: 0.6501 - val_accuracy: 0.8352
Epoch 27/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7152 - accuracy: 0.7842 - val_loss: 0.6427 - val_accuracy: 0.8352
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7422 - accuracy: 0.7609 - val_loss: 0.6356 - val_accuracy: 0.8352
Epoch 29/100
2/2 [==============================] - 0s 44ms/step - loss: 0.7492 - accuracy: 0.7678 - val_loss: 0.6286 - val_accuracy: 0.8352
Epoch 30/100
2/2 [==============================] - 0s 52ms/step - loss: 0.7111 - accuracy: 0.7746 - val_loss: 0.6219 - val_accuracy: 0.8352
Epoch 31/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7067 - accuracy: 0.7760 - val_loss: 0.6162 - val_accuracy: 0.8352
Epoch 32/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6660 - accuracy: 0.8033 - val_loss: 0.6108 - val_accuracy: 0.8352
Epoch 33/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7149 - accuracy: 0.7596 - val_loss: 0.6053 - val_accuracy: 0.8352
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6954 - accuracy: 0.7760 - val_loss: 0.5997 - val_accuracy: 0.8407
Epoch 35/100
2/2 [==============================] - 0s 45ms/step - loss: 0.6731 - accuracy: 0.7910 - val_loss: 0.5949 - val_accuracy: 0.8407
Epoch 36/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6747 - accuracy: 0.7937 - val_loss: 0.5898 - val_accuracy: 0.8407
Epoch 37/100
2/2 [==============================] - 0s 26ms/step - loss: 0.6646 - accuracy: 0.8033 - val_loss: 0.5848 - val_accuracy: 0.8407
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6431 - accuracy: 0.8046 - val_loss: 0.5805 - val_accuracy: 0.8352
Epoch 39/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6589 - accuracy: 0.7896 - val_loss: 0.5764 - val_accuracy: 0.8352
Epoch 40/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6607 - accuracy: 0.8169 - val_loss: 0.5722 - val_accuracy: 0.8352
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6266 - accuracy: 0.8046 - val_loss: 0.5681 - val_accuracy: 0.8352
Epoch 42/100
2/2 [==============================] - 0s 29ms/step - loss: 0.6284 - accuracy: 0.8128 - val_loss: 0.5641 - val_accuracy: 0.8407
Epoch 43/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6456 - accuracy: 0.8128 - val_loss: 0.5602 - val_accuracy: 0.8462
Epoch 44/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6518 - accuracy: 0.7937 - val_loss: 0.5569 - val_accuracy: 0.8462
Epoch 45/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6274 - accuracy: 0.8074 - val_loss: 0.5539 - val_accuracy: 0.8462
Epoch 46/100
2/2 [==============================] - 0s 30ms/step - loss: 0.6121 - accuracy: 0.8251 - val_loss: 0.5503 - val_accuracy: 0.8571
Epoch 47/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5918 - accuracy: 0.8224 - val_loss: 0.5473 - val_accuracy: 0.8571
Epoch 48/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5993 - accuracy: 0.8224 - val_loss: 0.5438 - val_accuracy: 0.8571
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6040 - accuracy: 0.8306 - val_loss: 0.5408 - val_accuracy: 0.8571
Epoch 50/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6164 - accuracy: 0.8115 - val_loss: 0.5381 - val_accuracy: 0.8571
Epoch 51/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6107 - accuracy: 0.8128 - val_loss: 0.5356 - val_accuracy: 0.8571
Epoch 52/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6048 - accuracy: 0.8361 - val_loss: 0.5322 - val_accuracy: 0.8571
Epoch 53/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6107 - accuracy: 0.8279 - val_loss: 0.5297 - val_accuracy: 0.8681
Epoch 54/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5979 - accuracy: 0.8183 - val_loss: 0.5269 - val_accuracy: 0.8626
Epoch 55/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5979 - accuracy: 0.8210 - val_loss: 0.5247 - val_accuracy: 0.8681
Epoch 56/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6170 - accuracy: 0.8279 - val_loss: 0.5222 - val_accuracy: 0.8681
Epoch 57/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6206 - accuracy: 0.8101 - val_loss: 0.5199 - val_accuracy: 0.8736
Epoch 58/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5876 - accuracy: 0.8388 - val_loss: 0.5173 - val_accuracy: 0.8736
Epoch 59/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5785 - accuracy: 0.8238 - val_loss: 0.5148 - val_accuracy: 0.8736
Epoch 60/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5713 - accuracy: 0.8306 - val_loss: 0.5126 - val_accuracy: 0.8736
Epoch 61/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5901 - accuracy: 0.8197 - val_loss: 0.5106 - val_accuracy: 0.8626
Epoch 62/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5770 - accuracy: 0.8347 - val_loss: 0.5087 - val_accuracy: 0.8681
Epoch 63/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5696 - accuracy: 0.8333 - val_loss: 0.5067 - val_accuracy: 0.8681
Epoch 64/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5743 - accuracy: 0.8265 - val_loss: 0.5046 - val_accuracy: 0.8626
Epoch 65/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5413 - accuracy: 0.8552 - val_loss: 0.5022 - val_accuracy: 0.8626
Epoch 66/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5651 - accuracy: 0.8333 - val_loss: 0.5003 - val_accuracy: 0.8681
Epoch 67/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5451 - accuracy: 0.8402 - val_loss: 0.4990 - val_accuracy: 0.8681
Epoch 68/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5583 - accuracy: 0.8306 - val_loss: 0.4970 - val_accuracy: 0.8626
Epoch 69/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5463 - accuracy: 0.8361 - val_loss: 0.4950 - val_accuracy: 0.8681
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5501 - accuracy: 0.8402 - val_loss: 0.4927 - val_accuracy: 0.8681
Epoch 71/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5390 - accuracy: 0.8374 - val_loss: 0.4909 - val_accuracy: 0.8681
Epoch 72/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5290 - accuracy: 0.8429 - val_loss: 0.4890 - val_accuracy: 0.8626
Epoch 73/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5570 - accuracy: 0.8251 - val_loss: 0.4873 - val_accuracy: 0.8626
Epoch 74/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5662 - accuracy: 0.8279 - val_loss: 0.4858 - val_accuracy: 0.8626
Epoch 75/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5506 - accuracy: 0.8361 - val_loss: 0.4840 - val_accuracy: 0.8626
Epoch 76/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5277 - accuracy: 0.8429 - val_loss: 0.4823 - val_accuracy: 0.8626
Epoch 77/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5442 - accuracy: 0.8320 - val_loss: 0.4806 - val_accuracy: 0.8681
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5457 - accuracy: 0.8429 - val_loss: 0.4793 - val_accuracy: 0.8681
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5125 - accuracy: 0.8607 - val_loss: 0.4778 - val_accuracy: 0.8681
Epoch 80/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5378 - accuracy: 0.8333 - val_loss: 0.4758 - val_accuracy: 0.8681
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5298 - accuracy: 0.8593 - val_loss: 0.4743 - val_accuracy: 0.8681
Epoch 82/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5196 - accuracy: 0.8566 - val_loss: 0.4731 - val_accuracy: 0.8681
Epoch 83/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5481 - accuracy: 0.8320 - val_loss: 0.4717 - val_accuracy: 0.8681
Epoch 84/100
2/2 [==============================] - 0s 28ms/step - loss: 0.5212 - accuracy: 0.8470 - val_loss: 0.4705 - val_accuracy: 0.8681
Epoch 85/100
2/2 [==============================] - 0s 63ms/step - loss: 0.4926 - accuracy: 0.8443 - val_loss: 0.4689 - val_accuracy: 0.8681
Epoch 86/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4983 - accuracy: 0.8484 - val_loss: 0.4676 - val_accuracy: 0.8736
Epoch 87/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5311 - accuracy: 0.8333 - val_loss: 0.4664 - val_accuracy: 0.8681
Epoch 88/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5209 - accuracy: 0.8388 - val_loss: 0.4656 - val_accuracy: 0.8736
Epoch 89/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5270 - accuracy: 0.8511 - val_loss: 0.4644 - val_accuracy: 0.8736
Epoch 90/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5090 - accuracy: 0.8374 - val_loss: 0.4629 - val_accuracy: 0.8681
Epoch 91/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5223 - accuracy: 0.8497 - val_loss: 0.4613 - val_accuracy: 0.8681
Epoch 92/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5022 - accuracy: 0.8443 - val_loss: 0.4604 - val_accuracy: 0.8736
Epoch 93/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5243 - accuracy: 0.8456 - val_loss: 0.4595 - val_accuracy: 0.8736
Epoch 94/100
2/2 [==============================] - 0s 29ms/step - loss: 0.5364 - accuracy: 0.8415 - val_loss: 0.4582 - val_accuracy: 0.8736
Epoch 95/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4923 - accuracy: 0.8415 - val_loss: 0.4571 - val_accuracy: 0.8736
Epoch 96/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5080 - accuracy: 0.8552 - val_loss: 0.4560 - val_accuracy: 0.8736
Epoch 97/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4747 - accuracy: 0.8470 - val_loss: 0.4548 - val_accuracy: 0.8736
Epoch 98/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5148 - accuracy: 0.8470 - val_loss: 0.4537 - val_accuracy: 0.8736
Epoch 99/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5035 - accuracy: 0.8538 - val_loss: 0.4526 - val_accuracy: 0.8736
Epoch 100/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5161 - accuracy: 0.8443 - val_loss: 0.4516 - val_accuracy: 0.8736
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Experiment number: 10
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 8, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 129ms/step - loss: 1.5619 - accuracy: 0.2435 - val_loss: 1.5340 - val_accuracy: 0.1366
Epoch 2/100
3/3 [==============================] - 0s 21ms/step - loss: 1.5620 - accuracy: 0.2654 - val_loss: 1.5143 - val_accuracy: 0.1366
Epoch 3/100
3/3 [==============================] - 0s 21ms/step - loss: 1.5328 - accuracy: 0.2886 - val_loss: 1.4874 - val_accuracy: 0.1421
Epoch 4/100
3/3 [==============================] - 0s 16ms/step - loss: 1.5413 - accuracy: 0.2859 - val_loss: 1.4556 - val_accuracy: 0.1421
Epoch 5/100
3/3 [==============================] - 0s 20ms/step - loss: 1.4782 - accuracy: 0.3311 - val_loss: 1.4213 - val_accuracy: 0.1530
Epoch 6/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4298 - accuracy: 0.3365 - val_loss: 1.3859 - val_accuracy: 0.1530
Epoch 7/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3521 - accuracy: 0.3721 - val_loss: 1.3507 - val_accuracy: 0.1694
Epoch 8/100
3/3 [==============================] - 0s 18ms/step - loss: 1.3620 - accuracy: 0.3735 - val_loss: 1.3163 - val_accuracy: 0.2131
Epoch 9/100
3/3 [==============================] - 0s 20ms/step - loss: 1.3151 - accuracy: 0.4118 - val_loss: 1.2827 - val_accuracy: 0.2350
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3153 - accuracy: 0.3803 - val_loss: 1.2505 - val_accuracy: 0.2459
Epoch 11/100
3/3 [==============================] - 0s 24ms/step - loss: 1.2957 - accuracy: 0.4022 - val_loss: 1.2195 - val_accuracy: 0.2623
Epoch 12/100
3/3 [==============================] - 0s 23ms/step - loss: 1.2408 - accuracy: 0.4282 - val_loss: 1.1902 - val_accuracy: 0.3005
Epoch 13/100
3/3 [==============================] - 0s 21ms/step - loss: 1.2005 - accuracy: 0.4323 - val_loss: 1.1625 - val_accuracy: 0.3279
Epoch 14/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1817 - accuracy: 0.4583 - val_loss: 1.1363 - val_accuracy: 0.3716
Epoch 15/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1609 - accuracy: 0.5007 - val_loss: 1.1115 - val_accuracy: 0.3934
Epoch 16/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1005 - accuracy: 0.5335 - val_loss: 1.0882 - val_accuracy: 0.4426
Epoch 17/100
3/3 [==============================] - 0s 19ms/step - loss: 1.0728 - accuracy: 0.5280 - val_loss: 1.0663 - val_accuracy: 0.4863
Epoch 18/100
3/3 [==============================] - 0s 19ms/step - loss: 1.0837 - accuracy: 0.5431 - val_loss: 1.0458 - val_accuracy: 0.5137
Epoch 19/100
3/3 [==============================] - 0s 20ms/step - loss: 1.0479 - accuracy: 0.5746 - val_loss: 1.0262 - val_accuracy: 0.5519
Epoch 20/100
3/3 [==============================] - 0s 20ms/step - loss: 1.0028 - accuracy: 0.6156 - val_loss: 1.0079 - val_accuracy: 0.6230
Epoch 21/100
3/3 [==============================] - 0s 20ms/step - loss: 1.0058 - accuracy: 0.6129 - val_loss: 0.9909 - val_accuracy: 0.6557
Epoch 22/100
3/3 [==============================] - 0s 17ms/step - loss: 0.9579 - accuracy: 0.6525 - val_loss: 0.9748 - val_accuracy: 0.7104
Epoch 23/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9725 - accuracy: 0.6854 - val_loss: 0.9595 - val_accuracy: 0.7377
Epoch 24/100
3/3 [==============================] - 0s 21ms/step - loss: 0.9540 - accuracy: 0.6854 - val_loss: 0.9451 - val_accuracy: 0.7596
Epoch 25/100
3/3 [==============================] - 0s 24ms/step - loss: 0.9410 - accuracy: 0.6854 - val_loss: 0.9314 - val_accuracy: 0.7650
Epoch 26/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9005 - accuracy: 0.7209 - val_loss: 0.9183 - val_accuracy: 0.7760
Epoch 27/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9046 - accuracy: 0.7155 - val_loss: 0.9059 - val_accuracy: 0.7814
Epoch 28/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8857 - accuracy: 0.7264 - val_loss: 0.8941 - val_accuracy: 0.7978
Epoch 29/100
3/3 [==============================] - 0s 21ms/step - loss: 0.8921 - accuracy: 0.7387 - val_loss: 0.8828 - val_accuracy: 0.7978
Epoch 30/100
3/3 [==============================] - 0s 18ms/step - loss: 0.8540 - accuracy: 0.7551 - val_loss: 0.8721 - val_accuracy: 0.8033
Epoch 31/100
3/3 [==============================] - 0s 20ms/step - loss: 0.8850 - accuracy: 0.7538 - val_loss: 0.8617 - val_accuracy: 0.7978
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 0.8380 - accuracy: 0.7715 - val_loss: 0.8517 - val_accuracy: 0.8033
Epoch 33/100
3/3 [==============================] - 0s 20ms/step - loss: 0.8612 - accuracy: 0.7524 - val_loss: 0.8420 - val_accuracy: 0.8033
Epoch 34/100
3/3 [==============================] - 0s 17ms/step - loss: 0.8530 - accuracy: 0.7798 - val_loss: 0.8326 - val_accuracy: 0.8033
Epoch 35/100
3/3 [==============================] - 0s 18ms/step - loss: 0.8044 - accuracy: 0.7825 - val_loss: 0.8235 - val_accuracy: 0.8087
Epoch 36/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7967 - accuracy: 0.7907 - val_loss: 0.8149 - val_accuracy: 0.8142
Epoch 37/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7763 - accuracy: 0.8112 - val_loss: 0.8066 - val_accuracy: 0.8142
Epoch 38/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7635 - accuracy: 0.8085 - val_loss: 0.7987 - val_accuracy: 0.8142
Epoch 39/100
3/3 [==============================] - 0s 21ms/step - loss: 0.7914 - accuracy: 0.8016 - val_loss: 0.7911 - val_accuracy: 0.8142
Epoch 40/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7741 - accuracy: 0.8071 - val_loss: 0.7837 - val_accuracy: 0.8142
Epoch 41/100
3/3 [==============================] - 0s 15ms/step - loss: 0.7533 - accuracy: 0.8331 - val_loss: 0.7765 - val_accuracy: 0.8142
Epoch 42/100
3/3 [==============================] - 0s 16ms/step - loss: 0.7488 - accuracy: 0.8304 - val_loss: 0.7696 - val_accuracy: 0.8142
Epoch 43/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7355 - accuracy: 0.8290 - val_loss: 0.7628 - val_accuracy: 0.8142
Epoch 44/100
3/3 [==============================] - 0s 15ms/step - loss: 0.7256 - accuracy: 0.8276 - val_loss: 0.7563 - val_accuracy: 0.8142
Epoch 45/100
3/3 [==============================] - 0s 15ms/step - loss: 0.7138 - accuracy: 0.8386 - val_loss: 0.7499 - val_accuracy: 0.8142
Epoch 46/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7230 - accuracy: 0.8317 - val_loss: 0.7439 - val_accuracy: 0.8142
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 0.7146 - accuracy: 0.8399 - val_loss: 0.7380 - val_accuracy: 0.8142
Epoch 48/100
3/3 [==============================] - 0s 17ms/step - loss: 0.7141 - accuracy: 0.8372 - val_loss: 0.7323 - val_accuracy: 0.8142
Epoch 49/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6861 - accuracy: 0.8235 - val_loss: 0.7267 - val_accuracy: 0.8142
Epoch 50/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7100 - accuracy: 0.8331 - val_loss: 0.7214 - val_accuracy: 0.8142
Epoch 51/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6886 - accuracy: 0.8386 - val_loss: 0.7161 - val_accuracy: 0.8142
Epoch 52/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6836 - accuracy: 0.8413 - val_loss: 0.7111 - val_accuracy: 0.8142
Epoch 53/100
3/3 [==============================] - 0s 14ms/step - loss: 0.6955 - accuracy: 0.8358 - val_loss: 0.7062 - val_accuracy: 0.8142
Epoch 54/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6805 - accuracy: 0.8358 - val_loss: 0.7014 - val_accuracy: 0.8142
Epoch 55/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6683 - accuracy: 0.8495 - val_loss: 0.6968 - val_accuracy: 0.8142
Epoch 56/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6771 - accuracy: 0.8358 - val_loss: 0.6922 - val_accuracy: 0.8142
Epoch 57/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6553 - accuracy: 0.8427 - val_loss: 0.6877 - val_accuracy: 0.8142
Epoch 58/100
3/3 [==============================] - 0s 22ms/step - loss: 0.6468 - accuracy: 0.8440 - val_loss: 0.6833 - val_accuracy: 0.8142
Epoch 59/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6456 - accuracy: 0.8495 - val_loss: 0.6790 - val_accuracy: 0.8142
Epoch 60/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6519 - accuracy: 0.8413 - val_loss: 0.6747 - val_accuracy: 0.8142
Epoch 61/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6270 - accuracy: 0.8413 - val_loss: 0.6706 - val_accuracy: 0.8142
Epoch 62/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6433 - accuracy: 0.8482 - val_loss: 0.6666 - val_accuracy: 0.8142
Epoch 63/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6334 - accuracy: 0.8523 - val_loss: 0.6627 - val_accuracy: 0.8142
Epoch 64/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6451 - accuracy: 0.8536 - val_loss: 0.6588 - val_accuracy: 0.8142
Epoch 65/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6362 - accuracy: 0.8523 - val_loss: 0.6551 - val_accuracy: 0.8142
Epoch 66/100
3/3 [==============================] - 0s 22ms/step - loss: 0.6071 - accuracy: 0.8564 - val_loss: 0.6514 - val_accuracy: 0.8142
Epoch 67/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6232 - accuracy: 0.8591 - val_loss: 0.6478 - val_accuracy: 0.8142
Epoch 68/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6135 - accuracy: 0.8550 - val_loss: 0.6443 - val_accuracy: 0.8142
Epoch 69/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6093 - accuracy: 0.8523 - val_loss: 0.6409 - val_accuracy: 0.8142
Epoch 70/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6144 - accuracy: 0.8509 - val_loss: 0.6376 - val_accuracy: 0.8142
Epoch 71/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6067 - accuracy: 0.8523 - val_loss: 0.6343 - val_accuracy: 0.8142
Epoch 72/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5979 - accuracy: 0.8523 - val_loss: 0.6311 - val_accuracy: 0.8142
Epoch 73/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6171 - accuracy: 0.8495 - val_loss: 0.6278 - val_accuracy: 0.8142
Epoch 74/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5941 - accuracy: 0.8523 - val_loss: 0.6247 - val_accuracy: 0.8142
Epoch 75/100
3/3 [==============================] - 0s 15ms/step - loss: 0.5913 - accuracy: 0.8550 - val_loss: 0.6217 - val_accuracy: 0.8142
Epoch 76/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5921 - accuracy: 0.8550 - val_loss: 0.6187 - val_accuracy: 0.8142
Epoch 77/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5984 - accuracy: 0.8564 - val_loss: 0.6158 - val_accuracy: 0.8142
Epoch 78/100
3/3 [==============================] - 0s 25ms/step - loss: 0.5742 - accuracy: 0.8523 - val_loss: 0.6130 - val_accuracy: 0.8142
Epoch 79/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5867 - accuracy: 0.8550 - val_loss: 0.6103 - val_accuracy: 0.8142
Epoch 80/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5844 - accuracy: 0.8495 - val_loss: 0.6076 - val_accuracy: 0.8142
Epoch 81/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5945 - accuracy: 0.8482 - val_loss: 0.6050 - val_accuracy: 0.8142
Epoch 82/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5930 - accuracy: 0.8536 - val_loss: 0.6024 - val_accuracy: 0.8142
Epoch 83/100
3/3 [==============================] - 0s 14ms/step - loss: 0.5727 - accuracy: 0.8564 - val_loss: 0.5999 - val_accuracy: 0.8142
Epoch 84/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5567 - accuracy: 0.8536 - val_loss: 0.5973 - val_accuracy: 0.8142
Epoch 85/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5676 - accuracy: 0.8577 - val_loss: 0.5948 - val_accuracy: 0.8142
Epoch 86/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5734 - accuracy: 0.8550 - val_loss: 0.5924 - val_accuracy: 0.8142
Epoch 87/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5592 - accuracy: 0.8564 - val_loss: 0.5899 - val_accuracy: 0.8142
Epoch 88/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5756 - accuracy: 0.8509 - val_loss: 0.5876 - val_accuracy: 0.8142
Epoch 89/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5620 - accuracy: 0.8550 - val_loss: 0.5852 - val_accuracy: 0.8142
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5658 - accuracy: 0.8550 - val_loss: 0.5830 - val_accuracy: 0.8142
Epoch 91/100
3/3 [==============================] - 0s 13ms/step - loss: 0.5559 - accuracy: 0.8536 - val_loss: 0.5808 - val_accuracy: 0.8142
Epoch 92/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5603 - accuracy: 0.8550 - val_loss: 0.5786 - val_accuracy: 0.8142
Epoch 93/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5406 - accuracy: 0.8564 - val_loss: 0.5765 - val_accuracy: 0.8142
Epoch 94/100
3/3 [==============================] - 0s 25ms/step - loss: 0.5573 - accuracy: 0.8577 - val_loss: 0.5743 - val_accuracy: 0.8142
Epoch 95/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5492 - accuracy: 0.8591 - val_loss: 0.5720 - val_accuracy: 0.8142
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5355 - accuracy: 0.8536 - val_loss: 0.5699 - val_accuracy: 0.8142
Epoch 97/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5382 - accuracy: 0.8550 - val_loss: 0.5678 - val_accuracy: 0.8142
Epoch 98/100
3/3 [==============================] - 0s 24ms/step - loss: 0.5426 - accuracy: 0.8577 - val_loss: 0.5657 - val_accuracy: 0.8142
Epoch 99/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5450 - accuracy: 0.8591 - val_loss: 0.5637 - val_accuracy: 0.8142
Epoch 100/100
3/3 [==============================] - 0s 15ms/step - loss: 0.5396 - accuracy: 0.8550 - val_loss: 0.5616 - val_accuracy: 0.8142
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 8, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 120ms/step - loss: 1.8138 - accuracy: 0.2900 - val_loss: 1.5986 - val_accuracy: 0.2842
Epoch 2/100
3/3 [==============================] - 0s 20ms/step - loss: 1.7267 - accuracy: 0.3119 - val_loss: 1.5690 - val_accuracy: 0.2842
Epoch 3/100
3/3 [==============================] - 0s 18ms/step - loss: 1.6965 - accuracy: 0.3023 - val_loss: 1.5286 - val_accuracy: 0.3005
Epoch 4/100
3/3 [==============================] - 0s 19ms/step - loss: 1.6153 - accuracy: 0.3570 - val_loss: 1.4822 - val_accuracy: 0.3169
Epoch 5/100
3/3 [==============================] - 0s 18ms/step - loss: 1.6324 - accuracy: 0.3297 - val_loss: 1.4321 - val_accuracy: 0.3443
Epoch 6/100
3/3 [==============================] - 0s 19ms/step - loss: 1.5440 - accuracy: 0.3543 - val_loss: 1.3811 - val_accuracy: 0.3716
Epoch 7/100
3/3 [==============================] - 0s 16ms/step - loss: 1.5005 - accuracy: 0.3721 - val_loss: 1.3304 - val_accuracy: 0.3880
Epoch 8/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4369 - accuracy: 0.3721 - val_loss: 1.2811 - val_accuracy: 0.4208
Epoch 9/100
3/3 [==============================] - 0s 19ms/step - loss: 1.3747 - accuracy: 0.4172 - val_loss: 1.2341 - val_accuracy: 0.4317
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 1.3787 - accuracy: 0.4063 - val_loss: 1.1892 - val_accuracy: 0.4536
Epoch 11/100
3/3 [==============================] - 0s 22ms/step - loss: 1.2825 - accuracy: 0.4665 - val_loss: 1.1468 - val_accuracy: 0.4590
Epoch 12/100
3/3 [==============================] - 0s 14ms/step - loss: 1.2656 - accuracy: 0.4679 - val_loss: 1.1069 - val_accuracy: 0.4918
Epoch 13/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1874 - accuracy: 0.4733 - val_loss: 1.0696 - val_accuracy: 0.5246
Epoch 14/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1793 - accuracy: 0.4815 - val_loss: 1.0352 - val_accuracy: 0.5464
Epoch 15/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1346 - accuracy: 0.5308 - val_loss: 1.0031 - val_accuracy: 0.5792
Epoch 16/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1277 - accuracy: 0.5239 - val_loss: 0.9730 - val_accuracy: 0.6175
Epoch 17/100
3/3 [==============================] - 0s 15ms/step - loss: 1.0797 - accuracy: 0.5527 - val_loss: 0.9451 - val_accuracy: 0.6230
Epoch 18/100
3/3 [==============================] - 0s 18ms/step - loss: 1.0353 - accuracy: 0.5554 - val_loss: 0.9193 - val_accuracy: 0.6339
Epoch 19/100
3/3 [==============================] - 0s 21ms/step - loss: 0.9682 - accuracy: 0.6129 - val_loss: 0.8957 - val_accuracy: 0.6503
Epoch 20/100
3/3 [==============================] - 0s 20ms/step - loss: 0.9703 - accuracy: 0.6019 - val_loss: 0.8739 - val_accuracy: 0.6612
Epoch 21/100
3/3 [==============================] - 0s 19ms/step - loss: 0.9473 - accuracy: 0.6279 - val_loss: 0.8536 - val_accuracy: 0.6721
Epoch 22/100
3/3 [==============================] - 0s 24ms/step - loss: 0.9477 - accuracy: 0.6416 - val_loss: 0.8345 - val_accuracy: 0.7049
Epoch 23/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9106 - accuracy: 0.6525 - val_loss: 0.8168 - val_accuracy: 0.7104
Epoch 24/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8819 - accuracy: 0.6840 - val_loss: 0.8004 - val_accuracy: 0.7486
Epoch 25/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8939 - accuracy: 0.6621 - val_loss: 0.7851 - val_accuracy: 0.7760
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8514 - accuracy: 0.7100 - val_loss: 0.7707 - val_accuracy: 0.7869
Epoch 27/100
3/3 [==============================] - 0s 17ms/step - loss: 0.8615 - accuracy: 0.6990 - val_loss: 0.7572 - val_accuracy: 0.8033
Epoch 28/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8245 - accuracy: 0.7387 - val_loss: 0.7447 - val_accuracy: 0.8033
Epoch 29/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7994 - accuracy: 0.7524 - val_loss: 0.7330 - val_accuracy: 0.8087
Epoch 30/100
3/3 [==============================] - 0s 24ms/step - loss: 0.8018 - accuracy: 0.7565 - val_loss: 0.7220 - val_accuracy: 0.8142
Epoch 31/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7748 - accuracy: 0.7579 - val_loss: 0.7117 - val_accuracy: 0.8142
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7803 - accuracy: 0.7688 - val_loss: 0.7021 - val_accuracy: 0.8251
Epoch 33/100
3/3 [==============================] - 0s 16ms/step - loss: 0.7742 - accuracy: 0.7620 - val_loss: 0.6929 - val_accuracy: 0.8251
Epoch 34/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7632 - accuracy: 0.7798 - val_loss: 0.6842 - val_accuracy: 0.8251
Epoch 35/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7388 - accuracy: 0.7893 - val_loss: 0.6760 - val_accuracy: 0.8306
Epoch 36/100
3/3 [==============================] - 0s 21ms/step - loss: 0.7272 - accuracy: 0.7825 - val_loss: 0.6682 - val_accuracy: 0.8361
Epoch 37/100
3/3 [==============================] - 0s 15ms/step - loss: 0.7298 - accuracy: 0.7907 - val_loss: 0.6607 - val_accuracy: 0.8361
Epoch 38/100
3/3 [==============================] - 0s 17ms/step - loss: 0.7308 - accuracy: 0.8016 - val_loss: 0.6535 - val_accuracy: 0.8415
Epoch 39/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7137 - accuracy: 0.8003 - val_loss: 0.6468 - val_accuracy: 0.8415
Epoch 40/100
3/3 [==============================] - 0s 23ms/step - loss: 0.7092 - accuracy: 0.8085 - val_loss: 0.6402 - val_accuracy: 0.8415
Epoch 41/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6997 - accuracy: 0.7989 - val_loss: 0.6340 - val_accuracy: 0.8415
Epoch 42/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7094 - accuracy: 0.8071 - val_loss: 0.6280 - val_accuracy: 0.8415
Epoch 43/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6928 - accuracy: 0.8153 - val_loss: 0.6223 - val_accuracy: 0.8415
Epoch 44/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6815 - accuracy: 0.8235 - val_loss: 0.6170 - val_accuracy: 0.8415
Epoch 45/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6690 - accuracy: 0.8153 - val_loss: 0.6119 - val_accuracy: 0.8415
Epoch 46/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6718 - accuracy: 0.8167 - val_loss: 0.6069 - val_accuracy: 0.8415
Epoch 47/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6703 - accuracy: 0.8167 - val_loss: 0.6022 - val_accuracy: 0.8415
Epoch 48/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6561 - accuracy: 0.8153 - val_loss: 0.5977 - val_accuracy: 0.8415
Epoch 49/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6416 - accuracy: 0.8263 - val_loss: 0.5934 - val_accuracy: 0.8415
Epoch 50/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6398 - accuracy: 0.8249 - val_loss: 0.5893 - val_accuracy: 0.8415
Epoch 51/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6409 - accuracy: 0.8317 - val_loss: 0.5853 - val_accuracy: 0.8415
Epoch 52/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6380 - accuracy: 0.8386 - val_loss: 0.5814 - val_accuracy: 0.8415
Epoch 53/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6151 - accuracy: 0.8317 - val_loss: 0.5778 - val_accuracy: 0.8415
Epoch 54/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6079 - accuracy: 0.8358 - val_loss: 0.5742 - val_accuracy: 0.8415
Epoch 55/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6284 - accuracy: 0.8304 - val_loss: 0.5708 - val_accuracy: 0.8415
Epoch 56/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6352 - accuracy: 0.8290 - val_loss: 0.5675 - val_accuracy: 0.8415
Epoch 57/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6168 - accuracy: 0.8372 - val_loss: 0.5644 - val_accuracy: 0.8415
Epoch 58/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6080 - accuracy: 0.8440 - val_loss: 0.5614 - val_accuracy: 0.8415
Epoch 59/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6021 - accuracy: 0.8372 - val_loss: 0.5584 - val_accuracy: 0.8415
Epoch 60/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6039 - accuracy: 0.8386 - val_loss: 0.5556 - val_accuracy: 0.8415
Epoch 61/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5990 - accuracy: 0.8413 - val_loss: 0.5529 - val_accuracy: 0.8415
Epoch 62/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5829 - accuracy: 0.8413 - val_loss: 0.5502 - val_accuracy: 0.8415
Epoch 63/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5920 - accuracy: 0.8427 - val_loss: 0.5477 - val_accuracy: 0.8415
Epoch 64/100
3/3 [==============================] - 0s 24ms/step - loss: 0.5916 - accuracy: 0.8427 - val_loss: 0.5452 - val_accuracy: 0.8415
Epoch 65/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5890 - accuracy: 0.8413 - val_loss: 0.5428 - val_accuracy: 0.8415
Epoch 66/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5824 - accuracy: 0.8427 - val_loss: 0.5404 - val_accuracy: 0.8415
Epoch 67/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5665 - accuracy: 0.8468 - val_loss: 0.5382 - val_accuracy: 0.8415
Epoch 68/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5900 - accuracy: 0.8509 - val_loss: 0.5360 - val_accuracy: 0.8415
Epoch 69/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5851 - accuracy: 0.8495 - val_loss: 0.5338 - val_accuracy: 0.8415
Epoch 70/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5674 - accuracy: 0.8440 - val_loss: 0.5318 - val_accuracy: 0.8415
Epoch 71/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5753 - accuracy: 0.8468 - val_loss: 0.5298 - val_accuracy: 0.8415
Epoch 72/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5784 - accuracy: 0.8482 - val_loss: 0.5278 - val_accuracy: 0.8415
Epoch 73/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5765 - accuracy: 0.8495 - val_loss: 0.5258 - val_accuracy: 0.8415
Epoch 74/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5652 - accuracy: 0.8468 - val_loss: 0.5240 - val_accuracy: 0.8415
Epoch 75/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5546 - accuracy: 0.8509 - val_loss: 0.5221 - val_accuracy: 0.8415
Epoch 76/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5705 - accuracy: 0.8495 - val_loss: 0.5203 - val_accuracy: 0.8415
Epoch 77/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5758 - accuracy: 0.8495 - val_loss: 0.5185 - val_accuracy: 0.8415
Epoch 78/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5683 - accuracy: 0.8482 - val_loss: 0.5166 - val_accuracy: 0.8415
Epoch 79/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5700 - accuracy: 0.8482 - val_loss: 0.5149 - val_accuracy: 0.8415
Epoch 80/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5614 - accuracy: 0.8482 - val_loss: 0.5132 - val_accuracy: 0.8415
Epoch 81/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5491 - accuracy: 0.8509 - val_loss: 0.5116 - val_accuracy: 0.8415
Epoch 82/100
3/3 [==============================] - 0s 14ms/step - loss: 0.5546 - accuracy: 0.8509 - val_loss: 0.5100 - val_accuracy: 0.8415
Epoch 83/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5512 - accuracy: 0.8523 - val_loss: 0.5084 - val_accuracy: 0.8415
Epoch 84/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5475 - accuracy: 0.8509 - val_loss: 0.5069 - val_accuracy: 0.8415
Epoch 85/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5476 - accuracy: 0.8523 - val_loss: 0.5054 - val_accuracy: 0.8415
Epoch 86/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5391 - accuracy: 0.8509 - val_loss: 0.5040 - val_accuracy: 0.8415
Epoch 87/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5577 - accuracy: 0.8523 - val_loss: 0.5026 - val_accuracy: 0.8415
Epoch 88/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5474 - accuracy: 0.8523 - val_loss: 0.5012 - val_accuracy: 0.8415
Epoch 89/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5512 - accuracy: 0.8523 - val_loss: 0.4998 - val_accuracy: 0.8415
Epoch 90/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5351 - accuracy: 0.8509 - val_loss: 0.4985 - val_accuracy: 0.8415
Epoch 91/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5282 - accuracy: 0.8523 - val_loss: 0.4972 - val_accuracy: 0.8415
Epoch 92/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5327 - accuracy: 0.8523 - val_loss: 0.4960 - val_accuracy: 0.8415
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5341 - accuracy: 0.8523 - val_loss: 0.4947 - val_accuracy: 0.8415
Epoch 94/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5338 - accuracy: 0.8523 - val_loss: 0.4935 - val_accuracy: 0.8415
Epoch 95/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5272 - accuracy: 0.8523 - val_loss: 0.4922 - val_accuracy: 0.8415
Epoch 96/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5350 - accuracy: 0.8523 - val_loss: 0.4911 - val_accuracy: 0.8415
Epoch 97/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5257 - accuracy: 0.8509 - val_loss: 0.4899 - val_accuracy: 0.8415
Epoch 98/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5221 - accuracy: 0.8523 - val_loss: 0.4887 - val_accuracy: 0.8415
Epoch 99/100
3/3 [==============================] - 0s 25ms/step - loss: 0.5305 - accuracy: 0.8523 - val_loss: 0.4876 - val_accuracy: 0.8415
Epoch 100/100
3/3 [==============================] - 0s 26ms/step - loss: 0.5099 - accuracy: 0.8523 - val_loss: 0.4864 - val_accuracy: 0.8415
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 8, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 115ms/step - loss: 1.2415 - accuracy: 0.4583 - val_loss: 1.1704 - val_accuracy: 0.4645
Epoch 2/100
3/3 [==============================] - 0s 15ms/step - loss: 1.2116 - accuracy: 0.4979 - val_loss: 1.1556 - val_accuracy: 0.4809
Epoch 3/100
3/3 [==============================] - 0s 16ms/step - loss: 1.2008 - accuracy: 0.5075 - val_loss: 1.1352 - val_accuracy: 0.5027
Epoch 4/100
3/3 [==============================] - 0s 22ms/step - loss: 1.1578 - accuracy: 0.5404 - val_loss: 1.1113 - val_accuracy: 0.5246
Epoch 5/100
3/3 [==============================] - 0s 20ms/step - loss: 1.1177 - accuracy: 0.5527 - val_loss: 1.0859 - val_accuracy: 0.5519
Epoch 6/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1449 - accuracy: 0.5335 - val_loss: 1.0595 - val_accuracy: 0.5519
Epoch 7/100
3/3 [==============================] - 0s 15ms/step - loss: 1.0936 - accuracy: 0.5622 - val_loss: 1.0332 - val_accuracy: 0.5847
Epoch 8/100
3/3 [==============================] - 0s 16ms/step - loss: 1.0755 - accuracy: 0.5622 - val_loss: 1.0073 - val_accuracy: 0.6066
Epoch 9/100
3/3 [==============================] - 0s 18ms/step - loss: 1.0477 - accuracy: 0.6033 - val_loss: 0.9822 - val_accuracy: 0.6284
Epoch 10/100
3/3 [==============================] - 0s 19ms/step - loss: 1.0298 - accuracy: 0.6115 - val_loss: 0.9579 - val_accuracy: 0.6503
Epoch 11/100
3/3 [==============================] - 0s 19ms/step - loss: 0.9991 - accuracy: 0.6060 - val_loss: 0.9345 - val_accuracy: 0.6721
Epoch 12/100
3/3 [==============================] - 0s 21ms/step - loss: 0.9957 - accuracy: 0.6115 - val_loss: 0.9122 - val_accuracy: 0.6831
Epoch 13/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9582 - accuracy: 0.6594 - val_loss: 0.8914 - val_accuracy: 0.7104
Epoch 14/100
3/3 [==============================] - 0s 21ms/step - loss: 0.9213 - accuracy: 0.6717 - val_loss: 0.8718 - val_accuracy: 0.7213
Epoch 15/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9263 - accuracy: 0.6826 - val_loss: 0.8533 - val_accuracy: 0.7322
Epoch 16/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9144 - accuracy: 0.6826 - val_loss: 0.8360 - val_accuracy: 0.7432
Epoch 17/100
3/3 [==============================] - 0s 20ms/step - loss: 0.8614 - accuracy: 0.7059 - val_loss: 0.8197 - val_accuracy: 0.7541
Epoch 18/100
3/3 [==============================] - 0s 20ms/step - loss: 0.8818 - accuracy: 0.7196 - val_loss: 0.8044 - val_accuracy: 0.7596
Epoch 19/100
3/3 [==============================] - 0s 22ms/step - loss: 0.8506 - accuracy: 0.7073 - val_loss: 0.7899 - val_accuracy: 0.7814
Epoch 20/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8529 - accuracy: 0.7223 - val_loss: 0.7764 - val_accuracy: 0.7814
Epoch 21/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8125 - accuracy: 0.7510 - val_loss: 0.7637 - val_accuracy: 0.7978
Epoch 22/100
3/3 [==============================] - 0s 17ms/step - loss: 0.8180 - accuracy: 0.7606 - val_loss: 0.7517 - val_accuracy: 0.8033
Epoch 23/100
3/3 [==============================] - 0s 14ms/step - loss: 0.7934 - accuracy: 0.7756 - val_loss: 0.7405 - val_accuracy: 0.8142
Epoch 24/100
3/3 [==============================] - 0s 13ms/step - loss: 0.7845 - accuracy: 0.7592 - val_loss: 0.7299 - val_accuracy: 0.8197
Epoch 25/100
3/3 [==============================] - 0s 17ms/step - loss: 0.7690 - accuracy: 0.7715 - val_loss: 0.7200 - val_accuracy: 0.8142
Epoch 26/100
3/3 [==============================] - 0s 23ms/step - loss: 0.7616 - accuracy: 0.7839 - val_loss: 0.7105 - val_accuracy: 0.8197
Epoch 27/100
3/3 [==============================] - 0s 22ms/step - loss: 0.7523 - accuracy: 0.7866 - val_loss: 0.7014 - val_accuracy: 0.8251
Epoch 28/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7428 - accuracy: 0.7866 - val_loss: 0.6929 - val_accuracy: 0.8197
Epoch 29/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7176 - accuracy: 0.8030 - val_loss: 0.6847 - val_accuracy: 0.8142
Epoch 30/100
3/3 [==============================] - 0s 22ms/step - loss: 0.7253 - accuracy: 0.8085 - val_loss: 0.6770 - val_accuracy: 0.8142
Epoch 31/100
3/3 [==============================] - 0s 23ms/step - loss: 0.7002 - accuracy: 0.8235 - val_loss: 0.6696 - val_accuracy: 0.8142
Epoch 32/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7180 - accuracy: 0.7989 - val_loss: 0.6626 - val_accuracy: 0.8306
Epoch 33/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6957 - accuracy: 0.8194 - val_loss: 0.6559 - val_accuracy: 0.8361
Epoch 34/100
3/3 [==============================] - 0s 14ms/step - loss: 0.7058 - accuracy: 0.8112 - val_loss: 0.6497 - val_accuracy: 0.8361
Epoch 35/100
3/3 [==============================] - 0s 21ms/step - loss: 0.7014 - accuracy: 0.8140 - val_loss: 0.6437 - val_accuracy: 0.8415
Epoch 36/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6899 - accuracy: 0.8167 - val_loss: 0.6380 - val_accuracy: 0.8415
Epoch 37/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6842 - accuracy: 0.8140 - val_loss: 0.6325 - val_accuracy: 0.8415
Epoch 38/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6746 - accuracy: 0.8153 - val_loss: 0.6273 - val_accuracy: 0.8415
Epoch 39/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6765 - accuracy: 0.8167 - val_loss: 0.6222 - val_accuracy: 0.8415
Epoch 40/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6633 - accuracy: 0.8140 - val_loss: 0.6174 - val_accuracy: 0.8415
Epoch 41/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6444 - accuracy: 0.8290 - val_loss: 0.6128 - val_accuracy: 0.8415
Epoch 42/100
3/3 [==============================] - 0s 33ms/step - loss: 0.6515 - accuracy: 0.8194 - val_loss: 0.6084 - val_accuracy: 0.8415
Epoch 43/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6458 - accuracy: 0.8167 - val_loss: 0.6041 - val_accuracy: 0.8470
Epoch 44/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6368 - accuracy: 0.8276 - val_loss: 0.6000 - val_accuracy: 0.8470
Epoch 45/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6444 - accuracy: 0.8181 - val_loss: 0.5961 - val_accuracy: 0.8470
Epoch 46/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6377 - accuracy: 0.8358 - val_loss: 0.5923 - val_accuracy: 0.8470
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6348 - accuracy: 0.8358 - val_loss: 0.5886 - val_accuracy: 0.8470
Epoch 48/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6196 - accuracy: 0.8263 - val_loss: 0.5851 - val_accuracy: 0.8470
Epoch 49/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6119 - accuracy: 0.8399 - val_loss: 0.5816 - val_accuracy: 0.8470
Epoch 50/100
3/3 [==============================] - 0s 14ms/step - loss: 0.6229 - accuracy: 0.8317 - val_loss: 0.5783 - val_accuracy: 0.8470
Epoch 51/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6238 - accuracy: 0.8249 - val_loss: 0.5751 - val_accuracy: 0.8470
Epoch 52/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6064 - accuracy: 0.8372 - val_loss: 0.5721 - val_accuracy: 0.8470
Epoch 53/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6046 - accuracy: 0.8386 - val_loss: 0.5692 - val_accuracy: 0.8470
Epoch 54/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6023 - accuracy: 0.8454 - val_loss: 0.5664 - val_accuracy: 0.8470
Epoch 55/100
3/3 [==============================] - 0s 13ms/step - loss: 0.6144 - accuracy: 0.8427 - val_loss: 0.5637 - val_accuracy: 0.8470
Epoch 56/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5813 - accuracy: 0.8399 - val_loss: 0.5612 - val_accuracy: 0.8470
Epoch 57/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5953 - accuracy: 0.8468 - val_loss: 0.5587 - val_accuracy: 0.8470
Epoch 58/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5984 - accuracy: 0.8413 - val_loss: 0.5563 - val_accuracy: 0.8470
Epoch 59/100
3/3 [==============================] - 0s 25ms/step - loss: 0.5937 - accuracy: 0.8358 - val_loss: 0.5540 - val_accuracy: 0.8470
Epoch 60/100
3/3 [==============================] - 0s 25ms/step - loss: 0.5879 - accuracy: 0.8372 - val_loss: 0.5517 - val_accuracy: 0.8470
Epoch 61/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5896 - accuracy: 0.8413 - val_loss: 0.5495 - val_accuracy: 0.8470
Epoch 62/100
3/3 [==============================] - 0s 32ms/step - loss: 0.5791 - accuracy: 0.8495 - val_loss: 0.5473 - val_accuracy: 0.8470
Epoch 63/100
3/3 [==============================] - 0s 25ms/step - loss: 0.5770 - accuracy: 0.8468 - val_loss: 0.5452 - val_accuracy: 0.8470
Epoch 64/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5904 - accuracy: 0.8427 - val_loss: 0.5431 - val_accuracy: 0.8470
Epoch 65/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5834 - accuracy: 0.8454 - val_loss: 0.5412 - val_accuracy: 0.8470
Epoch 66/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5697 - accuracy: 0.8454 - val_loss: 0.5392 - val_accuracy: 0.8470
Epoch 67/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5745 - accuracy: 0.8440 - val_loss: 0.5374 - val_accuracy: 0.8470
Epoch 68/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5561 - accuracy: 0.8468 - val_loss: 0.5356 - val_accuracy: 0.8470
Epoch 69/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5688 - accuracy: 0.8509 - val_loss: 0.5338 - val_accuracy: 0.8470
Epoch 70/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5639 - accuracy: 0.8482 - val_loss: 0.5321 - val_accuracy: 0.8470
Epoch 71/100
3/3 [==============================] - 0s 15ms/step - loss: 0.5629 - accuracy: 0.8468 - val_loss: 0.5304 - val_accuracy: 0.8470
Epoch 72/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5586 - accuracy: 0.8482 - val_loss: 0.5288 - val_accuracy: 0.8470
Epoch 73/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5468 - accuracy: 0.8509 - val_loss: 0.5272 - val_accuracy: 0.8470
Epoch 74/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5524 - accuracy: 0.8495 - val_loss: 0.5257 - val_accuracy: 0.8470
Epoch 75/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5575 - accuracy: 0.8468 - val_loss: 0.5242 - val_accuracy: 0.8470
Epoch 76/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5554 - accuracy: 0.8427 - val_loss: 0.5227 - val_accuracy: 0.8470
Epoch 77/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5383 - accuracy: 0.8482 - val_loss: 0.5213 - val_accuracy: 0.8470
Epoch 78/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5523 - accuracy: 0.8482 - val_loss: 0.5199 - val_accuracy: 0.8470
Epoch 79/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5451 - accuracy: 0.8509 - val_loss: 0.5186 - val_accuracy: 0.8470
Epoch 80/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5307 - accuracy: 0.8523 - val_loss: 0.5172 - val_accuracy: 0.8470
Epoch 81/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5370 - accuracy: 0.8454 - val_loss: 0.5159 - val_accuracy: 0.8470
Epoch 82/100
3/3 [==============================] - 0s 24ms/step - loss: 0.5570 - accuracy: 0.8468 - val_loss: 0.5147 - val_accuracy: 0.8470
Epoch 83/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5425 - accuracy: 0.8454 - val_loss: 0.5134 - val_accuracy: 0.8470
Epoch 84/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5381 - accuracy: 0.8482 - val_loss: 0.5122 - val_accuracy: 0.8470
Epoch 85/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5301 - accuracy: 0.8440 - val_loss: 0.5110 - val_accuracy: 0.8470
Epoch 86/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5196 - accuracy: 0.8550 - val_loss: 0.5099 - val_accuracy: 0.8470
Epoch 87/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5379 - accuracy: 0.8482 - val_loss: 0.5088 - val_accuracy: 0.8470
Epoch 88/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5343 - accuracy: 0.8495 - val_loss: 0.5077 - val_accuracy: 0.8470
Epoch 89/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5380 - accuracy: 0.8468 - val_loss: 0.5066 - val_accuracy: 0.8470
Epoch 90/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5428 - accuracy: 0.8482 - val_loss: 0.5056 - val_accuracy: 0.8470
Epoch 91/100
3/3 [==============================] - 0s 25ms/step - loss: 0.5145 - accuracy: 0.8482 - val_loss: 0.5046 - val_accuracy: 0.8470
Epoch 92/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5270 - accuracy: 0.8482 - val_loss: 0.5036 - val_accuracy: 0.8470
Epoch 93/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5438 - accuracy: 0.8454 - val_loss: 0.5026 - val_accuracy: 0.8470
Epoch 94/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5322 - accuracy: 0.8495 - val_loss: 0.5017 - val_accuracy: 0.8470
Epoch 95/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5121 - accuracy: 0.8482 - val_loss: 0.5008 - val_accuracy: 0.8470
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5331 - accuracy: 0.8536 - val_loss: 0.4998 - val_accuracy: 0.8470
Epoch 97/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5160 - accuracy: 0.8509 - val_loss: 0.4989 - val_accuracy: 0.8470
Epoch 98/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5115 - accuracy: 0.8440 - val_loss: 0.4980 - val_accuracy: 0.8470
Epoch 99/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5171 - accuracy: 0.8523 - val_loss: 0.4972 - val_accuracy: 0.8470
Epoch 100/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5261 - accuracy: 0.8454 - val_loss: 0.4963 - val_accuracy: 0.8470
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 8, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (731, 11)
y_current_train shape: (731, 3)
Epoch 1/100
3/3 [==============================] - 1s 107ms/step - loss: 1.7813 - accuracy: 0.2640 - val_loss: 1.8463 - val_accuracy: 0.2077
Epoch 2/100
3/3 [==============================] - 0s 26ms/step - loss: 1.8679 - accuracy: 0.2722 - val_loss: 1.8153 - val_accuracy: 0.2131
Epoch 3/100
3/3 [==============================] - 0s 20ms/step - loss: 1.7487 - accuracy: 0.2886 - val_loss: 1.7731 - val_accuracy: 0.2350
Epoch 4/100
3/3 [==============================] - 0s 17ms/step - loss: 1.7192 - accuracy: 0.2763 - val_loss: 1.7231 - val_accuracy: 0.2568
Epoch 5/100
3/3 [==============================] - 0s 16ms/step - loss: 1.7080 - accuracy: 0.3146 - val_loss: 1.6680 - val_accuracy: 0.2678
Epoch 6/100
3/3 [==============================] - 0s 21ms/step - loss: 1.6145 - accuracy: 0.3242 - val_loss: 1.6106 - val_accuracy: 0.2787
Epoch 7/100
3/3 [==============================] - 0s 14ms/step - loss: 1.6311 - accuracy: 0.3324 - val_loss: 1.5530 - val_accuracy: 0.3115
Epoch 8/100
3/3 [==============================] - 0s 18ms/step - loss: 1.5407 - accuracy: 0.3557 - val_loss: 1.4958 - val_accuracy: 0.3224
Epoch 9/100
3/3 [==============================] - 0s 17ms/step - loss: 1.5191 - accuracy: 0.3789 - val_loss: 1.4393 - val_accuracy: 0.3388
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 1.4816 - accuracy: 0.3707 - val_loss: 1.3843 - val_accuracy: 0.3661
Epoch 11/100
3/3 [==============================] - 0s 19ms/step - loss: 1.4471 - accuracy: 0.3912 - val_loss: 1.3313 - val_accuracy: 0.3880
Epoch 12/100
3/3 [==============================] - 0s 18ms/step - loss: 1.3168 - accuracy: 0.4309 - val_loss: 1.2814 - val_accuracy: 0.3880
Epoch 13/100
3/3 [==============================] - 0s 23ms/step - loss: 1.3257 - accuracy: 0.4337 - val_loss: 1.2341 - val_accuracy: 0.4153
Epoch 14/100
3/3 [==============================] - 0s 19ms/step - loss: 1.2641 - accuracy: 0.4542 - val_loss: 1.1899 - val_accuracy: 0.4481
Epoch 15/100
3/3 [==============================] - 0s 20ms/step - loss: 1.2057 - accuracy: 0.4788 - val_loss: 1.1484 - val_accuracy: 0.4699
Epoch 16/100
3/3 [==============================] - 0s 18ms/step - loss: 1.1933 - accuracy: 0.5075 - val_loss: 1.1093 - val_accuracy: 0.5082
Epoch 17/100
3/3 [==============================] - 0s 19ms/step - loss: 1.1607 - accuracy: 0.5075 - val_loss: 1.0724 - val_accuracy: 0.5246
Epoch 18/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1261 - accuracy: 0.5349 - val_loss: 1.0379 - val_accuracy: 0.5792
Epoch 19/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1025 - accuracy: 0.5718 - val_loss: 1.0056 - val_accuracy: 0.6066
Epoch 20/100
3/3 [==============================] - 0s 16ms/step - loss: 1.0604 - accuracy: 0.5814 - val_loss: 0.9756 - val_accuracy: 0.6175
Epoch 21/100
3/3 [==============================] - 0s 18ms/step - loss: 1.0175 - accuracy: 0.5978 - val_loss: 0.9474 - val_accuracy: 0.6448
Epoch 22/100
3/3 [==============================] - 0s 15ms/step - loss: 0.9953 - accuracy: 0.6115 - val_loss: 0.9212 - val_accuracy: 0.6612
Epoch 23/100
3/3 [==============================] - 0s 19ms/step - loss: 0.9802 - accuracy: 0.6224 - val_loss: 0.8968 - val_accuracy: 0.6667
Epoch 24/100
3/3 [==============================] - 0s 19ms/step - loss: 0.9465 - accuracy: 0.6293 - val_loss: 0.8740 - val_accuracy: 0.6667
Epoch 25/100
3/3 [==============================] - 0s 19ms/step - loss: 0.9547 - accuracy: 0.6293 - val_loss: 0.8524 - val_accuracy: 0.6721
Epoch 26/100
3/3 [==============================] - 0s 20ms/step - loss: 0.9395 - accuracy: 0.6566 - val_loss: 0.8320 - val_accuracy: 0.7104
Epoch 27/100
3/3 [==============================] - 0s 18ms/step - loss: 0.8998 - accuracy: 0.6936 - val_loss: 0.8129 - val_accuracy: 0.7322
Epoch 28/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8926 - accuracy: 0.6826 - val_loss: 0.7953 - val_accuracy: 0.7541
Epoch 29/100
3/3 [==============================] - 0s 21ms/step - loss: 0.8706 - accuracy: 0.6826 - val_loss: 0.7786 - val_accuracy: 0.7596
Epoch 30/100
3/3 [==============================] - 0s 22ms/step - loss: 0.8283 - accuracy: 0.7428 - val_loss: 0.7632 - val_accuracy: 0.7650
Epoch 31/100
3/3 [==============================] - 0s 15ms/step - loss: 0.8479 - accuracy: 0.7264 - val_loss: 0.7485 - val_accuracy: 0.7650
Epoch 32/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8246 - accuracy: 0.7360 - val_loss: 0.7346 - val_accuracy: 0.7705
Epoch 33/100
3/3 [==============================] - 0s 20ms/step - loss: 0.8414 - accuracy: 0.7209 - val_loss: 0.7213 - val_accuracy: 0.7705
Epoch 34/100
3/3 [==============================] - 0s 21ms/step - loss: 0.7983 - accuracy: 0.7606 - val_loss: 0.7086 - val_accuracy: 0.7814
Epoch 35/100
3/3 [==============================] - 0s 18ms/step - loss: 0.8036 - accuracy: 0.7592 - val_loss: 0.6966 - val_accuracy: 0.7923
Epoch 36/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7964 - accuracy: 0.7538 - val_loss: 0.6853 - val_accuracy: 0.8087
Epoch 37/100
3/3 [==============================] - 0s 17ms/step - loss: 0.7631 - accuracy: 0.7756 - val_loss: 0.6745 - val_accuracy: 0.8142
Epoch 38/100
3/3 [==============================] - 0s 21ms/step - loss: 0.7473 - accuracy: 0.7798 - val_loss: 0.6644 - val_accuracy: 0.8251
Epoch 39/100
3/3 [==============================] - 0s 16ms/step - loss: 0.7585 - accuracy: 0.7893 - val_loss: 0.6547 - val_accuracy: 0.8306
Epoch 40/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7562 - accuracy: 0.7592 - val_loss: 0.6454 - val_accuracy: 0.8306
Epoch 41/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7336 - accuracy: 0.7852 - val_loss: 0.6367 - val_accuracy: 0.8361
Epoch 42/100
3/3 [==============================] - 0s 16ms/step - loss: 0.7273 - accuracy: 0.8003 - val_loss: 0.6284 - val_accuracy: 0.8361
Epoch 43/100
3/3 [==============================] - 0s 15ms/step - loss: 0.7344 - accuracy: 0.7839 - val_loss: 0.6207 - val_accuracy: 0.8361
Epoch 44/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7083 - accuracy: 0.8003 - val_loss: 0.6133 - val_accuracy: 0.8306
Epoch 45/100
3/3 [==============================] - 0s 17ms/step - loss: 0.7145 - accuracy: 0.8085 - val_loss: 0.6063 - val_accuracy: 0.8306
Epoch 46/100
3/3 [==============================] - 1s 275ms/step - loss: 0.6973 - accuracy: 0.8153 - val_loss: 0.5998 - val_accuracy: 0.8306
Epoch 47/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6852 - accuracy: 0.8085 - val_loss: 0.5934 - val_accuracy: 0.8306
Epoch 48/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6818 - accuracy: 0.8167 - val_loss: 0.5873 - val_accuracy: 0.8306
Epoch 49/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6684 - accuracy: 0.8112 - val_loss: 0.5815 - val_accuracy: 0.8306
Epoch 50/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6652 - accuracy: 0.8153 - val_loss: 0.5760 - val_accuracy: 0.8251
Epoch 51/100
3/3 [==============================] - 0s 15ms/step - loss: 0.6900 - accuracy: 0.7975 - val_loss: 0.5707 - val_accuracy: 0.8251
Epoch 52/100
3/3 [==============================] - 0s 22ms/step - loss: 0.6540 - accuracy: 0.8276 - val_loss: 0.5656 - val_accuracy: 0.8142
Epoch 53/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6659 - accuracy: 0.8222 - val_loss: 0.5609 - val_accuracy: 0.8197
Epoch 54/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6522 - accuracy: 0.8235 - val_loss: 0.5563 - val_accuracy: 0.8197
Epoch 55/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6436 - accuracy: 0.8235 - val_loss: 0.5518 - val_accuracy: 0.8197
Epoch 56/100
3/3 [==============================] - 0s 25ms/step - loss: 0.6446 - accuracy: 0.8167 - val_loss: 0.5473 - val_accuracy: 0.8251
Epoch 57/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6267 - accuracy: 0.8304 - val_loss: 0.5431 - val_accuracy: 0.8251
Epoch 58/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6432 - accuracy: 0.8304 - val_loss: 0.5391 - val_accuracy: 0.8361
Epoch 59/100
3/3 [==============================] - 0s 15ms/step - loss: 0.6363 - accuracy: 0.8290 - val_loss: 0.5353 - val_accuracy: 0.8361
Epoch 60/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6350 - accuracy: 0.8304 - val_loss: 0.5315 - val_accuracy: 0.8361
Epoch 61/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6485 - accuracy: 0.8112 - val_loss: 0.5279 - val_accuracy: 0.8361
Epoch 62/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6156 - accuracy: 0.8372 - val_loss: 0.5243 - val_accuracy: 0.8361
Epoch 63/100
3/3 [==============================] - 0s 13ms/step - loss: 0.6290 - accuracy: 0.8317 - val_loss: 0.5209 - val_accuracy: 0.8361
Epoch 64/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6302 - accuracy: 0.8276 - val_loss: 0.5175 - val_accuracy: 0.8415
Epoch 65/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6134 - accuracy: 0.8290 - val_loss: 0.5144 - val_accuracy: 0.8415
Epoch 66/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6163 - accuracy: 0.8235 - val_loss: 0.5113 - val_accuracy: 0.8415
Epoch 67/100
3/3 [==============================] - 0s 21ms/step - loss: 0.6000 - accuracy: 0.8358 - val_loss: 0.5084 - val_accuracy: 0.8415
Epoch 68/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5941 - accuracy: 0.8454 - val_loss: 0.5054 - val_accuracy: 0.8415
Epoch 69/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5885 - accuracy: 0.8454 - val_loss: 0.5027 - val_accuracy: 0.8415
Epoch 70/100
3/3 [==============================] - 0s 25ms/step - loss: 0.5932 - accuracy: 0.8413 - val_loss: 0.5001 - val_accuracy: 0.8415
Epoch 71/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5857 - accuracy: 0.8290 - val_loss: 0.4975 - val_accuracy: 0.8470
Epoch 72/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5889 - accuracy: 0.8427 - val_loss: 0.4950 - val_accuracy: 0.8470
Epoch 73/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5804 - accuracy: 0.8263 - val_loss: 0.4925 - val_accuracy: 0.8525
Epoch 74/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5960 - accuracy: 0.8372 - val_loss: 0.4902 - val_accuracy: 0.8525
Epoch 75/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5747 - accuracy: 0.8440 - val_loss: 0.4879 - val_accuracy: 0.8525
Epoch 76/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5904 - accuracy: 0.8358 - val_loss: 0.4857 - val_accuracy: 0.8525
Epoch 77/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5656 - accuracy: 0.8482 - val_loss: 0.4836 - val_accuracy: 0.8470
Epoch 78/100
3/3 [==============================] - 0s 22ms/step - loss: 0.5694 - accuracy: 0.8482 - val_loss: 0.4816 - val_accuracy: 0.8470
Epoch 79/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5762 - accuracy: 0.8427 - val_loss: 0.4797 - val_accuracy: 0.8470
Epoch 80/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5696 - accuracy: 0.8317 - val_loss: 0.4778 - val_accuracy: 0.8470
Epoch 81/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5675 - accuracy: 0.8495 - val_loss: 0.4760 - val_accuracy: 0.8470
Epoch 82/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5815 - accuracy: 0.8345 - val_loss: 0.4743 - val_accuracy: 0.8470
Epoch 83/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5792 - accuracy: 0.8413 - val_loss: 0.4725 - val_accuracy: 0.8470
Epoch 84/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5504 - accuracy: 0.8454 - val_loss: 0.4708 - val_accuracy: 0.8525
Epoch 85/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5673 - accuracy: 0.8331 - val_loss: 0.4691 - val_accuracy: 0.8579
Epoch 86/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5896 - accuracy: 0.8399 - val_loss: 0.4676 - val_accuracy: 0.8579
Epoch 87/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5541 - accuracy: 0.8427 - val_loss: 0.4661 - val_accuracy: 0.8579
Epoch 88/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5384 - accuracy: 0.8495 - val_loss: 0.4647 - val_accuracy: 0.8579
Epoch 89/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5424 - accuracy: 0.8509 - val_loss: 0.4633 - val_accuracy: 0.8579
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5548 - accuracy: 0.8427 - val_loss: 0.4619 - val_accuracy: 0.8634
Epoch 91/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5520 - accuracy: 0.8358 - val_loss: 0.4605 - val_accuracy: 0.8634
Epoch 92/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5348 - accuracy: 0.8482 - val_loss: 0.4592 - val_accuracy: 0.8634
Epoch 93/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5596 - accuracy: 0.8290 - val_loss: 0.4578 - val_accuracy: 0.8634
Epoch 94/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5484 - accuracy: 0.8495 - val_loss: 0.4565 - val_accuracy: 0.8634
Epoch 95/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5198 - accuracy: 0.8454 - val_loss: 0.4552 - val_accuracy: 0.8579
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5556 - accuracy: 0.8331 - val_loss: 0.4539 - val_accuracy: 0.8579
Epoch 97/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5294 - accuracy: 0.8509 - val_loss: 0.4527 - val_accuracy: 0.8579
Epoch 98/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5400 - accuracy: 0.8523 - val_loss: 0.4515 - val_accuracy: 0.8579
Epoch 99/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5493 - accuracy: 0.8413 - val_loss: 0.4503 - val_accuracy: 0.8579
Epoch 100/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5198 - accuracy: 0.8536 - val_loss: 0.4492 - val_accuracy: 0.8579
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 4, 'hidden_units': 8, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None}
Batch size: 256
X_current_train shape: (732, 11)
y_current_train shape: (732, 3)
Epoch 1/100
3/3 [==============================] - 1s 118ms/step - loss: 1.2385 - accuracy: 0.4877 - val_loss: 1.2141 - val_accuracy: 0.4286
Epoch 2/100
3/3 [==============================] - 0s 17ms/step - loss: 1.2115 - accuracy: 0.4904 - val_loss: 1.2008 - val_accuracy: 0.4505
Epoch 3/100
3/3 [==============================] - 0s 18ms/step - loss: 1.2312 - accuracy: 0.5082 - val_loss: 1.1824 - val_accuracy: 0.4505
Epoch 4/100
3/3 [==============================] - 0s 19ms/step - loss: 1.2031 - accuracy: 0.5014 - val_loss: 1.1605 - val_accuracy: 0.4615
Epoch 5/100
3/3 [==============================] - 0s 23ms/step - loss: 1.1505 - accuracy: 0.5478 - val_loss: 1.1369 - val_accuracy: 0.4780
Epoch 6/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1251 - accuracy: 0.5574 - val_loss: 1.1125 - val_accuracy: 0.4835
Epoch 7/100
3/3 [==============================] - 0s 21ms/step - loss: 1.1086 - accuracy: 0.5519 - val_loss: 1.0880 - val_accuracy: 0.5000
Epoch 8/100
3/3 [==============================] - 0s 16ms/step - loss: 1.1127 - accuracy: 0.5560 - val_loss: 1.0636 - val_accuracy: 0.5220
Epoch 9/100
3/3 [==============================] - 0s 19ms/step - loss: 1.0670 - accuracy: 0.5683 - val_loss: 1.0396 - val_accuracy: 0.5385
Epoch 10/100
3/3 [==============================] - 0s 19ms/step - loss: 1.0444 - accuracy: 0.5765 - val_loss: 1.0160 - val_accuracy: 0.5549
Epoch 11/100
3/3 [==============================] - 0s 16ms/step - loss: 1.0619 - accuracy: 0.5847 - val_loss: 0.9933 - val_accuracy: 0.5659
Epoch 12/100
3/3 [==============================] - 0s 20ms/step - loss: 0.9941 - accuracy: 0.6366 - val_loss: 0.9713 - val_accuracy: 0.6044
Epoch 13/100
3/3 [==============================] - 0s 19ms/step - loss: 0.9924 - accuracy: 0.6462 - val_loss: 0.9504 - val_accuracy: 0.6538
Epoch 14/100
3/3 [==============================] - 0s 20ms/step - loss: 0.9784 - accuracy: 0.6421 - val_loss: 0.9305 - val_accuracy: 0.6978
Epoch 15/100
3/3 [==============================] - 0s 15ms/step - loss: 0.9337 - accuracy: 0.6585 - val_loss: 0.9113 - val_accuracy: 0.7143
Epoch 16/100
3/3 [==============================] - 0s 18ms/step - loss: 0.9499 - accuracy: 0.6516 - val_loss: 0.8932 - val_accuracy: 0.7363
Epoch 17/100
3/3 [==============================] - 0s 26ms/step - loss: 0.9215 - accuracy: 0.6913 - val_loss: 0.8758 - val_accuracy: 0.7582
Epoch 18/100
3/3 [==============================] - 0s 22ms/step - loss: 0.8794 - accuracy: 0.7022 - val_loss: 0.8595 - val_accuracy: 0.7637
Epoch 19/100
3/3 [==============================] - 0s 22ms/step - loss: 0.9107 - accuracy: 0.7008 - val_loss: 0.8438 - val_accuracy: 0.7802
Epoch 20/100
3/3 [==============================] - 0s 19ms/step - loss: 0.8815 - accuracy: 0.7036 - val_loss: 0.8289 - val_accuracy: 0.7967
Epoch 21/100
3/3 [==============================] - 0s 18ms/step - loss: 0.8678 - accuracy: 0.7199 - val_loss: 0.8145 - val_accuracy: 0.8022
Epoch 22/100
3/3 [==============================] - 0s 15ms/step - loss: 0.8544 - accuracy: 0.7213 - val_loss: 0.8011 - val_accuracy: 0.8187
Epoch 23/100
3/3 [==============================] - 0s 16ms/step - loss: 0.8479 - accuracy: 0.7445 - val_loss: 0.7881 - val_accuracy: 0.8187
Epoch 24/100
3/3 [==============================] - 0s 18ms/step - loss: 0.8133 - accuracy: 0.7596 - val_loss: 0.7760 - val_accuracy: 0.8242
Epoch 25/100
3/3 [==============================] - 0s 21ms/step - loss: 0.8059 - accuracy: 0.7555 - val_loss: 0.7644 - val_accuracy: 0.8352
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7985 - accuracy: 0.7623 - val_loss: 0.7534 - val_accuracy: 0.8352
Epoch 27/100
3/3 [==============================] - 0s 15ms/step - loss: 0.8100 - accuracy: 0.7637 - val_loss: 0.7429 - val_accuracy: 0.8407
Epoch 28/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7782 - accuracy: 0.7650 - val_loss: 0.7329 - val_accuracy: 0.8407
Epoch 29/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7589 - accuracy: 0.7773 - val_loss: 0.7234 - val_accuracy: 0.8407
Epoch 30/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7835 - accuracy: 0.7609 - val_loss: 0.7144 - val_accuracy: 0.8462
Epoch 31/100
3/3 [==============================] - 0s 16ms/step - loss: 0.7603 - accuracy: 0.7773 - val_loss: 0.7057 - val_accuracy: 0.8516
Epoch 32/100
3/3 [==============================] - 0s 21ms/step - loss: 0.7541 - accuracy: 0.7910 - val_loss: 0.6974 - val_accuracy: 0.8516
Epoch 33/100
3/3 [==============================] - 0s 17ms/step - loss: 0.7351 - accuracy: 0.8019 - val_loss: 0.6896 - val_accuracy: 0.8516
Epoch 34/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7119 - accuracy: 0.8046 - val_loss: 0.6820 - val_accuracy: 0.8462
Epoch 35/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7252 - accuracy: 0.8033 - val_loss: 0.6748 - val_accuracy: 0.8462
Epoch 36/100
3/3 [==============================] - 0s 18ms/step - loss: 0.7277 - accuracy: 0.8046 - val_loss: 0.6680 - val_accuracy: 0.8516
Epoch 37/100
3/3 [==============================] - 0s 22ms/step - loss: 0.7153 - accuracy: 0.7978 - val_loss: 0.6613 - val_accuracy: 0.8516
Epoch 38/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6973 - accuracy: 0.8046 - val_loss: 0.6549 - val_accuracy: 0.8516
Epoch 39/100
3/3 [==============================] - 0s 19ms/step - loss: 0.7080 - accuracy: 0.7978 - val_loss: 0.6488 - val_accuracy: 0.8516
Epoch 40/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7015 - accuracy: 0.8005 - val_loss: 0.6430 - val_accuracy: 0.8516
Epoch 41/100
3/3 [==============================] - 0s 15ms/step - loss: 0.7019 - accuracy: 0.7937 - val_loss: 0.6373 - val_accuracy: 0.8516
Epoch 42/100
3/3 [==============================] - 0s 25ms/step - loss: 0.7041 - accuracy: 0.8019 - val_loss: 0.6318 - val_accuracy: 0.8516
Epoch 43/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6854 - accuracy: 0.8156 - val_loss: 0.6267 - val_accuracy: 0.8516
Epoch 44/100
3/3 [==============================] - 0s 20ms/step - loss: 0.7014 - accuracy: 0.8115 - val_loss: 0.6217 - val_accuracy: 0.8516
Epoch 45/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6766 - accuracy: 0.8238 - val_loss: 0.6169 - val_accuracy: 0.8516
Epoch 46/100
3/3 [==============================] - 0s 14ms/step - loss: 0.6693 - accuracy: 0.8142 - val_loss: 0.6123 - val_accuracy: 0.8571
Epoch 47/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6674 - accuracy: 0.8197 - val_loss: 0.6078 - val_accuracy: 0.8571
Epoch 48/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6612 - accuracy: 0.8142 - val_loss: 0.6035 - val_accuracy: 0.8571
Epoch 49/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6498 - accuracy: 0.8251 - val_loss: 0.5994 - val_accuracy: 0.8571
Epoch 50/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6651 - accuracy: 0.8333 - val_loss: 0.5955 - val_accuracy: 0.8571
Epoch 51/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6732 - accuracy: 0.8197 - val_loss: 0.5916 - val_accuracy: 0.8571
Epoch 52/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6368 - accuracy: 0.8265 - val_loss: 0.5879 - val_accuracy: 0.8571
Epoch 53/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6363 - accuracy: 0.8265 - val_loss: 0.5844 - val_accuracy: 0.8571
Epoch 54/100
3/3 [==============================] - 0s 19ms/step - loss: 0.6387 - accuracy: 0.8238 - val_loss: 0.5810 - val_accuracy: 0.8571
Epoch 55/100
3/3 [==============================] - 0s 17ms/step - loss: 0.6416 - accuracy: 0.8292 - val_loss: 0.5776 - val_accuracy: 0.8571
Epoch 56/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6246 - accuracy: 0.8320 - val_loss: 0.5744 - val_accuracy: 0.8571
Epoch 57/100
3/3 [==============================] - 0s 16ms/step - loss: 0.6330 - accuracy: 0.8347 - val_loss: 0.5713 - val_accuracy: 0.8571
Epoch 58/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6385 - accuracy: 0.8224 - val_loss: 0.5682 - val_accuracy: 0.8571
Epoch 59/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6431 - accuracy: 0.8251 - val_loss: 0.5652 - val_accuracy: 0.8571
Epoch 60/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6094 - accuracy: 0.8415 - val_loss: 0.5623 - val_accuracy: 0.8571
Epoch 61/100
3/3 [==============================] - 0s 41ms/step - loss: 0.6275 - accuracy: 0.8333 - val_loss: 0.5595 - val_accuracy: 0.8571
Epoch 62/100
3/3 [==============================] - 0s 23ms/step - loss: 0.6223 - accuracy: 0.8279 - val_loss: 0.5568 - val_accuracy: 0.8571
Epoch 63/100
3/3 [==============================] - 0s 28ms/step - loss: 0.5900 - accuracy: 0.8374 - val_loss: 0.5542 - val_accuracy: 0.8571
Epoch 64/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6031 - accuracy: 0.8279 - val_loss: 0.5516 - val_accuracy: 0.8571
Epoch 65/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6231 - accuracy: 0.8347 - val_loss: 0.5491 - val_accuracy: 0.8571
Epoch 66/100
3/3 [==============================] - 0s 24ms/step - loss: 0.5971 - accuracy: 0.8361 - val_loss: 0.5467 - val_accuracy: 0.8571
Epoch 67/100
3/3 [==============================] - 0s 22ms/step - loss: 0.6014 - accuracy: 0.8251 - val_loss: 0.5443 - val_accuracy: 0.8571
Epoch 68/100
3/3 [==============================] - 0s 18ms/step - loss: 0.6017 - accuracy: 0.8333 - val_loss: 0.5419 - val_accuracy: 0.8571
Epoch 69/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5947 - accuracy: 0.8374 - val_loss: 0.5397 - val_accuracy: 0.8571
Epoch 70/100
3/3 [==============================] - 0s 20ms/step - loss: 0.6047 - accuracy: 0.8279 - val_loss: 0.5374 - val_accuracy: 0.8626
Epoch 71/100
3/3 [==============================] - 0s 14ms/step - loss: 0.6007 - accuracy: 0.8265 - val_loss: 0.5352 - val_accuracy: 0.8626
Epoch 72/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5960 - accuracy: 0.8374 - val_loss: 0.5331 - val_accuracy: 0.8626
Epoch 73/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5859 - accuracy: 0.8361 - val_loss: 0.5311 - val_accuracy: 0.8626
Epoch 74/100
3/3 [==============================] - 0s 24ms/step - loss: 0.5802 - accuracy: 0.8402 - val_loss: 0.5291 - val_accuracy: 0.8626
Epoch 75/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5750 - accuracy: 0.8443 - val_loss: 0.5272 - val_accuracy: 0.8626
Epoch 76/100
3/3 [==============================] - 0s 14ms/step - loss: 0.5944 - accuracy: 0.8388 - val_loss: 0.5252 - val_accuracy: 0.8626
Epoch 77/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5739 - accuracy: 0.8443 - val_loss: 0.5233 - val_accuracy: 0.8626
Epoch 78/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5758 - accuracy: 0.8347 - val_loss: 0.5215 - val_accuracy: 0.8626
Epoch 79/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5733 - accuracy: 0.8429 - val_loss: 0.5197 - val_accuracy: 0.8626
Epoch 80/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5642 - accuracy: 0.8374 - val_loss: 0.5180 - val_accuracy: 0.8626
Epoch 81/100
3/3 [==============================] - 0s 21ms/step - loss: 0.5606 - accuracy: 0.8429 - val_loss: 0.5163 - val_accuracy: 0.8626
Epoch 82/100
3/3 [==============================] - 0s 15ms/step - loss: 0.5811 - accuracy: 0.8402 - val_loss: 0.5146 - val_accuracy: 0.8626
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5732 - accuracy: 0.8388 - val_loss: 0.5130 - val_accuracy: 0.8626
Epoch 84/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5588 - accuracy: 0.8374 - val_loss: 0.5114 - val_accuracy: 0.8626
Epoch 85/100
3/3 [==============================] - 0s 23ms/step - loss: 0.5613 - accuracy: 0.8470 - val_loss: 0.5097 - val_accuracy: 0.8626
Epoch 86/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5703 - accuracy: 0.8388 - val_loss: 0.5082 - val_accuracy: 0.8626
Epoch 87/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5581 - accuracy: 0.8429 - val_loss: 0.5066 - val_accuracy: 0.8626
Epoch 88/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5670 - accuracy: 0.8347 - val_loss: 0.5051 - val_accuracy: 0.8626
Epoch 89/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5466 - accuracy: 0.8470 - val_loss: 0.5036 - val_accuracy: 0.8626
Epoch 90/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5529 - accuracy: 0.8402 - val_loss: 0.5021 - val_accuracy: 0.8626
Epoch 91/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5288 - accuracy: 0.8443 - val_loss: 0.5007 - val_accuracy: 0.8626
Epoch 92/100
3/3 [==============================] - 0s 16ms/step - loss: 0.5541 - accuracy: 0.8429 - val_loss: 0.4993 - val_accuracy: 0.8626
Epoch 93/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5497 - accuracy: 0.8361 - val_loss: 0.4979 - val_accuracy: 0.8626
Epoch 94/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5505 - accuracy: 0.8456 - val_loss: 0.4965 - val_accuracy: 0.8626
Epoch 95/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5645 - accuracy: 0.8361 - val_loss: 0.4952 - val_accuracy: 0.8626
Epoch 96/100
3/3 [==============================] - 0s 20ms/step - loss: 0.5543 - accuracy: 0.8347 - val_loss: 0.4939 - val_accuracy: 0.8626
Epoch 97/100
3/3 [==============================] - 0s 19ms/step - loss: 0.5446 - accuracy: 0.8470 - val_loss: 0.4926 - val_accuracy: 0.8626
Epoch 98/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5444 - accuracy: 0.8484 - val_loss: 0.4914 - val_accuracy: 0.8626
Epoch 99/100
3/3 [==============================] - 0s 17ms/step - loss: 0.5445 - accuracy: 0.8456 - val_loss: 0.4902 - val_accuracy: 0.8626
Epoch 100/100
3/3 [==============================] - 0s 18ms/step - loss: 0.5424 - accuracy: 0.8402 - val_loss: 0.4890 - val_accuracy: 0.8626
No description has been provided for this image
No description has been provided for this image 
6/6 [==============================] - 0s 1ms/step
Best score: 0.8610640725394824
Best parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 16, 'batch_size': 512, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'rho': 0.99}
Best model is in 10 experiment

Experiment 1 Result Analysis¶

The provided best score indicates a good level of accuracy; however, it shows a sign of overfitting. T If the model's accuracy on the training santly higher than its accuracy on the validatio.nte mmy's ability to geneI will

In your next experiment, you can implement batch normalization by addmodeltion layers i. It is normallyural neDenseure, typand y after fully connected layers buAnd I will functions). It is also advisable to monitor both training and validation metrics closely to determine if batch normalization helps in reducing the gap between training and validation performance, which would be a good indicator of mitigated overfitting.

Step 6: Scale up — Experiment 2: Kfold = 10, batch_normalization¶

In the next experiment, I will add batch normalization function.

  • Batch Normalization: True, False

Batch normalization is a technique to provide any layer in a neural network with inputs that are zero mean/unit variance, which helps to stabilize the training process.

In [65]:
n_splits=10
cross_validator = KFold(n_splits=n_splits, shuffle=True, random_state=42)

def create_model(hidden_units, hidden_layers, optimizer, dropout_rate, l1, l2, learning_rate, adam_beta_1=None, adam_beta_2=None, momentum=None, learning_rate_decay=None, rho=None, batch_norm=False):
    model = models.Sequential()
    model.add(layers.Dense(hidden_units, activation='relu', input_shape=(11,), kernel_regularizer=regularizers.l1_l2(l1=l1, l2=l2)))
    if batch_norm == True:
        model.add(layers.BatchNormalization())
    model.add(layers.Dropout(dropout_rate))
    model.add(layers.Dense(3, activation='softmax'))
    
    if optimizer == 'Adam':
        if adam_beta_1 is not None and adam_beta_2 is not None:
            optimizer = Adam(learning_rate=learning_rate, beta_1=adam_beta_1, beta_2=adam_beta_2)
    elif optimizer == 'RMSprop':
        optimizer = RMSprop(learning_rate=learning_rate, rho=rho)
    elif optimizer == 'momentum':
        optimizer = SGD(learning_rate=learning_rate, momentum=momentum)
    else:
        raise ValueError("Unknown optimizer")
    # I am not sure how to handle the parameter of different optimizers. I asked GPT4 about it, GPT4 paid version, accessed on Jan 25th.
        
    model.compile(loss='categorical_crossentropy', optimizer=optimizer, metrics=['accuracy'])
    return model
In [66]:
learning_rate = [
    10 ** -i for i in range(1, 6)
]
hidden_layers = [
    1, 2, 3, 4, 5,
]
hidden_units = [
    8, 16, 32, 64, 128, 256,
]
batch_size = [
    128, 256, 512,
]
optimizer = [
    'momentum', 'RMSprop', 'Adam',
]
dropout_rate = [0.2, 0.3, 0.4,]

l1=[0.001, 0.01, 0.1,]
l2=[0.001, 0.01, 0.1,]

momentum = [
    0.8, 0.9, 0.99, 0.999,
]
learning_rate_decay = [lr/100 for lr in learning_rate]

rho = [0.8, 0.9, 0.99]

adam_beta_1 = [0.9, 0.95]
adam_beta_2 = [0.999, 0.9995]

batch_norm = [True, False]

param_space = {
    'learning_rate': learning_rate,
    'hidden_layers': hidden_layers,
    'hidden_units': hidden_units,
    'batch_size': batch_size,
    'learning_rate_decay': learning_rate_decay,
    'optimizer': optimizer,
    'l1': l1,
    'l2': l2,
    'dropout_rate': dropout_rate,
    'momentum': momentum if 'momentum' in optimizer else [None],
    'adam_beta_1': adam_beta_1 if 'Adam' in optimizer else [None],
    'adam_beta_2': adam_beta_2 if 'Adam' in optimizer else [None],
    'rho': rho if 'RMSprop' in optimizer else [None],
    'batch_norm': batch_norm,
}
In [67]:
n_iter = 10
best_score = 0
best_params = {}

for i in range(n_iter):
    print(f"Experiment number: {i+1}")
    sampled_params = {k: np.random.choice(list(v)) for k,v in param_space.items()} # use random search
    model_params = {k:v for k, v in sampled_params.items() if k != 'batch_size'}
    if model_params['optimizer'] != 'momentum':
        model_params['momentum'] = None
    if model_params['optimizer'] != 'Adam':
        model_params['adam_beta_1'] = None
        model_params['adam_beta_2'] = None
    if model_params['optimizer'] != 'RMSprop':
        model_params['rho'] = None

    cv_scores = []
    for train_index, val_index in cross_validator.split(X_train):
        X_current_train, X_val = X_train[train_index], X_train[val_index]
        y_current_train, y_val = y_train[train_index], y_train[val_index]
        model = create_model(**model_params)
        print("Model parameters:", model_params)
        print("Batch size:", sampled_params['batch_size'])
        print("X_current_train shape:", X_current_train.shape)
        print("y_current_train shape:", y_current_train.shape)
        history = model.fit(
            X_current_train, y_current_train, 
            epochs=100, 
            batch_size=sampled_params['batch_size'],
            verbose=1,
            validation_data=(X_val, y_val)
        )
        plot_loss(history)
        plot_accuracy(history)
        y_val_pred = model.predict(X_val) 
        y_val_pred_classes = np.argmax(y_val_pred, axis=1)
        y_true_classes = np.argmax(y_val, axis=1)
        
        scoring = accuracy_score(y_true_classes, y_val_pred_classes)
        cv_scores.append(scoring)
    mean_cv_scores = np.mean(cv_scores)
        
    if mean_cv_scores > best_score:
        best_score = mean_cv_scores
        if sampled_params['optimizer'] == 'momentum':
            sampled_params['adam_beta_1'] = None
            sampled_params['adam_beta_2'] = None
            sampled_params['rho'] = None
        if sampled_params['optimizer'] == 'RMSprop':
            sampled_params['adam_beta_1'] = None
            sampled_params['adam_beta_2'] = None
            sampled_params['momentum'] = None
        if sampled_params['optimizer'] == 'Adam':
            sampled_params['momentum'] = None
            sampled_params['rho'] = None
        best_params = {k: v for k, v in sampled_params.items() if v is not None}
               
print("Best score:", best_score)
print("Best parameters:", best_params)
print(f"Best model is in {i+1} experiment")

Experiment number: 1
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 261ms/step - loss: 1.9773 - accuracy: 0.3613 - val_loss: 1.5196 - val_accuracy: 0.4457
Epoch 2/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9989 - accuracy: 0.3358 - val_loss: 1.5157 - val_accuracy: 0.4457
Epoch 3/100
2/2 [==============================] - 0s 46ms/step - loss: 1.9881 - accuracy: 0.3540 - val_loss: 1.5118 - val_accuracy: 0.4565
Epoch 4/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9547 - accuracy: 0.3589 - val_loss: 1.5079 - val_accuracy: 0.4783
Epoch 5/100
2/2 [==============================] - 0s 54ms/step - loss: 1.9049 - accuracy: 0.3662 - val_loss: 1.5039 - val_accuracy: 0.4783
Epoch 6/100
2/2 [==============================] - 0s 46ms/step - loss: 1.9287 - accuracy: 0.3382 - val_loss: 1.5000 - val_accuracy: 0.4891
Epoch 7/100
2/2 [==============================] - 0s 100ms/step - loss: 1.8880 - accuracy: 0.3650 - val_loss: 1.4961 - val_accuracy: 0.5109
Epoch 8/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8680 - accuracy: 0.3759 - val_loss: 1.4922 - val_accuracy: 0.5109
Epoch 9/100
2/2 [==============================] - 0s 46ms/step - loss: 1.8788 - accuracy: 0.3564 - val_loss: 1.4883 - val_accuracy: 0.5217
Epoch 10/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8058 - accuracy: 0.3735 - val_loss: 1.4845 - val_accuracy: 0.5326
Epoch 11/100
2/2 [==============================] - 0s 45ms/step - loss: 1.8246 - accuracy: 0.3650 - val_loss: 1.4807 - val_accuracy: 0.5435
Epoch 12/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7853 - accuracy: 0.4027 - val_loss: 1.4769 - val_accuracy: 0.5652
Epoch 13/100
2/2 [==============================] - 0s 44ms/step - loss: 1.8134 - accuracy: 0.3662 - val_loss: 1.4732 - val_accuracy: 0.5652
Epoch 14/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7594 - accuracy: 0.3783 - val_loss: 1.4695 - val_accuracy: 0.5978
Epoch 15/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7638 - accuracy: 0.3893 - val_loss: 1.4658 - val_accuracy: 0.5870
Epoch 16/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7539 - accuracy: 0.3954 - val_loss: 1.4621 - val_accuracy: 0.5761
Epoch 17/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7492 - accuracy: 0.3929 - val_loss: 1.4584 - val_accuracy: 0.5761
Epoch 18/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6875 - accuracy: 0.4221 - val_loss: 1.4546 - val_accuracy: 0.5761
Epoch 19/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7033 - accuracy: 0.4088 - val_loss: 1.4510 - val_accuracy: 0.5978
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7048 - accuracy: 0.3844 - val_loss: 1.4473 - val_accuracy: 0.5978
Epoch 21/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6317 - accuracy: 0.4465 - val_loss: 1.4436 - val_accuracy: 0.6087
Epoch 22/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6654 - accuracy: 0.4367 - val_loss: 1.4400 - val_accuracy: 0.6087
Epoch 23/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6299 - accuracy: 0.4246 - val_loss: 1.4365 - val_accuracy: 0.5978
Epoch 24/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6376 - accuracy: 0.4319 - val_loss: 1.4329 - val_accuracy: 0.5978
Epoch 25/100
2/2 [==============================] - 0s 52ms/step - loss: 1.5977 - accuracy: 0.4732 - val_loss: 1.4294 - val_accuracy: 0.5978
Epoch 26/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6070 - accuracy: 0.4659 - val_loss: 1.4259 - val_accuracy: 0.6087
Epoch 27/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5828 - accuracy: 0.4708 - val_loss: 1.4224 - val_accuracy: 0.6196
Epoch 28/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5558 - accuracy: 0.4842 - val_loss: 1.4189 - val_accuracy: 0.6196
Epoch 29/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5686 - accuracy: 0.4526 - val_loss: 1.4155 - val_accuracy: 0.6304
Epoch 30/100
2/2 [==============================] - 0s 45ms/step - loss: 1.5538 - accuracy: 0.4781 - val_loss: 1.4121 - val_accuracy: 0.6304
Epoch 31/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5459 - accuracy: 0.5231 - val_loss: 1.4087 - val_accuracy: 0.6304
Epoch 32/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5391 - accuracy: 0.4757 - val_loss: 1.4053 - val_accuracy: 0.6630
Epoch 33/100
2/2 [==============================] - 0s 52ms/step - loss: 1.5182 - accuracy: 0.4939 - val_loss: 1.4021 - val_accuracy: 0.6739
Epoch 34/100
2/2 [==============================] - 0s 53ms/step - loss: 1.5419 - accuracy: 0.4964 - val_loss: 1.3988 - val_accuracy: 0.6739
Epoch 35/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5176 - accuracy: 0.5122 - val_loss: 1.3955 - val_accuracy: 0.6957
Epoch 36/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5144 - accuracy: 0.5304 - val_loss: 1.3923 - val_accuracy: 0.6957
Epoch 37/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5415 - accuracy: 0.5036 - val_loss: 1.3891 - val_accuracy: 0.6957
Epoch 38/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5089 - accuracy: 0.5207 - val_loss: 1.3859 - val_accuracy: 0.7065
Epoch 39/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4917 - accuracy: 0.5109 - val_loss: 1.3828 - val_accuracy: 0.7065
Epoch 40/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4956 - accuracy: 0.5207 - val_loss: 1.3797 - val_accuracy: 0.7174
Epoch 41/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4624 - accuracy: 0.5499 - val_loss: 1.3766 - val_accuracy: 0.7174
Epoch 42/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4638 - accuracy: 0.5414 - val_loss: 1.3736 - val_accuracy: 0.7174
Epoch 43/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4571 - accuracy: 0.5426 - val_loss: 1.3706 - val_accuracy: 0.7174
Epoch 44/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4688 - accuracy: 0.5572 - val_loss: 1.3677 - val_accuracy: 0.7391
Epoch 45/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4657 - accuracy: 0.5389 - val_loss: 1.3647 - val_accuracy: 0.7500
Epoch 46/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4332 - accuracy: 0.5633 - val_loss: 1.3618 - val_accuracy: 0.7500
Epoch 47/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4682 - accuracy: 0.5353 - val_loss: 1.3589 - val_accuracy: 0.7609
Epoch 48/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4928 - accuracy: 0.5401 - val_loss: 1.3561 - val_accuracy: 0.7609
Epoch 49/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4518 - accuracy: 0.5560 - val_loss: 1.3532 - val_accuracy: 0.7717
Epoch 50/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4574 - accuracy: 0.5255 - val_loss: 1.3504 - val_accuracy: 0.7717
Epoch 51/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4346 - accuracy: 0.5791 - val_loss: 1.3476 - val_accuracy: 0.7717
Epoch 52/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4601 - accuracy: 0.5730 - val_loss: 1.3449 - val_accuracy: 0.7717
Epoch 53/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4283 - accuracy: 0.5669 - val_loss: 1.3421 - val_accuracy: 0.7717
Epoch 54/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4422 - accuracy: 0.5657 - val_loss: 1.3394 - val_accuracy: 0.7717
Epoch 55/100
2/2 [==============================] - 0s 52ms/step - loss: 1.4396 - accuracy: 0.5462 - val_loss: 1.3366 - val_accuracy: 0.7717
Epoch 56/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4410 - accuracy: 0.5669 - val_loss: 1.3339 - val_accuracy: 0.7717
Epoch 57/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4440 - accuracy: 0.5657 - val_loss: 1.3312 - val_accuracy: 0.7717
Epoch 58/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3928 - accuracy: 0.6058 - val_loss: 1.3286 - val_accuracy: 0.7717
Epoch 59/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3943 - accuracy: 0.6022 - val_loss: 1.3259 - val_accuracy: 0.7717
Epoch 60/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4167 - accuracy: 0.5912 - val_loss: 1.3234 - val_accuracy: 0.7717
Epoch 61/100
2/2 [==============================] - 0s 54ms/step - loss: 1.4028 - accuracy: 0.5937 - val_loss: 1.3208 - val_accuracy: 0.7826
Epoch 62/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3819 - accuracy: 0.5998 - val_loss: 1.3182 - val_accuracy: 0.7826
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4018 - accuracy: 0.5791 - val_loss: 1.3157 - val_accuracy: 0.7826
Epoch 64/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4122 - accuracy: 0.5912 - val_loss: 1.3132 - val_accuracy: 0.7826
Epoch 65/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4048 - accuracy: 0.5791 - val_loss: 1.3106 - val_accuracy: 0.7826
Epoch 66/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3890 - accuracy: 0.5888 - val_loss: 1.3081 - val_accuracy: 0.7826
Epoch 67/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3506 - accuracy: 0.6229 - val_loss: 1.3055 - val_accuracy: 0.7935
Epoch 68/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3611 - accuracy: 0.5949 - val_loss: 1.3029 - val_accuracy: 0.7935
Epoch 69/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3927 - accuracy: 0.6083 - val_loss: 1.3003 - val_accuracy: 0.7935
Epoch 70/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3726 - accuracy: 0.5985 - val_loss: 1.2979 - val_accuracy: 0.7935
Epoch 71/100
2/2 [==============================] - 0s 52ms/step - loss: 1.3565 - accuracy: 0.6241 - val_loss: 1.2954 - val_accuracy: 0.7826
Epoch 72/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3784 - accuracy: 0.6156 - val_loss: 1.2929 - val_accuracy: 0.7826
Epoch 73/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3461 - accuracy: 0.6290 - val_loss: 1.2904 - val_accuracy: 0.7826
Epoch 74/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3266 - accuracy: 0.6229 - val_loss: 1.2879 - val_accuracy: 0.7826
Epoch 75/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3440 - accuracy: 0.6302 - val_loss: 1.2854 - val_accuracy: 0.7826
Epoch 76/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3332 - accuracy: 0.6277 - val_loss: 1.2828 - val_accuracy: 0.7826
Epoch 77/100
2/2 [==============================] - 0s 30ms/step - loss: 1.3669 - accuracy: 0.6168 - val_loss: 1.2802 - val_accuracy: 0.7826
Epoch 78/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3416 - accuracy: 0.6326 - val_loss: 1.2776 - val_accuracy: 0.7935
Epoch 79/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3425 - accuracy: 0.6436 - val_loss: 1.2750 - val_accuracy: 0.7935
Epoch 80/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3325 - accuracy: 0.6338 - val_loss: 1.2724 - val_accuracy: 0.7935
Epoch 81/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3360 - accuracy: 0.6302 - val_loss: 1.2698 - val_accuracy: 0.7935
Epoch 82/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3296 - accuracy: 0.6338 - val_loss: 1.2671 - val_accuracy: 0.7935
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3251 - accuracy: 0.6509 - val_loss: 1.2645 - val_accuracy: 0.7935
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3238 - accuracy: 0.6204 - val_loss: 1.2618 - val_accuracy: 0.7935
Epoch 85/100
2/2 [==============================] - 0s 46ms/step - loss: 1.2970 - accuracy: 0.6496 - val_loss: 1.2592 - val_accuracy: 0.7935
Epoch 86/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3006 - accuracy: 0.6350 - val_loss: 1.2567 - val_accuracy: 0.7935
Epoch 87/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3106 - accuracy: 0.6436 - val_loss: 1.2541 - val_accuracy: 0.7935
Epoch 88/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3013 - accuracy: 0.6460 - val_loss: 1.2516 - val_accuracy: 0.7935
Epoch 89/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3268 - accuracy: 0.6484 - val_loss: 1.2490 - val_accuracy: 0.7935
Epoch 90/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3196 - accuracy: 0.6387 - val_loss: 1.2464 - val_accuracy: 0.7935
Epoch 91/100
2/2 [==============================] - 0s 50ms/step - loss: 1.2725 - accuracy: 0.6606 - val_loss: 1.2439 - val_accuracy: 0.7935
Epoch 92/100
2/2 [==============================] - 0s 54ms/step - loss: 1.2766 - accuracy: 0.6715 - val_loss: 1.2413 - val_accuracy: 0.7935
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3065 - accuracy: 0.6411 - val_loss: 1.2388 - val_accuracy: 0.7935
Epoch 94/100
2/2 [==============================] - 0s 49ms/step - loss: 1.2676 - accuracy: 0.6618 - val_loss: 1.2364 - val_accuracy: 0.7935
Epoch 95/100
2/2 [==============================] - 0s 48ms/step - loss: 1.2742 - accuracy: 0.6290 - val_loss: 1.2339 - val_accuracy: 0.7935
Epoch 96/100
2/2 [==============================] - 0s 54ms/step - loss: 1.2873 - accuracy: 0.6679 - val_loss: 1.2315 - val_accuracy: 0.7935
Epoch 97/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2978 - accuracy: 0.6606 - val_loss: 1.2291 - val_accuracy: 0.7935
Epoch 98/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2599 - accuracy: 0.6630 - val_loss: 1.2267 - val_accuracy: 0.7935
Epoch 99/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2588 - accuracy: 0.6800 - val_loss: 1.2244 - val_accuracy: 0.7935
Epoch 100/100
2/2 [==============================] - 0s 28ms/step - loss: 1.2725 - accuracy: 0.6655 - val_loss: 1.2220 - val_accuracy: 0.7935
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 233ms/step - loss: 2.1902 - accuracy: 0.3248 - val_loss: 1.6922 - val_accuracy: 0.1630
Epoch 2/100
2/2 [==============================] - 0s 44ms/step - loss: 2.1261 - accuracy: 0.3443 - val_loss: 1.6847 - val_accuracy: 0.1630
Epoch 3/100
2/2 [==============================] - 0s 44ms/step - loss: 2.0799 - accuracy: 0.3662 - val_loss: 1.6774 - val_accuracy: 0.1522
Epoch 4/100
2/2 [==============================] - 0s 45ms/step - loss: 2.0399 - accuracy: 0.3723 - val_loss: 1.6701 - val_accuracy: 0.1630
Epoch 5/100
2/2 [==============================] - 0s 32ms/step - loss: 2.0243 - accuracy: 0.3613 - val_loss: 1.6627 - val_accuracy: 0.1630
Epoch 6/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9874 - accuracy: 0.3674 - val_loss: 1.6554 - val_accuracy: 0.1630
Epoch 7/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9847 - accuracy: 0.3674 - val_loss: 1.6481 - val_accuracy: 0.1630
Epoch 8/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9383 - accuracy: 0.3613 - val_loss: 1.6409 - val_accuracy: 0.1739
Epoch 9/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8900 - accuracy: 0.3723 - val_loss: 1.6338 - val_accuracy: 0.1739
Epoch 10/100
2/2 [==============================] - 0s 33ms/step - loss: 1.9104 - accuracy: 0.4039 - val_loss: 1.6267 - val_accuracy: 0.1739
Epoch 11/100
2/2 [==============================] - 0s 30ms/step - loss: 1.8584 - accuracy: 0.3710 - val_loss: 1.6197 - val_accuracy: 0.1848
Epoch 12/100
2/2 [==============================] - 0s 45ms/step - loss: 1.8563 - accuracy: 0.4015 - val_loss: 1.6127 - val_accuracy: 0.1848
Epoch 13/100
2/2 [==============================] - 0s 46ms/step - loss: 1.8310 - accuracy: 0.3662 - val_loss: 1.6058 - val_accuracy: 0.1957
Epoch 14/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7836 - accuracy: 0.3954 - val_loss: 1.5990 - val_accuracy: 0.2174
Epoch 15/100
2/2 [==============================] - 0s 45ms/step - loss: 1.8134 - accuracy: 0.3856 - val_loss: 1.5922 - val_accuracy: 0.2500
Epoch 16/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7827 - accuracy: 0.4197 - val_loss: 1.5854 - val_accuracy: 0.2826
Epoch 17/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7706 - accuracy: 0.4294 - val_loss: 1.5787 - val_accuracy: 0.2935
Epoch 18/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7753 - accuracy: 0.4100 - val_loss: 1.5721 - val_accuracy: 0.3043
Epoch 19/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7074 - accuracy: 0.4246 - val_loss: 1.5655 - val_accuracy: 0.3152
Epoch 20/100
2/2 [==============================] - 0s 45ms/step - loss: 1.7053 - accuracy: 0.4380 - val_loss: 1.5590 - val_accuracy: 0.3370
Epoch 21/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7065 - accuracy: 0.4270 - val_loss: 1.5526 - val_accuracy: 0.3478
Epoch 22/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7026 - accuracy: 0.4355 - val_loss: 1.5462 - val_accuracy: 0.3696
Epoch 23/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6826 - accuracy: 0.4477 - val_loss: 1.5400 - val_accuracy: 0.3804
Epoch 24/100
2/2 [==============================] - 0s 49ms/step - loss: 1.6323 - accuracy: 0.4574 - val_loss: 1.5339 - val_accuracy: 0.4130
Epoch 25/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6605 - accuracy: 0.4586 - val_loss: 1.5279 - val_accuracy: 0.4130
Epoch 26/100
2/2 [==============================] - 0s 54ms/step - loss: 1.6726 - accuracy: 0.4635 - val_loss: 1.5219 - val_accuracy: 0.4348
Epoch 27/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6659 - accuracy: 0.4647 - val_loss: 1.5161 - val_accuracy: 0.4565
Epoch 28/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6483 - accuracy: 0.4513 - val_loss: 1.5103 - val_accuracy: 0.4783
Epoch 29/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6192 - accuracy: 0.4866 - val_loss: 1.5046 - val_accuracy: 0.5000
Epoch 30/100
2/2 [==============================] - 0s 65ms/step - loss: 1.6035 - accuracy: 0.4781 - val_loss: 1.4990 - val_accuracy: 0.5326
Epoch 31/100
2/2 [==============================] - 0s 53ms/step - loss: 1.5754 - accuracy: 0.4903 - val_loss: 1.4935 - val_accuracy: 0.5326
Epoch 32/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6013 - accuracy: 0.4769 - val_loss: 1.4880 - val_accuracy: 0.5326
Epoch 33/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5724 - accuracy: 0.4951 - val_loss: 1.4827 - val_accuracy: 0.5326
Epoch 34/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5771 - accuracy: 0.4854 - val_loss: 1.4774 - val_accuracy: 0.5435
Epoch 35/100
2/2 [==============================] - 0s 49ms/step - loss: 1.6063 - accuracy: 0.5000 - val_loss: 1.4722 - val_accuracy: 0.5543
Epoch 36/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5919 - accuracy: 0.5061 - val_loss: 1.4671 - val_accuracy: 0.5652
Epoch 37/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5599 - accuracy: 0.5134 - val_loss: 1.4619 - val_accuracy: 0.5761
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5333 - accuracy: 0.5243 - val_loss: 1.4569 - val_accuracy: 0.5978
Epoch 39/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5524 - accuracy: 0.5328 - val_loss: 1.4521 - val_accuracy: 0.6087
Epoch 40/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5534 - accuracy: 0.5353 - val_loss: 1.4473 - val_accuracy: 0.6087
Epoch 41/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5364 - accuracy: 0.5462 - val_loss: 1.4426 - val_accuracy: 0.5978
Epoch 42/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5190 - accuracy: 0.5693 - val_loss: 1.4381 - val_accuracy: 0.6304
Epoch 43/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5006 - accuracy: 0.5487 - val_loss: 1.4335 - val_accuracy: 0.6522
Epoch 44/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5283 - accuracy: 0.5596 - val_loss: 1.4292 - val_accuracy: 0.6522
Epoch 45/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5162 - accuracy: 0.5742 - val_loss: 1.4248 - val_accuracy: 0.6630
Epoch 46/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5103 - accuracy: 0.5462 - val_loss: 1.4205 - val_accuracy: 0.6630
Epoch 47/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4974 - accuracy: 0.5450 - val_loss: 1.4163 - val_accuracy: 0.6630
Epoch 48/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5287 - accuracy: 0.5414 - val_loss: 1.4122 - val_accuracy: 0.6739
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4758 - accuracy: 0.5523 - val_loss: 1.4082 - val_accuracy: 0.6848
Epoch 50/100
2/2 [==============================] - 0s 45ms/step - loss: 1.5143 - accuracy: 0.5487 - val_loss: 1.4043 - val_accuracy: 0.6957
Epoch 51/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5017 - accuracy: 0.5596 - val_loss: 1.4003 - val_accuracy: 0.7174
Epoch 52/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5019 - accuracy: 0.5487 - val_loss: 1.3965 - val_accuracy: 0.7174
Epoch 53/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4669 - accuracy: 0.5681 - val_loss: 1.3926 - val_accuracy: 0.7283
Epoch 54/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4699 - accuracy: 0.5742 - val_loss: 1.3888 - val_accuracy: 0.7500
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4491 - accuracy: 0.5754 - val_loss: 1.3850 - val_accuracy: 0.7609
Epoch 56/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4581 - accuracy: 0.5742 - val_loss: 1.3813 - val_accuracy: 0.7609
Epoch 57/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4566 - accuracy: 0.5657 - val_loss: 1.3776 - val_accuracy: 0.7609
Epoch 58/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4678 - accuracy: 0.5815 - val_loss: 1.3740 - val_accuracy: 0.7609
Epoch 59/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4641 - accuracy: 0.5876 - val_loss: 1.3703 - val_accuracy: 0.7609
Epoch 60/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4551 - accuracy: 0.5998 - val_loss: 1.3667 - val_accuracy: 0.7609
Epoch 61/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4530 - accuracy: 0.5864 - val_loss: 1.3631 - val_accuracy: 0.7609
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4336 - accuracy: 0.5949 - val_loss: 1.3595 - val_accuracy: 0.7717
Epoch 63/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4750 - accuracy: 0.5791 - val_loss: 1.3559 - val_accuracy: 0.7717
Epoch 64/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4530 - accuracy: 0.5888 - val_loss: 1.3524 - val_accuracy: 0.7717
Epoch 65/100
2/2 [==============================] - 0s 54ms/step - loss: 1.4068 - accuracy: 0.6022 - val_loss: 1.3488 - val_accuracy: 0.7717
Epoch 66/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4374 - accuracy: 0.6022 - val_loss: 1.3453 - val_accuracy: 0.7609
Epoch 67/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4404 - accuracy: 0.5973 - val_loss: 1.3419 - val_accuracy: 0.7609
Epoch 68/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4058 - accuracy: 0.6095 - val_loss: 1.3384 - val_accuracy: 0.7609
Epoch 69/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4472 - accuracy: 0.5852 - val_loss: 1.3350 - val_accuracy: 0.7609
Epoch 70/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3960 - accuracy: 0.5937 - val_loss: 1.3315 - val_accuracy: 0.7609
Epoch 71/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4092 - accuracy: 0.5937 - val_loss: 1.3281 - val_accuracy: 0.7609
Epoch 72/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4404 - accuracy: 0.5937 - val_loss: 1.3248 - val_accuracy: 0.7609
Epoch 73/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4257 - accuracy: 0.5949 - val_loss: 1.3214 - val_accuracy: 0.7609
Epoch 74/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3805 - accuracy: 0.6217 - val_loss: 1.3179 - val_accuracy: 0.7609
Epoch 75/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3923 - accuracy: 0.6046 - val_loss: 1.3145 - val_accuracy: 0.7609
Epoch 76/100
2/2 [==============================] - 0s 55ms/step - loss: 1.3807 - accuracy: 0.6144 - val_loss: 1.3112 - val_accuracy: 0.7717
Epoch 77/100
2/2 [==============================] - 0s 30ms/step - loss: 1.4097 - accuracy: 0.5912 - val_loss: 1.3077 - val_accuracy: 0.7717
Epoch 78/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3870 - accuracy: 0.6058 - val_loss: 1.3042 - val_accuracy: 0.7717
Epoch 79/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3706 - accuracy: 0.6302 - val_loss: 1.3007 - val_accuracy: 0.7717
Epoch 80/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3856 - accuracy: 0.6083 - val_loss: 1.2973 - val_accuracy: 0.7717
Epoch 81/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3618 - accuracy: 0.6277 - val_loss: 1.2938 - val_accuracy: 0.7717
Epoch 82/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3843 - accuracy: 0.6375 - val_loss: 1.2903 - val_accuracy: 0.7717
Epoch 83/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3763 - accuracy: 0.6058 - val_loss: 1.2870 - val_accuracy: 0.7717
Epoch 84/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3542 - accuracy: 0.6399 - val_loss: 1.2835 - val_accuracy: 0.7826
Epoch 85/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3409 - accuracy: 0.6387 - val_loss: 1.2800 - val_accuracy: 0.7826
Epoch 86/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3829 - accuracy: 0.6046 - val_loss: 1.2766 - val_accuracy: 0.7826
Epoch 87/100
2/2 [==============================] - 0s 54ms/step - loss: 1.3493 - accuracy: 0.6119 - val_loss: 1.2732 - val_accuracy: 0.7826
Epoch 88/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3341 - accuracy: 0.6484 - val_loss: 1.2699 - val_accuracy: 0.7826
Epoch 89/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3405 - accuracy: 0.6241 - val_loss: 1.2666 - val_accuracy: 0.7935
Epoch 90/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3514 - accuracy: 0.6326 - val_loss: 1.2633 - val_accuracy: 0.7935
Epoch 91/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3735 - accuracy: 0.6302 - val_loss: 1.2600 - val_accuracy: 0.7935
Epoch 92/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3208 - accuracy: 0.6241 - val_loss: 1.2567 - val_accuracy: 0.7935
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3218 - accuracy: 0.6460 - val_loss: 1.2534 - val_accuracy: 0.7935
Epoch 94/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3769 - accuracy: 0.6095 - val_loss: 1.2502 - val_accuracy: 0.8043
Epoch 95/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3118 - accuracy: 0.6375 - val_loss: 1.2469 - val_accuracy: 0.8043
Epoch 96/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3612 - accuracy: 0.6338 - val_loss: 1.2437 - val_accuracy: 0.8043
Epoch 97/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2943 - accuracy: 0.6582 - val_loss: 1.2404 - val_accuracy: 0.8043
Epoch 98/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3293 - accuracy: 0.6229 - val_loss: 1.2372 - val_accuracy: 0.8152
Epoch 99/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3359 - accuracy: 0.6363 - val_loss: 1.2339 - val_accuracy: 0.8152
Epoch 100/100
2/2 [==============================] - 0s 54ms/step - loss: 1.3530 - accuracy: 0.6204 - val_loss: 1.2307 - val_accuracy: 0.8152
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 254ms/step - loss: 2.1555 - accuracy: 0.3187 - val_loss: 1.7397 - val_accuracy: 0.1196
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1263 - accuracy: 0.3102 - val_loss: 1.7312 - val_accuracy: 0.1196
Epoch 3/100
2/2 [==============================] - 0s 50ms/step - loss: 2.0708 - accuracy: 0.3358 - val_loss: 1.7228 - val_accuracy: 0.1196
Epoch 4/100
2/2 [==============================] - 0s 49ms/step - loss: 2.0849 - accuracy: 0.3090 - val_loss: 1.7145 - val_accuracy: 0.1087
Epoch 5/100
2/2 [==============================] - 0s 45ms/step - loss: 2.0507 - accuracy: 0.3260 - val_loss: 1.7062 - val_accuracy: 0.1087
Epoch 6/100
2/2 [==============================] - 0s 45ms/step - loss: 2.0359 - accuracy: 0.3431 - val_loss: 1.6978 - val_accuracy: 0.1196
Epoch 7/100
2/2 [==============================] - 0s 33ms/step - loss: 1.9889 - accuracy: 0.3382 - val_loss: 1.6895 - val_accuracy: 0.1196
Epoch 8/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9511 - accuracy: 0.3516 - val_loss: 1.6813 - val_accuracy: 0.1304
Epoch 9/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9026 - accuracy: 0.3747 - val_loss: 1.6731 - val_accuracy: 0.1304
Epoch 10/100
2/2 [==============================] - 0s 49ms/step - loss: 1.8566 - accuracy: 0.3625 - val_loss: 1.6649 - val_accuracy: 0.1304
Epoch 11/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8930 - accuracy: 0.3637 - val_loss: 1.6567 - val_accuracy: 0.1413
Epoch 12/100
2/2 [==============================] - 0s 49ms/step - loss: 1.8515 - accuracy: 0.3686 - val_loss: 1.6485 - val_accuracy: 0.1413
Epoch 13/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8541 - accuracy: 0.3723 - val_loss: 1.6405 - val_accuracy: 0.1522
Epoch 14/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7978 - accuracy: 0.3856 - val_loss: 1.6324 - val_accuracy: 0.1522
Epoch 15/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7811 - accuracy: 0.3869 - val_loss: 1.6244 - val_accuracy: 0.1739
Epoch 16/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7920 - accuracy: 0.3698 - val_loss: 1.6165 - val_accuracy: 0.1739
Epoch 17/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7765 - accuracy: 0.4112 - val_loss: 1.6087 - val_accuracy: 0.1739
Epoch 18/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6823 - accuracy: 0.4331 - val_loss: 1.6008 - val_accuracy: 0.2065
Epoch 19/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7218 - accuracy: 0.4051 - val_loss: 1.5931 - val_accuracy: 0.2283
Epoch 20/100
2/2 [==============================] - 0s 56ms/step - loss: 1.6998 - accuracy: 0.4282 - val_loss: 1.5854 - val_accuracy: 0.2391
Epoch 21/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6856 - accuracy: 0.4343 - val_loss: 1.5778 - val_accuracy: 0.2391
Epoch 22/100
2/2 [==============================] - 0s 50ms/step - loss: 1.6742 - accuracy: 0.4672 - val_loss: 1.5703 - val_accuracy: 0.2500
Epoch 23/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6429 - accuracy: 0.4574 - val_loss: 1.5629 - val_accuracy: 0.2826
Epoch 24/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6213 - accuracy: 0.4732 - val_loss: 1.5555 - val_accuracy: 0.2935
Epoch 25/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6268 - accuracy: 0.4708 - val_loss: 1.5483 - val_accuracy: 0.3043
Epoch 26/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6187 - accuracy: 0.4732 - val_loss: 1.5411 - val_accuracy: 0.3370
Epoch 27/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6093 - accuracy: 0.4818 - val_loss: 1.5341 - val_accuracy: 0.3478
Epoch 28/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6028 - accuracy: 0.5109 - val_loss: 1.5271 - val_accuracy: 0.3696
Epoch 29/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6026 - accuracy: 0.4915 - val_loss: 1.5202 - val_accuracy: 0.3913
Epoch 30/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5708 - accuracy: 0.5085 - val_loss: 1.5135 - val_accuracy: 0.4130
Epoch 31/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5654 - accuracy: 0.4964 - val_loss: 1.5069 - val_accuracy: 0.4348
Epoch 32/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5723 - accuracy: 0.5049 - val_loss: 1.5004 - val_accuracy: 0.4457
Epoch 33/100
2/2 [==============================] - 0s 50ms/step - loss: 1.5364 - accuracy: 0.5000 - val_loss: 1.4940 - val_accuracy: 0.4674
Epoch 34/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5250 - accuracy: 0.5182 - val_loss: 1.4878 - val_accuracy: 0.4674
Epoch 35/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5474 - accuracy: 0.5097 - val_loss: 1.4816 - val_accuracy: 0.4674
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5225 - accuracy: 0.5353 - val_loss: 1.4755 - val_accuracy: 0.4891
Epoch 37/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5227 - accuracy: 0.5462 - val_loss: 1.4696 - val_accuracy: 0.5000
Epoch 38/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5174 - accuracy: 0.5268 - val_loss: 1.4637 - val_accuracy: 0.5109
Epoch 39/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4952 - accuracy: 0.5450 - val_loss: 1.4581 - val_accuracy: 0.5326
Epoch 40/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4884 - accuracy: 0.5401 - val_loss: 1.4525 - val_accuracy: 0.5435
Epoch 41/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5106 - accuracy: 0.5316 - val_loss: 1.4471 - val_accuracy: 0.5435
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4742 - accuracy: 0.5560 - val_loss: 1.4418 - val_accuracy: 0.5652
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4761 - accuracy: 0.5620 - val_loss: 1.4365 - val_accuracy: 0.5652
Epoch 44/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4819 - accuracy: 0.5438 - val_loss: 1.4314 - val_accuracy: 0.5870
Epoch 45/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5048 - accuracy: 0.5487 - val_loss: 1.4263 - val_accuracy: 0.6087
Epoch 46/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4805 - accuracy: 0.5547 - val_loss: 1.4213 - val_accuracy: 0.6196
Epoch 47/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4305 - accuracy: 0.5888 - val_loss: 1.4163 - val_accuracy: 0.6304
Epoch 48/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4544 - accuracy: 0.5438 - val_loss: 1.4115 - val_accuracy: 0.6304
Epoch 49/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4427 - accuracy: 0.5706 - val_loss: 1.4067 - val_accuracy: 0.6413
Epoch 50/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4751 - accuracy: 0.5572 - val_loss: 1.4020 - val_accuracy: 0.6413
Epoch 51/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4489 - accuracy: 0.5693 - val_loss: 1.3973 - val_accuracy: 0.6739
Epoch 52/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4535 - accuracy: 0.5912 - val_loss: 1.3927 - val_accuracy: 0.6739
Epoch 53/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4634 - accuracy: 0.5876 - val_loss: 1.3882 - val_accuracy: 0.6739
Epoch 54/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4323 - accuracy: 0.5754 - val_loss: 1.3838 - val_accuracy: 0.6739
Epoch 55/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4059 - accuracy: 0.5998 - val_loss: 1.3794 - val_accuracy: 0.6957
Epoch 56/100
2/2 [==============================] - 0s 61ms/step - loss: 1.4153 - accuracy: 0.5912 - val_loss: 1.3752 - val_accuracy: 0.6957
Epoch 57/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4066 - accuracy: 0.6107 - val_loss: 1.3710 - val_accuracy: 0.6957
Epoch 58/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3891 - accuracy: 0.5900 - val_loss: 1.3669 - val_accuracy: 0.6957
Epoch 59/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4052 - accuracy: 0.5949 - val_loss: 1.3628 - val_accuracy: 0.6957
Epoch 60/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3900 - accuracy: 0.5985 - val_loss: 1.3588 - val_accuracy: 0.6957
Epoch 61/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3904 - accuracy: 0.6338 - val_loss: 1.3548 - val_accuracy: 0.6957
Epoch 62/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3974 - accuracy: 0.6168 - val_loss: 1.3509 - val_accuracy: 0.6957
Epoch 63/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4207 - accuracy: 0.6058 - val_loss: 1.3470 - val_accuracy: 0.6957
Epoch 64/100
2/2 [==============================] - 0s 30ms/step - loss: 1.3957 - accuracy: 0.5961 - val_loss: 1.3432 - val_accuracy: 0.6957
Epoch 65/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3817 - accuracy: 0.6071 - val_loss: 1.3395 - val_accuracy: 0.7065
Epoch 66/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4194 - accuracy: 0.6095 - val_loss: 1.3358 - val_accuracy: 0.7065
Epoch 67/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3338 - accuracy: 0.6350 - val_loss: 1.3322 - val_accuracy: 0.7065
Epoch 68/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3496 - accuracy: 0.6265 - val_loss: 1.3287 - val_accuracy: 0.7065
Epoch 69/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3639 - accuracy: 0.6241 - val_loss: 1.3252 - val_accuracy: 0.7065
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3883 - accuracy: 0.6095 - val_loss: 1.3217 - val_accuracy: 0.7065
Epoch 71/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3710 - accuracy: 0.6277 - val_loss: 1.3183 - val_accuracy: 0.7174
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3681 - accuracy: 0.6107 - val_loss: 1.3149 - val_accuracy: 0.7174
Epoch 73/100
2/2 [==============================] - 0s 53ms/step - loss: 1.3709 - accuracy: 0.6253 - val_loss: 1.3116 - val_accuracy: 0.7174
Epoch 74/100
2/2 [==============================] - 0s 53ms/step - loss: 1.3825 - accuracy: 0.6168 - val_loss: 1.3083 - val_accuracy: 0.7391
Epoch 75/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3645 - accuracy: 0.6557 - val_loss: 1.3050 - val_accuracy: 0.7500
Epoch 76/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3599 - accuracy: 0.6314 - val_loss: 1.3016 - val_accuracy: 0.7500
Epoch 77/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3374 - accuracy: 0.6131 - val_loss: 1.2983 - val_accuracy: 0.7500
Epoch 78/100
2/2 [==============================] - 0s 53ms/step - loss: 1.3254 - accuracy: 0.6411 - val_loss: 1.2950 - val_accuracy: 0.7500
Epoch 79/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3090 - accuracy: 0.6642 - val_loss: 1.2917 - val_accuracy: 0.7500
Epoch 80/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3164 - accuracy: 0.6484 - val_loss: 1.2884 - val_accuracy: 0.7609
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3462 - accuracy: 0.6180 - val_loss: 1.2850 - val_accuracy: 0.7717
Epoch 82/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3295 - accuracy: 0.6448 - val_loss: 1.2817 - val_accuracy: 0.7826
Epoch 83/100
2/2 [==============================] - 0s 27ms/step - loss: 1.3168 - accuracy: 0.6411 - val_loss: 1.2784 - val_accuracy: 0.7826
Epoch 84/100
2/2 [==============================] - 0s 26ms/step - loss: 1.3265 - accuracy: 0.6131 - val_loss: 1.2751 - val_accuracy: 0.7826
Epoch 85/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3218 - accuracy: 0.6496 - val_loss: 1.2718 - val_accuracy: 0.7826
Epoch 86/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3322 - accuracy: 0.6472 - val_loss: 1.2686 - val_accuracy: 0.7826
Epoch 87/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3222 - accuracy: 0.6448 - val_loss: 1.2654 - val_accuracy: 0.7935
Epoch 88/100
2/2 [==============================] - 0s 34ms/step - loss: 1.2902 - accuracy: 0.6509 - val_loss: 1.2623 - val_accuracy: 0.7935
Epoch 89/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3436 - accuracy: 0.6338 - val_loss: 1.2591 - val_accuracy: 0.7935
Epoch 90/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3137 - accuracy: 0.6338 - val_loss: 1.2560 - val_accuracy: 0.7935
Epoch 91/100
2/2 [==============================] - 0s 29ms/step - loss: 1.2908 - accuracy: 0.6448 - val_loss: 1.2529 - val_accuracy: 0.8043
Epoch 92/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2701 - accuracy: 0.6667 - val_loss: 1.2498 - val_accuracy: 0.8152
Epoch 93/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3088 - accuracy: 0.6557 - val_loss: 1.2467 - val_accuracy: 0.8152
Epoch 94/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2935 - accuracy: 0.6350 - val_loss: 1.2437 - val_accuracy: 0.8152
Epoch 95/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2704 - accuracy: 0.6545 - val_loss: 1.2407 - val_accuracy: 0.8152
Epoch 96/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2691 - accuracy: 0.6618 - val_loss: 1.2377 - val_accuracy: 0.8152
Epoch 97/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3062 - accuracy: 0.6618 - val_loss: 1.2347 - val_accuracy: 0.8152
Epoch 98/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3124 - accuracy: 0.6423 - val_loss: 1.2317 - val_accuracy: 0.8152
Epoch 99/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2753 - accuracy: 0.6594 - val_loss: 1.2286 - val_accuracy: 0.8152
Epoch 100/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2946 - accuracy: 0.6545 - val_loss: 1.2256 - val_accuracy: 0.8152
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 252ms/step - loss: 2.0529 - accuracy: 0.2774 - val_loss: 1.3232 - val_accuracy: 0.8370
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0095 - accuracy: 0.2725 - val_loss: 1.3219 - val_accuracy: 0.8370
Epoch 3/100
2/2 [==============================] - 0s 52ms/step - loss: 1.9820 - accuracy: 0.2859 - val_loss: 1.3205 - val_accuracy: 0.8370
Epoch 4/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9644 - accuracy: 0.2762 - val_loss: 1.3191 - val_accuracy: 0.8370
Epoch 5/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8972 - accuracy: 0.2956 - val_loss: 1.3177 - val_accuracy: 0.8478
Epoch 6/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9184 - accuracy: 0.2713 - val_loss: 1.3162 - val_accuracy: 0.8587
Epoch 7/100
2/2 [==============================] - 0s 52ms/step - loss: 1.8726 - accuracy: 0.3029 - val_loss: 1.3146 - val_accuracy: 0.8696
Epoch 8/100
2/2 [==============================] - 0s 50ms/step - loss: 1.8460 - accuracy: 0.3102 - val_loss: 1.3130 - val_accuracy: 0.8696
Epoch 9/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8196 - accuracy: 0.3285 - val_loss: 1.3114 - val_accuracy: 0.8804
Epoch 10/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7827 - accuracy: 0.3066 - val_loss: 1.3098 - val_accuracy: 0.8804
Epoch 11/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7858 - accuracy: 0.3321 - val_loss: 1.3083 - val_accuracy: 0.8804
Epoch 12/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7668 - accuracy: 0.3187 - val_loss: 1.3067 - val_accuracy: 0.8804
Epoch 13/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7060 - accuracy: 0.3625 - val_loss: 1.3051 - val_accuracy: 0.8804
Epoch 14/100
2/2 [==============================] - 0s 46ms/step - loss: 1.7250 - accuracy: 0.3625 - val_loss: 1.3036 - val_accuracy: 0.8696
Epoch 15/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7097 - accuracy: 0.3601 - val_loss: 1.3021 - val_accuracy: 0.8696
Epoch 16/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6787 - accuracy: 0.3759 - val_loss: 1.3006 - val_accuracy: 0.8804
Epoch 17/100
2/2 [==============================] - 0s 53ms/step - loss: 1.6903 - accuracy: 0.3832 - val_loss: 1.2991 - val_accuracy: 0.8804
Epoch 18/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6648 - accuracy: 0.3832 - val_loss: 1.2976 - val_accuracy: 0.8804
Epoch 19/100
2/2 [==============================] - 0s 49ms/step - loss: 1.6459 - accuracy: 0.4015 - val_loss: 1.2962 - val_accuracy: 0.8913
Epoch 20/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6591 - accuracy: 0.4136 - val_loss: 1.2948 - val_accuracy: 0.9022
Epoch 21/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6198 - accuracy: 0.4002 - val_loss: 1.2935 - val_accuracy: 0.9239
Epoch 22/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6479 - accuracy: 0.4197 - val_loss: 1.2921 - val_accuracy: 0.9239
Epoch 23/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6359 - accuracy: 0.4063 - val_loss: 1.2909 - val_accuracy: 0.9239
Epoch 24/100
2/2 [==============================] - 0s 54ms/step - loss: 1.6202 - accuracy: 0.4404 - val_loss: 1.2896 - val_accuracy: 0.9239
Epoch 25/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6230 - accuracy: 0.4209 - val_loss: 1.2884 - val_accuracy: 0.9130
Epoch 26/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5774 - accuracy: 0.4611 - val_loss: 1.2871 - val_accuracy: 0.9130
Epoch 27/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5892 - accuracy: 0.4647 - val_loss: 1.2860 - val_accuracy: 0.9130
Epoch 28/100
2/2 [==============================] - 0s 50ms/step - loss: 1.5564 - accuracy: 0.4696 - val_loss: 1.2848 - val_accuracy: 0.9130
Epoch 29/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5599 - accuracy: 0.4732 - val_loss: 1.2836 - val_accuracy: 0.8913
Epoch 30/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5760 - accuracy: 0.4672 - val_loss: 1.2824 - val_accuracy: 0.8913
Epoch 31/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5641 - accuracy: 0.4769 - val_loss: 1.2813 - val_accuracy: 0.8913
Epoch 32/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5562 - accuracy: 0.4939 - val_loss: 1.2802 - val_accuracy: 0.8913
Epoch 33/100
2/2 [==============================] - 0s 45ms/step - loss: 1.5646 - accuracy: 0.5012 - val_loss: 1.2792 - val_accuracy: 0.9022
Epoch 34/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5537 - accuracy: 0.4708 - val_loss: 1.2781 - val_accuracy: 0.9022
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5032 - accuracy: 0.5401 - val_loss: 1.2771 - val_accuracy: 0.9022
Epoch 36/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5263 - accuracy: 0.5134 - val_loss: 1.2761 - val_accuracy: 0.9022
Epoch 37/100
2/2 [==============================] - 0s 52ms/step - loss: 1.4917 - accuracy: 0.5134 - val_loss: 1.2751 - val_accuracy: 0.9022
Epoch 38/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5205 - accuracy: 0.5243 - val_loss: 1.2741 - val_accuracy: 0.9022
Epoch 39/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5214 - accuracy: 0.5122 - val_loss: 1.2730 - val_accuracy: 0.9022
Epoch 40/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4772 - accuracy: 0.5450 - val_loss: 1.2719 - val_accuracy: 0.8913
Epoch 41/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4747 - accuracy: 0.5596 - val_loss: 1.2708 - val_accuracy: 0.8913
Epoch 42/100
2/2 [==============================] - 0s 63ms/step - loss: 1.5044 - accuracy: 0.5365 - val_loss: 1.2697 - val_accuracy: 0.8913
Epoch 43/100
2/2 [==============================] - 0s 58ms/step - loss: 1.4921 - accuracy: 0.5414 - val_loss: 1.2685 - val_accuracy: 0.8913
Epoch 44/100
2/2 [==============================] - 0s 53ms/step - loss: 1.4986 - accuracy: 0.5280 - val_loss: 1.2674 - val_accuracy: 0.8913
Epoch 45/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4680 - accuracy: 0.5669 - val_loss: 1.2662 - val_accuracy: 0.8804
Epoch 46/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4460 - accuracy: 0.5572 - val_loss: 1.2650 - val_accuracy: 0.8804
Epoch 47/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5016 - accuracy: 0.5353 - val_loss: 1.2638 - val_accuracy: 0.8804
Epoch 48/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4163 - accuracy: 0.5888 - val_loss: 1.2625 - val_accuracy: 0.8804
Epoch 49/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4304 - accuracy: 0.5572 - val_loss: 1.2612 - val_accuracy: 0.8804
Epoch 50/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4399 - accuracy: 0.5730 - val_loss: 1.2599 - val_accuracy: 0.8804
Epoch 51/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4324 - accuracy: 0.5693 - val_loss: 1.2586 - val_accuracy: 0.8804
Epoch 52/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4306 - accuracy: 0.5596 - val_loss: 1.2572 - val_accuracy: 0.8804
Epoch 53/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4662 - accuracy: 0.5414 - val_loss: 1.2558 - val_accuracy: 0.8804
Epoch 54/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4632 - accuracy: 0.5572 - val_loss: 1.2543 - val_accuracy: 0.8804
Epoch 55/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4205 - accuracy: 0.5633 - val_loss: 1.2528 - val_accuracy: 0.8913
Epoch 56/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4342 - accuracy: 0.5900 - val_loss: 1.2513 - val_accuracy: 0.8913
Epoch 57/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4155 - accuracy: 0.5803 - val_loss: 1.2497 - val_accuracy: 0.8913
Epoch 58/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4188 - accuracy: 0.5864 - val_loss: 1.2481 - val_accuracy: 0.8913
Epoch 59/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4067 - accuracy: 0.5718 - val_loss: 1.2464 - val_accuracy: 0.8913
Epoch 60/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4069 - accuracy: 0.5852 - val_loss: 1.2446 - val_accuracy: 0.8913
Epoch 61/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4117 - accuracy: 0.5839 - val_loss: 1.2427 - val_accuracy: 0.8913
Epoch 62/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4032 - accuracy: 0.5608 - val_loss: 1.2409 - val_accuracy: 0.8913
Epoch 63/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3973 - accuracy: 0.5815 - val_loss: 1.2389 - val_accuracy: 0.8913
Epoch 64/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3926 - accuracy: 0.6010 - val_loss: 1.2370 - val_accuracy: 0.9022
Epoch 65/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3966 - accuracy: 0.5791 - val_loss: 1.2350 - val_accuracy: 0.9022
Epoch 66/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3937 - accuracy: 0.5839 - val_loss: 1.2330 - val_accuracy: 0.9022
Epoch 67/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3746 - accuracy: 0.5912 - val_loss: 1.2310 - val_accuracy: 0.9022
Epoch 68/100
2/2 [==============================] - 0s 52ms/step - loss: 1.3742 - accuracy: 0.6058 - val_loss: 1.2290 - val_accuracy: 0.9022
Epoch 69/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3763 - accuracy: 0.6204 - val_loss: 1.2270 - val_accuracy: 0.9022
Epoch 70/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3497 - accuracy: 0.6095 - val_loss: 1.2250 - val_accuracy: 0.9130
Epoch 71/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3536 - accuracy: 0.6034 - val_loss: 1.2227 - val_accuracy: 0.9130
Epoch 72/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3649 - accuracy: 0.6119 - val_loss: 1.2205 - val_accuracy: 0.9130
Epoch 73/100
2/2 [==============================] - 0s 52ms/step - loss: 1.3913 - accuracy: 0.5900 - val_loss: 1.2183 - val_accuracy: 0.9130
Epoch 74/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3603 - accuracy: 0.6083 - val_loss: 1.2161 - val_accuracy: 0.9130
Epoch 75/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3502 - accuracy: 0.6119 - val_loss: 1.2138 - val_accuracy: 0.9130
Epoch 76/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3679 - accuracy: 0.6119 - val_loss: 1.2115 - val_accuracy: 0.9130
Epoch 77/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3749 - accuracy: 0.5791 - val_loss: 1.2091 - val_accuracy: 0.9130
Epoch 78/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3457 - accuracy: 0.6180 - val_loss: 1.2066 - val_accuracy: 0.9130
Epoch 79/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3359 - accuracy: 0.6192 - val_loss: 1.2042 - val_accuracy: 0.9130
Epoch 80/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3194 - accuracy: 0.6375 - val_loss: 1.2018 - val_accuracy: 0.9130
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3316 - accuracy: 0.6217 - val_loss: 1.1993 - val_accuracy: 0.9130
Epoch 82/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3105 - accuracy: 0.6387 - val_loss: 1.1968 - val_accuracy: 0.9130
Epoch 83/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3269 - accuracy: 0.6217 - val_loss: 1.1943 - val_accuracy: 0.9130
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3258 - accuracy: 0.6290 - val_loss: 1.1917 - val_accuracy: 0.9130
Epoch 85/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2933 - accuracy: 0.6350 - val_loss: 1.1890 - val_accuracy: 0.9130
Epoch 86/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3350 - accuracy: 0.6265 - val_loss: 1.1864 - val_accuracy: 0.9130
Epoch 87/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2962 - accuracy: 0.6314 - val_loss: 1.1837 - val_accuracy: 0.9130
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3082 - accuracy: 0.6411 - val_loss: 1.1810 - val_accuracy: 0.9130
Epoch 89/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3245 - accuracy: 0.6509 - val_loss: 1.1784 - val_accuracy: 0.9130
Epoch 90/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3026 - accuracy: 0.6472 - val_loss: 1.1756 - val_accuracy: 0.9130
Epoch 91/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2940 - accuracy: 0.6521 - val_loss: 1.1729 - val_accuracy: 0.9130
Epoch 92/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3067 - accuracy: 0.6253 - val_loss: 1.1702 - val_accuracy: 0.9130
Epoch 93/100
2/2 [==============================] - 0s 68ms/step - loss: 1.3053 - accuracy: 0.6557 - val_loss: 1.1674 - val_accuracy: 0.9130
Epoch 94/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2851 - accuracy: 0.6679 - val_loss: 1.1647 - val_accuracy: 0.9130
Epoch 95/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2715 - accuracy: 0.6582 - val_loss: 1.1620 - val_accuracy: 0.9130
Epoch 96/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3128 - accuracy: 0.6521 - val_loss: 1.1594 - val_accuracy: 0.9130
Epoch 97/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2933 - accuracy: 0.6496 - val_loss: 1.1567 - val_accuracy: 0.9239
Epoch 98/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2920 - accuracy: 0.6594 - val_loss: 1.1541 - val_accuracy: 0.9239
Epoch 99/100
2/2 [==============================] - 0s 50ms/step - loss: 1.2482 - accuracy: 0.6630 - val_loss: 1.1514 - val_accuracy: 0.9239
Epoch 100/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2627 - accuracy: 0.6484 - val_loss: 1.1487 - val_accuracy: 0.9239
No description has been provided for this image
No description has been provided for this image 
WARNING:tensorflow:5 out of the last 16 calls to <function Model.make_predict_function.<locals>.predict_function at 0x000001FC79E974C0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.
3/3 [==============================] - 0s 5ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 258ms/step - loss: 2.1164 - accuracy: 0.3900 - val_loss: 1.5681 - val_accuracy: 0.2637
Epoch 2/100
2/2 [==============================] - 0s 45ms/step - loss: 2.0268 - accuracy: 0.4034 - val_loss: 1.5629 - val_accuracy: 0.2637
Epoch 3/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9817 - accuracy: 0.3998 - val_loss: 1.5579 - val_accuracy: 0.2857
Epoch 4/100
2/2 [==============================] - 0s 43ms/step - loss: 2.0155 - accuracy: 0.4265 - val_loss: 1.5530 - val_accuracy: 0.3077
Epoch 5/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9695 - accuracy: 0.4216 - val_loss: 1.5482 - val_accuracy: 0.3297
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9229 - accuracy: 0.4362 - val_loss: 1.5435 - val_accuracy: 0.3516
Epoch 7/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9361 - accuracy: 0.4289 - val_loss: 1.5389 - val_accuracy: 0.3736
Epoch 8/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9291 - accuracy: 0.4216 - val_loss: 1.5343 - val_accuracy: 0.3736
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8960 - accuracy: 0.4435 - val_loss: 1.5298 - val_accuracy: 0.3846
Epoch 10/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8992 - accuracy: 0.4362 - val_loss: 1.5253 - val_accuracy: 0.3956
Epoch 11/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8827 - accuracy: 0.4362 - val_loss: 1.5209 - val_accuracy: 0.4176
Epoch 12/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8535 - accuracy: 0.4447 - val_loss: 1.5166 - val_accuracy: 0.4286
Epoch 13/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7501 - accuracy: 0.4739 - val_loss: 1.5125 - val_accuracy: 0.4396
Epoch 14/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7476 - accuracy: 0.4751 - val_loss: 1.5084 - val_accuracy: 0.4505
Epoch 15/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7778 - accuracy: 0.4629 - val_loss: 1.5043 - val_accuracy: 0.4505
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7636 - accuracy: 0.4702 - val_loss: 1.5003 - val_accuracy: 0.4505
Epoch 17/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7744 - accuracy: 0.4714 - val_loss: 1.4964 - val_accuracy: 0.4725
Epoch 18/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7172 - accuracy: 0.4860 - val_loss: 1.4925 - val_accuracy: 0.4945
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7288 - accuracy: 0.4933 - val_loss: 1.4888 - val_accuracy: 0.5165
Epoch 20/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7375 - accuracy: 0.4885 - val_loss: 1.4851 - val_accuracy: 0.5055
Epoch 21/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7250 - accuracy: 0.4824 - val_loss: 1.4814 - val_accuracy: 0.5055
Epoch 22/100
2/2 [==============================] - 0s 29ms/step - loss: 1.7083 - accuracy: 0.4945 - val_loss: 1.4777 - val_accuracy: 0.5165
Epoch 23/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6370 - accuracy: 0.5310 - val_loss: 1.4742 - val_accuracy: 0.5055
Epoch 24/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6598 - accuracy: 0.4933 - val_loss: 1.4706 - val_accuracy: 0.5275
Epoch 25/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6431 - accuracy: 0.5055 - val_loss: 1.4671 - val_accuracy: 0.5275
Epoch 26/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6494 - accuracy: 0.4933 - val_loss: 1.4636 - val_accuracy: 0.5275
Epoch 27/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6425 - accuracy: 0.5055 - val_loss: 1.4602 - val_accuracy: 0.5275
Epoch 28/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6650 - accuracy: 0.4933 - val_loss: 1.4567 - val_accuracy: 0.5385
Epoch 29/100
2/2 [==============================] - 0s 52ms/step - loss: 1.5910 - accuracy: 0.5188 - val_loss: 1.4532 - val_accuracy: 0.5495
Epoch 30/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6132 - accuracy: 0.5249 - val_loss: 1.4498 - val_accuracy: 0.5604
Epoch 31/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5951 - accuracy: 0.5431 - val_loss: 1.4464 - val_accuracy: 0.5604
Epoch 32/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6046 - accuracy: 0.5249 - val_loss: 1.4430 - val_accuracy: 0.5714
Epoch 33/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5784 - accuracy: 0.5419 - val_loss: 1.4397 - val_accuracy: 0.5714
Epoch 34/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5671 - accuracy: 0.5261 - val_loss: 1.4364 - val_accuracy: 0.5934
Epoch 35/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6100 - accuracy: 0.5298 - val_loss: 1.4330 - val_accuracy: 0.6154
Epoch 36/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5825 - accuracy: 0.5334 - val_loss: 1.4296 - val_accuracy: 0.6264
Epoch 37/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5995 - accuracy: 0.5346 - val_loss: 1.4263 - val_accuracy: 0.6374
Epoch 38/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5960 - accuracy: 0.5322 - val_loss: 1.4231 - val_accuracy: 0.6374
Epoch 39/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5192 - accuracy: 0.5614 - val_loss: 1.4198 - val_accuracy: 0.6374
Epoch 40/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5500 - accuracy: 0.5577 - val_loss: 1.4165 - val_accuracy: 0.6484
Epoch 41/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5316 - accuracy: 0.5614 - val_loss: 1.4133 - val_accuracy: 0.6593
Epoch 42/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5133 - accuracy: 0.5529 - val_loss: 1.4100 - val_accuracy: 0.6593
Epoch 43/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4989 - accuracy: 0.5601 - val_loss: 1.4067 - val_accuracy: 0.6703
Epoch 44/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4826 - accuracy: 0.5674 - val_loss: 1.4034 - val_accuracy: 0.6703
Epoch 45/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5342 - accuracy: 0.5589 - val_loss: 1.4001 - val_accuracy: 0.6703
Epoch 46/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5170 - accuracy: 0.5699 - val_loss: 1.3968 - val_accuracy: 0.6703
Epoch 47/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5214 - accuracy: 0.5529 - val_loss: 1.3935 - val_accuracy: 0.6923
Epoch 48/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4711 - accuracy: 0.5772 - val_loss: 1.3902 - val_accuracy: 0.6923
Epoch 49/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4735 - accuracy: 0.5674 - val_loss: 1.3870 - val_accuracy: 0.7033
Epoch 50/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4607 - accuracy: 0.5881 - val_loss: 1.3837 - val_accuracy: 0.7253
Epoch 51/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4952 - accuracy: 0.5735 - val_loss: 1.3805 - val_accuracy: 0.7363
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4694 - accuracy: 0.5784 - val_loss: 1.3773 - val_accuracy: 0.7363
Epoch 53/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4777 - accuracy: 0.5735 - val_loss: 1.3741 - val_accuracy: 0.7363
Epoch 54/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4626 - accuracy: 0.5735 - val_loss: 1.3709 - val_accuracy: 0.7363
Epoch 55/100
2/2 [==============================] - 0s 52ms/step - loss: 1.4489 - accuracy: 0.5820 - val_loss: 1.3676 - val_accuracy: 0.7363
Epoch 56/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4590 - accuracy: 0.5832 - val_loss: 1.3644 - val_accuracy: 0.7363
Epoch 57/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4503 - accuracy: 0.5893 - val_loss: 1.3613 - val_accuracy: 0.7363
Epoch 58/100
2/2 [==============================] - 0s 54ms/step - loss: 1.4808 - accuracy: 0.5832 - val_loss: 1.3582 - val_accuracy: 0.7363
Epoch 59/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4688 - accuracy: 0.6015 - val_loss: 1.3551 - val_accuracy: 0.7363
Epoch 60/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4128 - accuracy: 0.6087 - val_loss: 1.3520 - val_accuracy: 0.7363
Epoch 61/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4119 - accuracy: 0.5881 - val_loss: 1.3490 - val_accuracy: 0.7363
Epoch 62/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4218 - accuracy: 0.5942 - val_loss: 1.3459 - val_accuracy: 0.7363
Epoch 63/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4235 - accuracy: 0.6173 - val_loss: 1.3428 - val_accuracy: 0.7363
Epoch 64/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4229 - accuracy: 0.5759 - val_loss: 1.3397 - val_accuracy: 0.7363
Epoch 65/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4176 - accuracy: 0.6148 - val_loss: 1.3367 - val_accuracy: 0.7363
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3656 - accuracy: 0.6428 - val_loss: 1.3337 - val_accuracy: 0.7363
Epoch 67/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4168 - accuracy: 0.5917 - val_loss: 1.3305 - val_accuracy: 0.7363
Epoch 68/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4549 - accuracy: 0.5881 - val_loss: 1.3275 - val_accuracy: 0.7363
Epoch 69/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4075 - accuracy: 0.5990 - val_loss: 1.3244 - val_accuracy: 0.7363
Epoch 70/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3728 - accuracy: 0.6197 - val_loss: 1.3214 - val_accuracy: 0.7473
Epoch 71/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3600 - accuracy: 0.6440 - val_loss: 1.3183 - val_accuracy: 0.7582
Epoch 72/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3988 - accuracy: 0.6027 - val_loss: 1.3152 - val_accuracy: 0.7582
Epoch 73/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3660 - accuracy: 0.6258 - val_loss: 1.3121 - val_accuracy: 0.7802
Epoch 74/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3681 - accuracy: 0.6136 - val_loss: 1.3091 - val_accuracy: 0.7802
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3699 - accuracy: 0.6173 - val_loss: 1.3061 - val_accuracy: 0.7692
Epoch 76/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3818 - accuracy: 0.6112 - val_loss: 1.3030 - val_accuracy: 0.7692
Epoch 77/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3789 - accuracy: 0.6330 - val_loss: 1.2999 - val_accuracy: 0.7692
Epoch 78/100
2/2 [==============================] - 0s 30ms/step - loss: 1.3642 - accuracy: 0.6100 - val_loss: 1.2970 - val_accuracy: 0.7692
Epoch 79/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3789 - accuracy: 0.6197 - val_loss: 1.2939 - val_accuracy: 0.7692
Epoch 80/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3400 - accuracy: 0.6258 - val_loss: 1.2909 - val_accuracy: 0.7692
Epoch 81/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3659 - accuracy: 0.6209 - val_loss: 1.2880 - val_accuracy: 0.7692
Epoch 82/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3475 - accuracy: 0.6513 - val_loss: 1.2850 - val_accuracy: 0.7802
Epoch 83/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3258 - accuracy: 0.6428 - val_loss: 1.2820 - val_accuracy: 0.7802
Epoch 84/100
2/2 [==============================] - 0s 30ms/step - loss: 1.3704 - accuracy: 0.5990 - val_loss: 1.2791 - val_accuracy: 0.7802
Epoch 85/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3603 - accuracy: 0.6209 - val_loss: 1.2762 - val_accuracy: 0.7802
Epoch 86/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3339 - accuracy: 0.6464 - val_loss: 1.2732 - val_accuracy: 0.7912
Epoch 87/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3428 - accuracy: 0.6391 - val_loss: 1.2702 - val_accuracy: 0.7912
Epoch 88/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3272 - accuracy: 0.6367 - val_loss: 1.2673 - val_accuracy: 0.7912
Epoch 89/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3141 - accuracy: 0.6488 - val_loss: 1.2643 - val_accuracy: 0.7912
Epoch 90/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3348 - accuracy: 0.6245 - val_loss: 1.2613 - val_accuracy: 0.7912
Epoch 91/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3330 - accuracy: 0.6452 - val_loss: 1.2583 - val_accuracy: 0.7912
Epoch 92/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3115 - accuracy: 0.6488 - val_loss: 1.2553 - val_accuracy: 0.7912
Epoch 93/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3303 - accuracy: 0.6391 - val_loss: 1.2523 - val_accuracy: 0.7912
Epoch 94/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2902 - accuracy: 0.6574 - val_loss: 1.2493 - val_accuracy: 0.7912
Epoch 95/100
2/2 [==============================] - 0s 52ms/step - loss: 1.3255 - accuracy: 0.6513 - val_loss: 1.2463 - val_accuracy: 0.7912
Epoch 96/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3231 - accuracy: 0.6416 - val_loss: 1.2433 - val_accuracy: 0.8022
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2825 - accuracy: 0.6598 - val_loss: 1.2403 - val_accuracy: 0.8242
Epoch 98/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2807 - accuracy: 0.6622 - val_loss: 1.2373 - val_accuracy: 0.8352
Epoch 99/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2843 - accuracy: 0.6634 - val_loss: 1.2342 - val_accuracy: 0.8352
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2518 - accuracy: 0.6804 - val_loss: 1.2312 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
WARNING:tensorflow:5 out of the last 13 calls to <function Model.make_predict_function.<locals>.predict_function at 0x000001FC79ECC3A0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.
3/3 [==============================] - 0s 722us/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 225ms/step - loss: 2.1183 - accuracy: 0.3086 - val_loss: 1.3800 - val_accuracy: 0.6374
Epoch 2/100
2/2 [==============================] - 0s 52ms/step - loss: 2.0539 - accuracy: 0.3244 - val_loss: 1.3785 - val_accuracy: 0.6484
Epoch 3/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0395 - accuracy: 0.3378 - val_loss: 1.3769 - val_accuracy: 0.6593
Epoch 4/100
2/2 [==============================] - 0s 36ms/step - loss: 2.0268 - accuracy: 0.3414 - val_loss: 1.3755 - val_accuracy: 0.6703
Epoch 5/100
2/2 [==============================] - 0s 35ms/step - loss: 2.0364 - accuracy: 0.3281 - val_loss: 1.3740 - val_accuracy: 0.6703
Epoch 6/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9778 - accuracy: 0.3621 - val_loss: 1.3725 - val_accuracy: 0.7033
Epoch 7/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9815 - accuracy: 0.3244 - val_loss: 1.3709 - val_accuracy: 0.7033
Epoch 8/100
2/2 [==============================] - 0s 32ms/step - loss: 1.9672 - accuracy: 0.3329 - val_loss: 1.3694 - val_accuracy: 0.7033
Epoch 9/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9245 - accuracy: 0.3645 - val_loss: 1.3678 - val_accuracy: 0.7033
Epoch 10/100
2/2 [==============================] - 0s 70ms/step - loss: 1.9116 - accuracy: 0.3670 - val_loss: 1.3663 - val_accuracy: 0.7253
Epoch 11/100
2/2 [==============================] - 0s 49ms/step - loss: 1.9001 - accuracy: 0.3876 - val_loss: 1.3647 - val_accuracy: 0.7253
Epoch 12/100
2/2 [==============================] - 0s 48ms/step - loss: 1.8553 - accuracy: 0.4131 - val_loss: 1.3632 - val_accuracy: 0.7253
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8654 - accuracy: 0.3900 - val_loss: 1.3616 - val_accuracy: 0.7363
Epoch 14/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8458 - accuracy: 0.3694 - val_loss: 1.3600 - val_accuracy: 0.7363
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7829 - accuracy: 0.3876 - val_loss: 1.3584 - val_accuracy: 0.7363
Epoch 16/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7884 - accuracy: 0.4241 - val_loss: 1.3568 - val_accuracy: 0.7143
Epoch 17/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7768 - accuracy: 0.4083 - val_loss: 1.3552 - val_accuracy: 0.7033
Epoch 18/100
2/2 [==============================] - 0s 51ms/step - loss: 1.7635 - accuracy: 0.4083 - val_loss: 1.3536 - val_accuracy: 0.7033
Epoch 19/100
2/2 [==============================] - 0s 46ms/step - loss: 1.7491 - accuracy: 0.4277 - val_loss: 1.3519 - val_accuracy: 0.7033
Epoch 20/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7810 - accuracy: 0.4131 - val_loss: 1.3503 - val_accuracy: 0.7033
Epoch 21/100
2/2 [==============================] - 0s 32ms/step - loss: 1.6952 - accuracy: 0.4459 - val_loss: 1.3486 - val_accuracy: 0.7143
Epoch 22/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7003 - accuracy: 0.4435 - val_loss: 1.3469 - val_accuracy: 0.7143
Epoch 23/100
2/2 [==============================] - 0s 52ms/step - loss: 1.6917 - accuracy: 0.4544 - val_loss: 1.3453 - val_accuracy: 0.7143
Epoch 24/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6850 - accuracy: 0.4435 - val_loss: 1.3436 - val_accuracy: 0.7143
Epoch 25/100
2/2 [==============================] - 0s 50ms/step - loss: 1.6753 - accuracy: 0.4605 - val_loss: 1.3419 - val_accuracy: 0.7143
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6571 - accuracy: 0.4435 - val_loss: 1.3402 - val_accuracy: 0.7143
Epoch 27/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6536 - accuracy: 0.4557 - val_loss: 1.3385 - val_accuracy: 0.7253
Epoch 28/100
2/2 [==============================] - 0s 32ms/step - loss: 1.6155 - accuracy: 0.4629 - val_loss: 1.3368 - val_accuracy: 0.7473
Epoch 29/100
2/2 [==============================] - 0s 50ms/step - loss: 1.6241 - accuracy: 0.4532 - val_loss: 1.3350 - val_accuracy: 0.7802
Epoch 30/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6168 - accuracy: 0.4605 - val_loss: 1.3333 - val_accuracy: 0.7802
Epoch 31/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5702 - accuracy: 0.4812 - val_loss: 1.3315 - val_accuracy: 0.7582
Epoch 32/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5759 - accuracy: 0.4763 - val_loss: 1.3298 - val_accuracy: 0.7582
Epoch 33/100
2/2 [==============================] - 0s 51ms/step - loss: 1.6191 - accuracy: 0.4581 - val_loss: 1.3279 - val_accuracy: 0.7692
Epoch 34/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6103 - accuracy: 0.4800 - val_loss: 1.3261 - val_accuracy: 0.7692
Epoch 35/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5693 - accuracy: 0.5055 - val_loss: 1.3242 - val_accuracy: 0.7692
Epoch 36/100
2/2 [==============================] - 0s 64ms/step - loss: 1.5244 - accuracy: 0.5018 - val_loss: 1.3223 - val_accuracy: 0.7802
Epoch 37/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5671 - accuracy: 0.4885 - val_loss: 1.3205 - val_accuracy: 0.7802
Epoch 38/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5671 - accuracy: 0.4872 - val_loss: 1.3186 - val_accuracy: 0.7912
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5420 - accuracy: 0.4800 - val_loss: 1.3167 - val_accuracy: 0.7912
Epoch 40/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5382 - accuracy: 0.5091 - val_loss: 1.3148 - val_accuracy: 0.8022
Epoch 41/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5357 - accuracy: 0.4921 - val_loss: 1.3130 - val_accuracy: 0.8022
Epoch 42/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5062 - accuracy: 0.5225 - val_loss: 1.3111 - val_accuracy: 0.8022
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4930 - accuracy: 0.5395 - val_loss: 1.3092 - val_accuracy: 0.8022
Epoch 44/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5214 - accuracy: 0.5091 - val_loss: 1.3073 - val_accuracy: 0.7912
Epoch 45/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4948 - accuracy: 0.5103 - val_loss: 1.3054 - val_accuracy: 0.7912
Epoch 46/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5173 - accuracy: 0.5310 - val_loss: 1.3035 - val_accuracy: 0.8242
Epoch 47/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4833 - accuracy: 0.5456 - val_loss: 1.3016 - val_accuracy: 0.8242
Epoch 48/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5041 - accuracy: 0.5310 - val_loss: 1.2997 - val_accuracy: 0.8242
Epoch 49/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4621 - accuracy: 0.5358 - val_loss: 1.2978 - val_accuracy: 0.8352
Epoch 50/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4886 - accuracy: 0.5346 - val_loss: 1.2959 - val_accuracy: 0.8352
Epoch 51/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4724 - accuracy: 0.5286 - val_loss: 1.2940 - val_accuracy: 0.8352
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4456 - accuracy: 0.5541 - val_loss: 1.2920 - val_accuracy: 0.8352
Epoch 53/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4286 - accuracy: 0.5869 - val_loss: 1.2901 - val_accuracy: 0.8352
Epoch 54/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4627 - accuracy: 0.5662 - val_loss: 1.2882 - val_accuracy: 0.8352
Epoch 55/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4237 - accuracy: 0.5735 - val_loss: 1.2863 - val_accuracy: 0.8352
Epoch 56/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4294 - accuracy: 0.5820 - val_loss: 1.2844 - val_accuracy: 0.8352
Epoch 57/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4315 - accuracy: 0.5699 - val_loss: 1.2825 - val_accuracy: 0.8352
Epoch 58/100
2/2 [==============================] - 0s 30ms/step - loss: 1.4388 - accuracy: 0.5796 - val_loss: 1.2806 - val_accuracy: 0.8242
Epoch 59/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4035 - accuracy: 0.5674 - val_loss: 1.2788 - val_accuracy: 0.8242
Epoch 60/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3999 - accuracy: 0.5905 - val_loss: 1.2769 - val_accuracy: 0.8242
Epoch 61/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4076 - accuracy: 0.5881 - val_loss: 1.2751 - val_accuracy: 0.8242
Epoch 62/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4167 - accuracy: 0.5711 - val_loss: 1.2732 - val_accuracy: 0.8242
Epoch 63/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4324 - accuracy: 0.5638 - val_loss: 1.2712 - val_accuracy: 0.8242
Epoch 64/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3969 - accuracy: 0.5930 - val_loss: 1.2694 - val_accuracy: 0.8242
Epoch 65/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3988 - accuracy: 0.5832 - val_loss: 1.2675 - val_accuracy: 0.8242
Epoch 66/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3826 - accuracy: 0.5917 - val_loss: 1.2656 - val_accuracy: 0.8242
Epoch 67/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3728 - accuracy: 0.5954 - val_loss: 1.2637 - val_accuracy: 0.8242
Epoch 68/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3860 - accuracy: 0.5978 - val_loss: 1.2618 - val_accuracy: 0.8242
Epoch 69/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3946 - accuracy: 0.5905 - val_loss: 1.2598 - val_accuracy: 0.8352
Epoch 70/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3707 - accuracy: 0.6221 - val_loss: 1.2579 - val_accuracy: 0.8462
Epoch 71/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3300 - accuracy: 0.6318 - val_loss: 1.2560 - val_accuracy: 0.8462
Epoch 72/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3605 - accuracy: 0.6087 - val_loss: 1.2540 - val_accuracy: 0.8462
Epoch 73/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3522 - accuracy: 0.6027 - val_loss: 1.2520 - val_accuracy: 0.8462
Epoch 74/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3523 - accuracy: 0.6100 - val_loss: 1.2499 - val_accuracy: 0.8462
Epoch 75/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3418 - accuracy: 0.6148 - val_loss: 1.2479 - val_accuracy: 0.8462
Epoch 76/100
2/2 [==============================] - 0s 55ms/step - loss: 1.3550 - accuracy: 0.6330 - val_loss: 1.2458 - val_accuracy: 0.8352
Epoch 77/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3514 - accuracy: 0.6258 - val_loss: 1.2438 - val_accuracy: 0.8352
Epoch 78/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3140 - accuracy: 0.6403 - val_loss: 1.2418 - val_accuracy: 0.8352
Epoch 79/100
2/2 [==============================] - 0s 52ms/step - loss: 1.3159 - accuracy: 0.6428 - val_loss: 1.2398 - val_accuracy: 0.8242
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3538 - accuracy: 0.6039 - val_loss: 1.2378 - val_accuracy: 0.8242
Epoch 81/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3153 - accuracy: 0.6343 - val_loss: 1.2357 - val_accuracy: 0.8242
Epoch 82/100
2/2 [==============================] - 0s 52ms/step - loss: 1.3358 - accuracy: 0.6282 - val_loss: 1.2337 - val_accuracy: 0.8242
Epoch 83/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3508 - accuracy: 0.6282 - val_loss: 1.2317 - val_accuracy: 0.8242
Epoch 84/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3139 - accuracy: 0.6270 - val_loss: 1.2295 - val_accuracy: 0.8242
Epoch 85/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3038 - accuracy: 0.6440 - val_loss: 1.2274 - val_accuracy: 0.8242
Epoch 86/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3205 - accuracy: 0.6343 - val_loss: 1.2254 - val_accuracy: 0.8242
Epoch 87/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2978 - accuracy: 0.6695 - val_loss: 1.2234 - val_accuracy: 0.8242
Epoch 88/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3088 - accuracy: 0.6440 - val_loss: 1.2214 - val_accuracy: 0.8242
Epoch 89/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3143 - accuracy: 0.6428 - val_loss: 1.2194 - val_accuracy: 0.8242
Epoch 90/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3010 - accuracy: 0.6574 - val_loss: 1.2174 - val_accuracy: 0.8242
Epoch 91/100
2/2 [==============================] - 0s 51ms/step - loss: 1.2919 - accuracy: 0.6634 - val_loss: 1.2155 - val_accuracy: 0.8242
Epoch 92/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3063 - accuracy: 0.6598 - val_loss: 1.2135 - val_accuracy: 0.8242
Epoch 93/100
2/2 [==============================] - 0s 34ms/step - loss: 1.2796 - accuracy: 0.6719 - val_loss: 1.2116 - val_accuracy: 0.8242
Epoch 94/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2893 - accuracy: 0.6464 - val_loss: 1.2096 - val_accuracy: 0.8242
Epoch 95/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2984 - accuracy: 0.6598 - val_loss: 1.2076 - val_accuracy: 0.8242
Epoch 96/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2966 - accuracy: 0.6574 - val_loss: 1.2056 - val_accuracy: 0.8242
Epoch 97/100
2/2 [==============================] - 0s 51ms/step - loss: 1.2515 - accuracy: 0.6914 - val_loss: 1.2036 - val_accuracy: 0.8242
Epoch 98/100
2/2 [==============================] - 0s 51ms/step - loss: 1.2479 - accuracy: 0.6719 - val_loss: 1.2016 - val_accuracy: 0.8242
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2633 - accuracy: 0.6841 - val_loss: 1.1996 - val_accuracy: 0.8242
Epoch 100/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2852 - accuracy: 0.6853 - val_loss: 1.1976 - val_accuracy: 0.8242
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 251ms/step - loss: 2.0285 - accuracy: 0.4095 - val_loss: 1.6862 - val_accuracy: 0.1209
Epoch 2/100
2/2 [==============================] - 0s 28ms/step - loss: 2.0501 - accuracy: 0.3973 - val_loss: 1.6795 - val_accuracy: 0.1209
Epoch 3/100
2/2 [==============================] - 0s 51ms/step - loss: 1.9795 - accuracy: 0.4010 - val_loss: 1.6727 - val_accuracy: 0.1209
Epoch 4/100
2/2 [==============================] - 0s 51ms/step - loss: 1.8918 - accuracy: 0.4277 - val_loss: 1.6660 - val_accuracy: 0.1209
Epoch 5/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9420 - accuracy: 0.4241 - val_loss: 1.6594 - val_accuracy: 0.1319
Epoch 6/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9301 - accuracy: 0.4192 - val_loss: 1.6526 - val_accuracy: 0.1319
Epoch 7/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9374 - accuracy: 0.4119 - val_loss: 1.6459 - val_accuracy: 0.1319
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8552 - accuracy: 0.4350 - val_loss: 1.6392 - val_accuracy: 0.1429
Epoch 9/100
2/2 [==============================] - 0s 48ms/step - loss: 1.8696 - accuracy: 0.4204 - val_loss: 1.6325 - val_accuracy: 0.1429
Epoch 10/100
2/2 [==============================] - 0s 51ms/step - loss: 1.8356 - accuracy: 0.4459 - val_loss: 1.6259 - val_accuracy: 0.1429
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8253 - accuracy: 0.4374 - val_loss: 1.6193 - val_accuracy: 0.1429
Epoch 12/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7791 - accuracy: 0.4484 - val_loss: 1.6127 - val_accuracy: 0.1429
Epoch 13/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7781 - accuracy: 0.4350 - val_loss: 1.6062 - val_accuracy: 0.1538
Epoch 14/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8012 - accuracy: 0.4338 - val_loss: 1.5997 - val_accuracy: 0.1648
Epoch 15/100
2/2 [==============================] - 0s 50ms/step - loss: 1.7487 - accuracy: 0.4714 - val_loss: 1.5933 - val_accuracy: 0.1758
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7583 - accuracy: 0.4362 - val_loss: 1.5868 - val_accuracy: 0.1758
Epoch 17/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6673 - accuracy: 0.4654 - val_loss: 1.5805 - val_accuracy: 0.1868
Epoch 18/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7008 - accuracy: 0.4642 - val_loss: 1.5741 - val_accuracy: 0.1978
Epoch 19/100
2/2 [==============================] - 0s 51ms/step - loss: 1.7084 - accuracy: 0.4569 - val_loss: 1.5679 - val_accuracy: 0.1978
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6880 - accuracy: 0.4629 - val_loss: 1.5617 - val_accuracy: 0.2088
Epoch 21/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6723 - accuracy: 0.4787 - val_loss: 1.5557 - val_accuracy: 0.2527
Epoch 22/100
2/2 [==============================] - 0s 49ms/step - loss: 1.6747 - accuracy: 0.4994 - val_loss: 1.5496 - val_accuracy: 0.2747
Epoch 23/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6831 - accuracy: 0.4678 - val_loss: 1.5436 - val_accuracy: 0.2967
Epoch 24/100
2/2 [==============================] - 0s 49ms/step - loss: 1.6364 - accuracy: 0.4982 - val_loss: 1.5377 - val_accuracy: 0.3187
Epoch 25/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6095 - accuracy: 0.4909 - val_loss: 1.5319 - val_accuracy: 0.3407
Epoch 26/100
2/2 [==============================] - 0s 50ms/step - loss: 1.6022 - accuracy: 0.5018 - val_loss: 1.5262 - val_accuracy: 0.3407
Epoch 27/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6107 - accuracy: 0.4933 - val_loss: 1.5205 - val_accuracy: 0.3626
Epoch 28/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6195 - accuracy: 0.4970 - val_loss: 1.5148 - val_accuracy: 0.3736
Epoch 29/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6105 - accuracy: 0.5164 - val_loss: 1.5093 - val_accuracy: 0.4066
Epoch 30/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5588 - accuracy: 0.5164 - val_loss: 1.5039 - val_accuracy: 0.4286
Epoch 31/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5866 - accuracy: 0.5140 - val_loss: 1.4986 - val_accuracy: 0.4725
Epoch 32/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5409 - accuracy: 0.5043 - val_loss: 1.4934 - val_accuracy: 0.4835
Epoch 33/100
2/2 [==============================] - 0s 52ms/step - loss: 1.5755 - accuracy: 0.5200 - val_loss: 1.4881 - val_accuracy: 0.5055
Epoch 34/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5757 - accuracy: 0.5322 - val_loss: 1.4830 - val_accuracy: 0.5385
Epoch 35/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5610 - accuracy: 0.5225 - val_loss: 1.4781 - val_accuracy: 0.5385
Epoch 36/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5623 - accuracy: 0.5358 - val_loss: 1.4731 - val_accuracy: 0.5385
Epoch 37/100
2/2 [==============================] - 0s 45ms/step - loss: 1.5414 - accuracy: 0.5456 - val_loss: 1.4683 - val_accuracy: 0.5385
Epoch 38/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5646 - accuracy: 0.5334 - val_loss: 1.4634 - val_accuracy: 0.5385
Epoch 39/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5127 - accuracy: 0.5504 - val_loss: 1.4587 - val_accuracy: 0.5604
Epoch 40/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5165 - accuracy: 0.5419 - val_loss: 1.4541 - val_accuracy: 0.5824
Epoch 41/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5397 - accuracy: 0.5383 - val_loss: 1.4496 - val_accuracy: 0.5934
Epoch 42/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5246 - accuracy: 0.5456 - val_loss: 1.4451 - val_accuracy: 0.6044
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5099 - accuracy: 0.5589 - val_loss: 1.4407 - val_accuracy: 0.6154
Epoch 44/100
2/2 [==============================] - 0s 30ms/step - loss: 1.4848 - accuracy: 0.5614 - val_loss: 1.4365 - val_accuracy: 0.6264
Epoch 45/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4901 - accuracy: 0.5699 - val_loss: 1.4323 - val_accuracy: 0.6264
Epoch 46/100
2/2 [==============================] - 0s 58ms/step - loss: 1.4904 - accuracy: 0.5541 - val_loss: 1.4282 - val_accuracy: 0.6374
Epoch 47/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4859 - accuracy: 0.5662 - val_loss: 1.4241 - val_accuracy: 0.6484
Epoch 48/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5361 - accuracy: 0.5504 - val_loss: 1.4201 - val_accuracy: 0.6593
Epoch 49/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4929 - accuracy: 0.5650 - val_loss: 1.4162 - val_accuracy: 0.6703
Epoch 50/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4955 - accuracy: 0.5638 - val_loss: 1.4123 - val_accuracy: 0.6813
Epoch 51/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4658 - accuracy: 0.5844 - val_loss: 1.4086 - val_accuracy: 0.6923
Epoch 52/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4474 - accuracy: 0.5759 - val_loss: 1.4049 - val_accuracy: 0.6923
Epoch 53/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4591 - accuracy: 0.5784 - val_loss: 1.4012 - val_accuracy: 0.6923
Epoch 54/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4375 - accuracy: 0.5869 - val_loss: 1.3976 - val_accuracy: 0.6923
Epoch 55/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4704 - accuracy: 0.5796 - val_loss: 1.3941 - val_accuracy: 0.6923
Epoch 56/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4541 - accuracy: 0.5735 - val_loss: 1.3906 - val_accuracy: 0.6923
Epoch 57/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4458 - accuracy: 0.5553 - val_loss: 1.3872 - val_accuracy: 0.7033
Epoch 58/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4452 - accuracy: 0.5942 - val_loss: 1.3837 - val_accuracy: 0.7033
Epoch 59/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4595 - accuracy: 0.5905 - val_loss: 1.3803 - val_accuracy: 0.7143
Epoch 60/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4281 - accuracy: 0.6051 - val_loss: 1.3770 - val_accuracy: 0.7363
Epoch 61/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4565 - accuracy: 0.6002 - val_loss: 1.3737 - val_accuracy: 0.7363
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4195 - accuracy: 0.5893 - val_loss: 1.3704 - val_accuracy: 0.7363
Epoch 63/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4139 - accuracy: 0.5942 - val_loss: 1.3672 - val_accuracy: 0.7363
Epoch 64/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4176 - accuracy: 0.6027 - val_loss: 1.3639 - val_accuracy: 0.7363
Epoch 65/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4208 - accuracy: 0.6051 - val_loss: 1.3607 - val_accuracy: 0.7473
Epoch 66/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4188 - accuracy: 0.6039 - val_loss: 1.3575 - val_accuracy: 0.7582
Epoch 67/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3935 - accuracy: 0.6209 - val_loss: 1.3544 - val_accuracy: 0.7582
Epoch 68/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3965 - accuracy: 0.6039 - val_loss: 1.3513 - val_accuracy: 0.7582
Epoch 69/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3895 - accuracy: 0.5966 - val_loss: 1.3482 - val_accuracy: 0.7692
Epoch 70/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3847 - accuracy: 0.6124 - val_loss: 1.3452 - val_accuracy: 0.7692
Epoch 71/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4160 - accuracy: 0.6027 - val_loss: 1.3421 - val_accuracy: 0.7692
Epoch 72/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3940 - accuracy: 0.6148 - val_loss: 1.3390 - val_accuracy: 0.7692
Epoch 73/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3727 - accuracy: 0.6245 - val_loss: 1.3359 - val_accuracy: 0.7692
Epoch 74/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3871 - accuracy: 0.6245 - val_loss: 1.3328 - val_accuracy: 0.7692
Epoch 75/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3909 - accuracy: 0.6063 - val_loss: 1.3297 - val_accuracy: 0.7692
Epoch 76/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3740 - accuracy: 0.6075 - val_loss: 1.3264 - val_accuracy: 0.7692
Epoch 77/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3579 - accuracy: 0.6245 - val_loss: 1.3232 - val_accuracy: 0.7692
Epoch 78/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3458 - accuracy: 0.6258 - val_loss: 1.3200 - val_accuracy: 0.7692
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3668 - accuracy: 0.6233 - val_loss: 1.3168 - val_accuracy: 0.7692
Epoch 80/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3757 - accuracy: 0.6185 - val_loss: 1.3135 - val_accuracy: 0.7692
Epoch 81/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3753 - accuracy: 0.6294 - val_loss: 1.3103 - val_accuracy: 0.7692
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3507 - accuracy: 0.6233 - val_loss: 1.3071 - val_accuracy: 0.7692
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3470 - accuracy: 0.6100 - val_loss: 1.3039 - val_accuracy: 0.7692
Epoch 84/100
2/2 [==============================] - 0s 68ms/step - loss: 1.3804 - accuracy: 0.6245 - val_loss: 1.3007 - val_accuracy: 0.7692
Epoch 85/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3533 - accuracy: 0.6416 - val_loss: 1.2975 - val_accuracy: 0.7692
Epoch 86/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3396 - accuracy: 0.6148 - val_loss: 1.2943 - val_accuracy: 0.7692
Epoch 87/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3751 - accuracy: 0.6221 - val_loss: 1.2912 - val_accuracy: 0.7802
Epoch 88/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3298 - accuracy: 0.6330 - val_loss: 1.2881 - val_accuracy: 0.7802
Epoch 89/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3193 - accuracy: 0.6549 - val_loss: 1.2850 - val_accuracy: 0.8022
Epoch 90/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3110 - accuracy: 0.6598 - val_loss: 1.2820 - val_accuracy: 0.8022
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3120 - accuracy: 0.6428 - val_loss: 1.2789 - val_accuracy: 0.8022
Epoch 92/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3062 - accuracy: 0.6501 - val_loss: 1.2759 - val_accuracy: 0.8132
Epoch 93/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3206 - accuracy: 0.6391 - val_loss: 1.2730 - val_accuracy: 0.8132
Epoch 94/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3331 - accuracy: 0.6391 - val_loss: 1.2701 - val_accuracy: 0.8132
Epoch 95/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2992 - accuracy: 0.6525 - val_loss: 1.2672 - val_accuracy: 0.8132
Epoch 96/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3020 - accuracy: 0.6549 - val_loss: 1.2643 - val_accuracy: 0.8132
Epoch 97/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3098 - accuracy: 0.6561 - val_loss: 1.2614 - val_accuracy: 0.8242
Epoch 98/100
2/2 [==============================] - 0s 57ms/step - loss: 1.3172 - accuracy: 0.6245 - val_loss: 1.2585 - val_accuracy: 0.8242
Epoch 99/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3007 - accuracy: 0.6646 - val_loss: 1.2557 - val_accuracy: 0.8242
Epoch 100/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3048 - accuracy: 0.6549 - val_loss: 1.2526 - val_accuracy: 0.8242
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 263ms/step - loss: 1.7996 - accuracy: 0.3609 - val_loss: 1.5682 - val_accuracy: 0.2527
Epoch 2/100
2/2 [==============================] - 0s 86ms/step - loss: 1.8042 - accuracy: 0.3633 - val_loss: 1.5656 - val_accuracy: 0.2747
Epoch 3/100
2/2 [==============================] - 0s 45ms/step - loss: 1.7844 - accuracy: 0.3426 - val_loss: 1.5630 - val_accuracy: 0.2857
Epoch 4/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7500 - accuracy: 0.3597 - val_loss: 1.5606 - val_accuracy: 0.3187
Epoch 5/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7141 - accuracy: 0.3913 - val_loss: 1.5581 - val_accuracy: 0.3407
Epoch 6/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7878 - accuracy: 0.3961 - val_loss: 1.5556 - val_accuracy: 0.3407
Epoch 7/100
2/2 [==============================] - 0s 50ms/step - loss: 1.7376 - accuracy: 0.4010 - val_loss: 1.5531 - val_accuracy: 0.3626
Epoch 8/100
2/2 [==============================] - 0s 52ms/step - loss: 1.7338 - accuracy: 0.3876 - val_loss: 1.5506 - val_accuracy: 0.3736
Epoch 9/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6916 - accuracy: 0.4192 - val_loss: 1.5481 - val_accuracy: 0.3736
Epoch 10/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6706 - accuracy: 0.4593 - val_loss: 1.5456 - val_accuracy: 0.4066
Epoch 11/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6772 - accuracy: 0.4289 - val_loss: 1.5431 - val_accuracy: 0.4176
Epoch 12/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6503 - accuracy: 0.4666 - val_loss: 1.5407 - val_accuracy: 0.4176
Epoch 13/100
2/2 [==============================] - 0s 52ms/step - loss: 1.6422 - accuracy: 0.4411 - val_loss: 1.5382 - val_accuracy: 0.4176
Epoch 14/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6273 - accuracy: 0.4593 - val_loss: 1.5357 - val_accuracy: 0.4286
Epoch 15/100
2/2 [==============================] - 0s 30ms/step - loss: 1.6123 - accuracy: 0.4702 - val_loss: 1.5333 - val_accuracy: 0.4505
Epoch 16/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5850 - accuracy: 0.4872 - val_loss: 1.5308 - val_accuracy: 0.4505
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5842 - accuracy: 0.4957 - val_loss: 1.5283 - val_accuracy: 0.4725
Epoch 18/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6169 - accuracy: 0.4933 - val_loss: 1.5258 - val_accuracy: 0.4945
Epoch 19/100
2/2 [==============================] - 0s 45ms/step - loss: 1.5935 - accuracy: 0.4970 - val_loss: 1.5232 - val_accuracy: 0.5055
Epoch 20/100
2/2 [==============================] - 0s 50ms/step - loss: 1.5822 - accuracy: 0.5152 - val_loss: 1.5208 - val_accuracy: 0.5275
Epoch 21/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5584 - accuracy: 0.5298 - val_loss: 1.5183 - val_accuracy: 0.5275
Epoch 22/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6212 - accuracy: 0.4848 - val_loss: 1.5158 - val_accuracy: 0.5275
Epoch 23/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5821 - accuracy: 0.5358 - val_loss: 1.5134 - val_accuracy: 0.5385
Epoch 24/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5568 - accuracy: 0.5334 - val_loss: 1.5109 - val_accuracy: 0.5385
Epoch 25/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5155 - accuracy: 0.5346 - val_loss: 1.5085 - val_accuracy: 0.5385
Epoch 26/100
2/2 [==============================] - 0s 53ms/step - loss: 1.5662 - accuracy: 0.5322 - val_loss: 1.5061 - val_accuracy: 0.5495
Epoch 27/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4970 - accuracy: 0.5650 - val_loss: 1.5036 - val_accuracy: 0.5714
Epoch 28/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5223 - accuracy: 0.5310 - val_loss: 1.5011 - val_accuracy: 0.5714
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5200 - accuracy: 0.5456 - val_loss: 1.4985 - val_accuracy: 0.5714
Epoch 30/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5086 - accuracy: 0.5638 - val_loss: 1.4960 - val_accuracy: 0.5824
Epoch 31/100
2/2 [==============================] - 0s 52ms/step - loss: 1.5305 - accuracy: 0.5358 - val_loss: 1.4934 - val_accuracy: 0.5824
Epoch 32/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5129 - accuracy: 0.5589 - val_loss: 1.4909 - val_accuracy: 0.5824
Epoch 33/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4992 - accuracy: 0.5699 - val_loss: 1.4884 - val_accuracy: 0.5824
Epoch 34/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4815 - accuracy: 0.5772 - val_loss: 1.4859 - val_accuracy: 0.5824
Epoch 35/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4769 - accuracy: 0.5784 - val_loss: 1.4834 - val_accuracy: 0.6044
Epoch 36/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4571 - accuracy: 0.5990 - val_loss: 1.4809 - val_accuracy: 0.6044
Epoch 37/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4809 - accuracy: 0.5808 - val_loss: 1.4783 - val_accuracy: 0.6044
Epoch 38/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4629 - accuracy: 0.5687 - val_loss: 1.4759 - val_accuracy: 0.6044
Epoch 39/100
2/2 [==============================] - 0s 27ms/step - loss: 1.4502 - accuracy: 0.5990 - val_loss: 1.4734 - val_accuracy: 0.6154
Epoch 40/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4791 - accuracy: 0.5565 - val_loss: 1.4710 - val_accuracy: 0.6154
Epoch 41/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4677 - accuracy: 0.5820 - val_loss: 1.4686 - val_accuracy: 0.6264
Epoch 42/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4761 - accuracy: 0.5857 - val_loss: 1.4662 - val_accuracy: 0.6374
Epoch 43/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4466 - accuracy: 0.5917 - val_loss: 1.4638 - val_accuracy: 0.6374
Epoch 44/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4365 - accuracy: 0.5917 - val_loss: 1.4615 - val_accuracy: 0.6484
Epoch 45/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4593 - accuracy: 0.5808 - val_loss: 1.4590 - val_accuracy: 0.6484
Epoch 46/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4193 - accuracy: 0.6087 - val_loss: 1.4566 - val_accuracy: 0.6484
Epoch 47/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4251 - accuracy: 0.6294 - val_loss: 1.4540 - val_accuracy: 0.6484
Epoch 48/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4069 - accuracy: 0.6221 - val_loss: 1.4516 - val_accuracy: 0.6484
Epoch 49/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4063 - accuracy: 0.6270 - val_loss: 1.4490 - val_accuracy: 0.6484
Epoch 50/100
2/2 [==============================] - 0s 53ms/step - loss: 1.4044 - accuracy: 0.6245 - val_loss: 1.4465 - val_accuracy: 0.6484
Epoch 51/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4475 - accuracy: 0.6160 - val_loss: 1.4439 - val_accuracy: 0.6484
Epoch 52/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4100 - accuracy: 0.6245 - val_loss: 1.4414 - val_accuracy: 0.6593
Epoch 53/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3941 - accuracy: 0.6160 - val_loss: 1.4388 - val_accuracy: 0.6593
Epoch 54/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3922 - accuracy: 0.6343 - val_loss: 1.4363 - val_accuracy: 0.6703
Epoch 55/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3933 - accuracy: 0.6245 - val_loss: 1.4337 - val_accuracy: 0.6703
Epoch 56/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4114 - accuracy: 0.6136 - val_loss: 1.4312 - val_accuracy: 0.6703
Epoch 57/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3904 - accuracy: 0.6282 - val_loss: 1.4287 - val_accuracy: 0.6703
Epoch 58/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4130 - accuracy: 0.6209 - val_loss: 1.4261 - val_accuracy: 0.6813
Epoch 59/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3768 - accuracy: 0.6258 - val_loss: 1.4236 - val_accuracy: 0.6813
Epoch 60/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3731 - accuracy: 0.6294 - val_loss: 1.4212 - val_accuracy: 0.6813
Epoch 61/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3575 - accuracy: 0.6513 - val_loss: 1.4188 - val_accuracy: 0.6813
Epoch 62/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3681 - accuracy: 0.6525 - val_loss: 1.4164 - val_accuracy: 0.6813
Epoch 63/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3888 - accuracy: 0.6355 - val_loss: 1.4140 - val_accuracy: 0.6813
Epoch 64/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3429 - accuracy: 0.6488 - val_loss: 1.4117 - val_accuracy: 0.6813
Epoch 65/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3384 - accuracy: 0.6574 - val_loss: 1.4094 - val_accuracy: 0.6813
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3674 - accuracy: 0.6464 - val_loss: 1.4071 - val_accuracy: 0.6813
Epoch 67/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3839 - accuracy: 0.6330 - val_loss: 1.4048 - val_accuracy: 0.6923
Epoch 68/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4014 - accuracy: 0.6452 - val_loss: 1.4025 - val_accuracy: 0.6923
Epoch 69/100
2/2 [==============================] - 0s 53ms/step - loss: 1.3531 - accuracy: 0.6379 - val_loss: 1.4002 - val_accuracy: 0.7033
Epoch 70/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3499 - accuracy: 0.6549 - val_loss: 1.3980 - val_accuracy: 0.7033
Epoch 71/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3336 - accuracy: 0.6428 - val_loss: 1.3957 - val_accuracy: 0.7143
Epoch 72/100
2/2 [==============================] - 0s 54ms/step - loss: 1.3277 - accuracy: 0.6707 - val_loss: 1.3935 - val_accuracy: 0.7143
Epoch 73/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3168 - accuracy: 0.6659 - val_loss: 1.3912 - val_accuracy: 0.7143
Epoch 74/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3517 - accuracy: 0.6513 - val_loss: 1.3891 - val_accuracy: 0.7143
Epoch 75/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3357 - accuracy: 0.6634 - val_loss: 1.3870 - val_accuracy: 0.7143
Epoch 76/100
2/2 [==============================] - 0s 52ms/step - loss: 1.3286 - accuracy: 0.6671 - val_loss: 1.3848 - val_accuracy: 0.7143
Epoch 77/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3399 - accuracy: 0.6561 - val_loss: 1.3827 - val_accuracy: 0.7143
Epoch 78/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3003 - accuracy: 0.6877 - val_loss: 1.3804 - val_accuracy: 0.7143
Epoch 79/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3262 - accuracy: 0.6403 - val_loss: 1.3782 - val_accuracy: 0.7143
Epoch 80/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3107 - accuracy: 0.6804 - val_loss: 1.3761 - val_accuracy: 0.7143
Epoch 81/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3156 - accuracy: 0.6683 - val_loss: 1.3738 - val_accuracy: 0.7143
Epoch 82/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2921 - accuracy: 0.6780 - val_loss: 1.3716 - val_accuracy: 0.7143
Epoch 83/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2918 - accuracy: 0.6780 - val_loss: 1.3694 - val_accuracy: 0.7143
Epoch 84/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2867 - accuracy: 0.6829 - val_loss: 1.3673 - val_accuracy: 0.7143
Epoch 85/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2838 - accuracy: 0.6707 - val_loss: 1.3652 - val_accuracy: 0.7143
Epoch 86/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3028 - accuracy: 0.6841 - val_loss: 1.3630 - val_accuracy: 0.7253
Epoch 87/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2704 - accuracy: 0.7035 - val_loss: 1.3607 - val_accuracy: 0.7143
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3091 - accuracy: 0.6744 - val_loss: 1.3583 - val_accuracy: 0.7143
Epoch 89/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3040 - accuracy: 0.6646 - val_loss: 1.3560 - val_accuracy: 0.7143
Epoch 90/100
2/2 [==============================] - 0s 53ms/step - loss: 1.2861 - accuracy: 0.6902 - val_loss: 1.3537 - val_accuracy: 0.7143
Epoch 91/100
2/2 [==============================] - 0s 34ms/step - loss: 1.2890 - accuracy: 0.6768 - val_loss: 1.3515 - val_accuracy: 0.7143
Epoch 92/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2731 - accuracy: 0.6768 - val_loss: 1.3492 - val_accuracy: 0.7143
Epoch 93/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2507 - accuracy: 0.7084 - val_loss: 1.3469 - val_accuracy: 0.7143
Epoch 94/100
2/2 [==============================] - 0s 57ms/step - loss: 1.2929 - accuracy: 0.6950 - val_loss: 1.3446 - val_accuracy: 0.7143
Epoch 95/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2819 - accuracy: 0.6914 - val_loss: 1.3424 - val_accuracy: 0.7143
Epoch 96/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2923 - accuracy: 0.6999 - val_loss: 1.3401 - val_accuracy: 0.7143
Epoch 97/100
2/2 [==============================] - 0s 46ms/step - loss: 1.2641 - accuracy: 0.6853 - val_loss: 1.3380 - val_accuracy: 0.7143
Epoch 98/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2936 - accuracy: 0.6926 - val_loss: 1.3358 - val_accuracy: 0.7143
Epoch 99/100
2/2 [==============================] - 0s 55ms/step - loss: 1.2423 - accuracy: 0.6938 - val_loss: 1.3337 - val_accuracy: 0.7143
Epoch 100/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2621 - accuracy: 0.6926 - val_loss: 1.3317 - val_accuracy: 0.7143
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 270us/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 266ms/step - loss: 2.1488 - accuracy: 0.2539 - val_loss: 1.3601 - val_accuracy: 0.8352
Epoch 2/100
2/2 [==============================] - 0s 53ms/step - loss: 2.1320 - accuracy: 0.2479 - val_loss: 1.3590 - val_accuracy: 0.8352
Epoch 3/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1138 - accuracy: 0.2612 - val_loss: 1.3581 - val_accuracy: 0.8462
Epoch 4/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1226 - accuracy: 0.2637 - val_loss: 1.3572 - val_accuracy: 0.8352
Epoch 5/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0942 - accuracy: 0.2600 - val_loss: 1.3563 - val_accuracy: 0.8242
Epoch 6/100
2/2 [==============================] - 0s 51ms/step - loss: 2.0542 - accuracy: 0.2734 - val_loss: 1.3553 - val_accuracy: 0.8242
Epoch 7/100
2/2 [==============================] - 0s 54ms/step - loss: 2.0415 - accuracy: 0.2770 - val_loss: 1.3544 - val_accuracy: 0.8132
Epoch 8/100
2/2 [==============================] - 0s 32ms/step - loss: 1.9623 - accuracy: 0.3111 - val_loss: 1.3534 - val_accuracy: 0.8132
Epoch 9/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9625 - accuracy: 0.3086 - val_loss: 1.3524 - val_accuracy: 0.8132
Epoch 10/100
2/2 [==============================] - 0s 49ms/step - loss: 1.9496 - accuracy: 0.2928 - val_loss: 1.3514 - val_accuracy: 0.8132
Epoch 11/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9463 - accuracy: 0.3086 - val_loss: 1.3504 - val_accuracy: 0.8132
Epoch 12/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9236 - accuracy: 0.3074 - val_loss: 1.3493 - val_accuracy: 0.8132
Epoch 13/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9268 - accuracy: 0.3256 - val_loss: 1.3483 - val_accuracy: 0.8132
Epoch 14/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8451 - accuracy: 0.3499 - val_loss: 1.3472 - val_accuracy: 0.8132
Epoch 15/100
2/2 [==============================] - 0s 51ms/step - loss: 1.8397 - accuracy: 0.3560 - val_loss: 1.3461 - val_accuracy: 0.8022
Epoch 16/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8243 - accuracy: 0.3584 - val_loss: 1.3450 - val_accuracy: 0.8022
Epoch 17/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8110 - accuracy: 0.3706 - val_loss: 1.3438 - val_accuracy: 0.8022
Epoch 18/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7896 - accuracy: 0.3670 - val_loss: 1.3428 - val_accuracy: 0.8022
Epoch 19/100
2/2 [==============================] - 0s 45ms/step - loss: 1.7914 - accuracy: 0.3767 - val_loss: 1.3416 - val_accuracy: 0.7912
Epoch 20/100
2/2 [==============================] - 0s 45ms/step - loss: 1.7847 - accuracy: 0.3913 - val_loss: 1.3405 - val_accuracy: 0.7912
Epoch 21/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7587 - accuracy: 0.4119 - val_loss: 1.3392 - val_accuracy: 0.8022
Epoch 22/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6942 - accuracy: 0.4107 - val_loss: 1.3380 - val_accuracy: 0.8132
Epoch 23/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7280 - accuracy: 0.3949 - val_loss: 1.3367 - val_accuracy: 0.8132
Epoch 24/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7323 - accuracy: 0.3985 - val_loss: 1.3354 - val_accuracy: 0.8132
Epoch 25/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7102 - accuracy: 0.3961 - val_loss: 1.3341 - val_accuracy: 0.8132
Epoch 26/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7200 - accuracy: 0.4046 - val_loss: 1.3327 - val_accuracy: 0.8132
Epoch 27/100
2/2 [==============================] - 0s 51ms/step - loss: 1.6952 - accuracy: 0.4034 - val_loss: 1.3313 - val_accuracy: 0.8132
Epoch 28/100
2/2 [==============================] - 0s 54ms/step - loss: 1.6431 - accuracy: 0.4435 - val_loss: 1.3299 - val_accuracy: 0.8132
Epoch 29/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6440 - accuracy: 0.4374 - val_loss: 1.3285 - val_accuracy: 0.8132
Epoch 30/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6399 - accuracy: 0.4399 - val_loss: 1.3272 - val_accuracy: 0.8132
Epoch 31/100
2/2 [==============================] - 0s 66ms/step - loss: 1.6559 - accuracy: 0.4338 - val_loss: 1.3258 - val_accuracy: 0.8132
Epoch 32/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6263 - accuracy: 0.4508 - val_loss: 1.3244 - val_accuracy: 0.8132
Epoch 33/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6264 - accuracy: 0.4459 - val_loss: 1.3230 - val_accuracy: 0.8132
Epoch 34/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6370 - accuracy: 0.4569 - val_loss: 1.3216 - val_accuracy: 0.8132
Epoch 35/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5999 - accuracy: 0.4642 - val_loss: 1.3202 - val_accuracy: 0.8132
Epoch 36/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6170 - accuracy: 0.4569 - val_loss: 1.3189 - val_accuracy: 0.8132
Epoch 37/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5849 - accuracy: 0.4970 - val_loss: 1.3176 - val_accuracy: 0.8132
Epoch 38/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5677 - accuracy: 0.4763 - val_loss: 1.3163 - val_accuracy: 0.8242
Epoch 39/100
2/2 [==============================] - 0s 50ms/step - loss: 1.5744 - accuracy: 0.4970 - val_loss: 1.3150 - val_accuracy: 0.8352
Epoch 40/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5609 - accuracy: 0.4885 - val_loss: 1.3137 - val_accuracy: 0.8352
Epoch 41/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5550 - accuracy: 0.5006 - val_loss: 1.3123 - val_accuracy: 0.8352
Epoch 42/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5669 - accuracy: 0.4897 - val_loss: 1.3109 - val_accuracy: 0.8352
Epoch 43/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5403 - accuracy: 0.5018 - val_loss: 1.3094 - val_accuracy: 0.8352
Epoch 44/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5583 - accuracy: 0.4945 - val_loss: 1.3080 - val_accuracy: 0.8352
Epoch 45/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5369 - accuracy: 0.5200 - val_loss: 1.3066 - val_accuracy: 0.8462
Epoch 46/100
2/2 [==============================] - 0s 52ms/step - loss: 1.5115 - accuracy: 0.5006 - val_loss: 1.3052 - val_accuracy: 0.8462
Epoch 47/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4806 - accuracy: 0.5346 - val_loss: 1.3038 - val_accuracy: 0.8462
Epoch 48/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5176 - accuracy: 0.5286 - val_loss: 1.3023 - val_accuracy: 0.8462
Epoch 49/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5295 - accuracy: 0.4885 - val_loss: 1.3009 - val_accuracy: 0.8462
Epoch 50/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5205 - accuracy: 0.5249 - val_loss: 1.2995 - val_accuracy: 0.8571
Epoch 51/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4730 - accuracy: 0.5407 - val_loss: 1.2980 - val_accuracy: 0.8462
Epoch 52/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4867 - accuracy: 0.5346 - val_loss: 1.2966 - val_accuracy: 0.8462
Epoch 53/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4799 - accuracy: 0.5358 - val_loss: 1.2951 - val_accuracy: 0.8462
Epoch 54/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4704 - accuracy: 0.5638 - val_loss: 1.2936 - val_accuracy: 0.8462
Epoch 55/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4724 - accuracy: 0.5346 - val_loss: 1.2922 - val_accuracy: 0.8462
Epoch 56/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4659 - accuracy: 0.5334 - val_loss: 1.2907 - val_accuracy: 0.8462
Epoch 57/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4611 - accuracy: 0.5395 - val_loss: 1.2892 - val_accuracy: 0.8462
Epoch 58/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4822 - accuracy: 0.5383 - val_loss: 1.2877 - val_accuracy: 0.8462
Epoch 59/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4285 - accuracy: 0.5541 - val_loss: 1.2862 - val_accuracy: 0.8462
Epoch 60/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4319 - accuracy: 0.5553 - val_loss: 1.2847 - val_accuracy: 0.8462
Epoch 61/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4736 - accuracy: 0.5286 - val_loss: 1.2831 - val_accuracy: 0.8462
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4128 - accuracy: 0.5687 - val_loss: 1.2816 - val_accuracy: 0.8462
Epoch 63/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4420 - accuracy: 0.5565 - val_loss: 1.2801 - val_accuracy: 0.8462
Epoch 64/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4504 - accuracy: 0.5492 - val_loss: 1.2786 - val_accuracy: 0.8462
Epoch 65/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4470 - accuracy: 0.5650 - val_loss: 1.2770 - val_accuracy: 0.8462
Epoch 66/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4211 - accuracy: 0.5626 - val_loss: 1.2753 - val_accuracy: 0.8462
Epoch 67/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4594 - accuracy: 0.5443 - val_loss: 1.2737 - val_accuracy: 0.8462
Epoch 68/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4461 - accuracy: 0.5650 - val_loss: 1.2719 - val_accuracy: 0.8462
Epoch 69/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4453 - accuracy: 0.5419 - val_loss: 1.2702 - val_accuracy: 0.8571
Epoch 70/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4085 - accuracy: 0.5687 - val_loss: 1.2685 - val_accuracy: 0.8571
Epoch 71/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4097 - accuracy: 0.5577 - val_loss: 1.2668 - val_accuracy: 0.8571
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4007 - accuracy: 0.5638 - val_loss: 1.2650 - val_accuracy: 0.8571
Epoch 73/100
2/2 [==============================] - 0s 52ms/step - loss: 1.4331 - accuracy: 0.5480 - val_loss: 1.2632 - val_accuracy: 0.8571
Epoch 74/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4216 - accuracy: 0.5419 - val_loss: 1.2614 - val_accuracy: 0.8571
Epoch 75/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4106 - accuracy: 0.5638 - val_loss: 1.2595 - val_accuracy: 0.8571
Epoch 76/100
2/2 [==============================] - 0s 28ms/step - loss: 1.4106 - accuracy: 0.5796 - val_loss: 1.2575 - val_accuracy: 0.8571
Epoch 77/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4065 - accuracy: 0.5662 - val_loss: 1.2555 - val_accuracy: 0.8571
Epoch 78/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3762 - accuracy: 0.5930 - val_loss: 1.2535 - val_accuracy: 0.8571
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4006 - accuracy: 0.5723 - val_loss: 1.2514 - val_accuracy: 0.8571
Epoch 80/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4192 - accuracy: 0.5638 - val_loss: 1.2494 - val_accuracy: 0.8571
Epoch 81/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3671 - accuracy: 0.6027 - val_loss: 1.2474 - val_accuracy: 0.8571
Epoch 82/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3681 - accuracy: 0.5820 - val_loss: 1.2453 - val_accuracy: 0.8571
Epoch 83/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3643 - accuracy: 0.6051 - val_loss: 1.2433 - val_accuracy: 0.8571
Epoch 84/100
2/2 [==============================] - 0s 113ms/step - loss: 1.3719 - accuracy: 0.5990 - val_loss: 1.2412 - val_accuracy: 0.8571
Epoch 85/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3606 - accuracy: 0.6173 - val_loss: 1.2391 - val_accuracy: 0.8571
Epoch 86/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3722 - accuracy: 0.5881 - val_loss: 1.2370 - val_accuracy: 0.8571
Epoch 87/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3562 - accuracy: 0.5966 - val_loss: 1.2349 - val_accuracy: 0.8571
Epoch 88/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3496 - accuracy: 0.6075 - val_loss: 1.2327 - val_accuracy: 0.8571
Epoch 89/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3478 - accuracy: 0.6063 - val_loss: 1.2305 - val_accuracy: 0.8571
Epoch 90/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3731 - accuracy: 0.5905 - val_loss: 1.2283 - val_accuracy: 0.8571
Epoch 91/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3323 - accuracy: 0.6185 - val_loss: 1.2260 - val_accuracy: 0.8571
Epoch 92/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3046 - accuracy: 0.6221 - val_loss: 1.2239 - val_accuracy: 0.8571
Epoch 93/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3089 - accuracy: 0.6270 - val_loss: 1.2216 - val_accuracy: 0.8571
Epoch 94/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3262 - accuracy: 0.6112 - val_loss: 1.2194 - val_accuracy: 0.8571
Epoch 95/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3420 - accuracy: 0.6197 - val_loss: 1.2172 - val_accuracy: 0.8571
Epoch 96/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3356 - accuracy: 0.6185 - val_loss: 1.2149 - val_accuracy: 0.8571
Epoch 97/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2964 - accuracy: 0.6245 - val_loss: 1.2127 - val_accuracy: 0.8571
Epoch 98/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2873 - accuracy: 0.6318 - val_loss: 1.2104 - val_accuracy: 0.8571
Epoch 99/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3466 - accuracy: 0.5808 - val_loss: 1.2082 - val_accuracy: 0.8571
Epoch 100/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3150 - accuracy: 0.6270 - val_loss: 1.2060 - val_accuracy: 0.8571
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 247ms/step - loss: 2.1543 - accuracy: 0.2661 - val_loss: 1.4816 - val_accuracy: 0.3077
Epoch 2/100
2/2 [==============================] - 0s 44ms/step - loss: 2.1077 - accuracy: 0.2807 - val_loss: 1.4782 - val_accuracy: 0.3297
Epoch 3/100
2/2 [==============================] - 0s 46ms/step - loss: 2.0497 - accuracy: 0.3123 - val_loss: 1.4748 - val_accuracy: 0.3516
Epoch 4/100
2/2 [==============================] - 0s 41ms/step - loss: 2.1039 - accuracy: 0.2673 - val_loss: 1.4713 - val_accuracy: 0.3626
Epoch 5/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0504 - accuracy: 0.2965 - val_loss: 1.4678 - val_accuracy: 0.3956
Epoch 6/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9724 - accuracy: 0.3086 - val_loss: 1.4644 - val_accuracy: 0.4176
Epoch 7/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9475 - accuracy: 0.3196 - val_loss: 1.4609 - val_accuracy: 0.4286
Epoch 8/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9445 - accuracy: 0.2928 - val_loss: 1.4574 - val_accuracy: 0.4725
Epoch 9/100
2/2 [==============================] - 0s 58ms/step - loss: 1.9267 - accuracy: 0.3050 - val_loss: 1.4539 - val_accuracy: 0.4835
Epoch 10/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9278 - accuracy: 0.3050 - val_loss: 1.4504 - val_accuracy: 0.5055
Epoch 11/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8774 - accuracy: 0.3439 - val_loss: 1.4469 - val_accuracy: 0.5055
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8518 - accuracy: 0.3354 - val_loss: 1.4434 - val_accuracy: 0.5275
Epoch 13/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8525 - accuracy: 0.3354 - val_loss: 1.4400 - val_accuracy: 0.5385
Epoch 14/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8015 - accuracy: 0.3572 - val_loss: 1.4365 - val_accuracy: 0.5385
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7772 - accuracy: 0.3512 - val_loss: 1.4331 - val_accuracy: 0.5824
Epoch 16/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7830 - accuracy: 0.3572 - val_loss: 1.4298 - val_accuracy: 0.5824
Epoch 17/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7523 - accuracy: 0.3730 - val_loss: 1.4264 - val_accuracy: 0.6044
Epoch 18/100
2/2 [==============================] - 0s 50ms/step - loss: 1.7411 - accuracy: 0.3706 - val_loss: 1.4230 - val_accuracy: 0.6044
Epoch 19/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7561 - accuracy: 0.3609 - val_loss: 1.4197 - val_accuracy: 0.6264
Epoch 20/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7739 - accuracy: 0.3755 - val_loss: 1.4164 - val_accuracy: 0.6374
Epoch 21/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6760 - accuracy: 0.4083 - val_loss: 1.4131 - val_accuracy: 0.6593
Epoch 22/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6744 - accuracy: 0.4156 - val_loss: 1.4099 - val_accuracy: 0.6593
Epoch 23/100
2/2 [==============================] - 0s 48ms/step - loss: 1.6668 - accuracy: 0.3998 - val_loss: 1.4068 - val_accuracy: 0.6593
Epoch 24/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6401 - accuracy: 0.4168 - val_loss: 1.4037 - val_accuracy: 0.6703
Epoch 25/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6855 - accuracy: 0.4143 - val_loss: 1.4006 - val_accuracy: 0.6703
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6589 - accuracy: 0.4204 - val_loss: 1.3975 - val_accuracy: 0.6703
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6653 - accuracy: 0.4435 - val_loss: 1.3944 - val_accuracy: 0.6923
Epoch 28/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6092 - accuracy: 0.4532 - val_loss: 1.3915 - val_accuracy: 0.7033
Epoch 29/100
2/2 [==============================] - 0s 53ms/step - loss: 1.6237 - accuracy: 0.4180 - val_loss: 1.3885 - val_accuracy: 0.7033
Epoch 30/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6295 - accuracy: 0.4471 - val_loss: 1.3856 - val_accuracy: 0.7033
Epoch 31/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5882 - accuracy: 0.4642 - val_loss: 1.3827 - val_accuracy: 0.7143
Epoch 32/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6092 - accuracy: 0.4411 - val_loss: 1.3799 - val_accuracy: 0.7143
Epoch 33/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5955 - accuracy: 0.4763 - val_loss: 1.3771 - val_accuracy: 0.7253
Epoch 34/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5779 - accuracy: 0.4629 - val_loss: 1.3743 - val_accuracy: 0.7143
Epoch 35/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5193 - accuracy: 0.5079 - val_loss: 1.3716 - val_accuracy: 0.7033
Epoch 36/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5937 - accuracy: 0.4848 - val_loss: 1.3690 - val_accuracy: 0.7033
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5345 - accuracy: 0.5006 - val_loss: 1.3663 - val_accuracy: 0.7033
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5449 - accuracy: 0.4860 - val_loss: 1.3637 - val_accuracy: 0.7033
Epoch 39/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5632 - accuracy: 0.4909 - val_loss: 1.3611 - val_accuracy: 0.7033
Epoch 40/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5330 - accuracy: 0.5079 - val_loss: 1.3585 - val_accuracy: 0.7033
Epoch 41/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5506 - accuracy: 0.5115 - val_loss: 1.3560 - val_accuracy: 0.7033
Epoch 42/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5291 - accuracy: 0.5006 - val_loss: 1.3535 - val_accuracy: 0.6923
Epoch 43/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5243 - accuracy: 0.5079 - val_loss: 1.3510 - val_accuracy: 0.7033
Epoch 44/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4887 - accuracy: 0.5213 - val_loss: 1.3485 - val_accuracy: 0.7143
Epoch 45/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5020 - accuracy: 0.5346 - val_loss: 1.3461 - val_accuracy: 0.7253
Epoch 46/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5152 - accuracy: 0.5043 - val_loss: 1.3436 - val_accuracy: 0.7253
Epoch 47/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5134 - accuracy: 0.5310 - val_loss: 1.3412 - val_accuracy: 0.7253
Epoch 48/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5109 - accuracy: 0.5358 - val_loss: 1.3388 - val_accuracy: 0.7253
Epoch 49/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4890 - accuracy: 0.5614 - val_loss: 1.3365 - val_accuracy: 0.7253
Epoch 50/100
2/2 [==============================] - 0s 28ms/step - loss: 1.4751 - accuracy: 0.5383 - val_loss: 1.3341 - val_accuracy: 0.7253
Epoch 51/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4855 - accuracy: 0.5371 - val_loss: 1.3319 - val_accuracy: 0.7253
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4587 - accuracy: 0.5723 - val_loss: 1.3296 - val_accuracy: 0.7363
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4789 - accuracy: 0.5273 - val_loss: 1.3273 - val_accuracy: 0.7363
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5231 - accuracy: 0.5310 - val_loss: 1.3250 - val_accuracy: 0.7363
Epoch 55/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4811 - accuracy: 0.5480 - val_loss: 1.3228 - val_accuracy: 0.7363
Epoch 56/100
2/2 [==============================] - 0s 52ms/step - loss: 1.4148 - accuracy: 0.5772 - val_loss: 1.3206 - val_accuracy: 0.7363
Epoch 57/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4655 - accuracy: 0.5614 - val_loss: 1.3184 - val_accuracy: 0.7363
Epoch 58/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4251 - accuracy: 0.5966 - val_loss: 1.3162 - val_accuracy: 0.7363
Epoch 59/100
2/2 [==============================] - 0s 31ms/step - loss: 1.4310 - accuracy: 0.5723 - val_loss: 1.3140 - val_accuracy: 0.7363
Epoch 60/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4294 - accuracy: 0.5881 - val_loss: 1.3118 - val_accuracy: 0.7363
Epoch 61/100
2/2 [==============================] - 0s 53ms/step - loss: 1.4216 - accuracy: 0.5723 - val_loss: 1.3097 - val_accuracy: 0.7363
Epoch 62/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4268 - accuracy: 0.5772 - val_loss: 1.3076 - val_accuracy: 0.7363
Epoch 63/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4632 - accuracy: 0.5419 - val_loss: 1.3055 - val_accuracy: 0.7363
Epoch 64/100
2/2 [==============================] - 0s 31ms/step - loss: 1.4354 - accuracy: 0.5480 - val_loss: 1.3034 - val_accuracy: 0.7363
Epoch 65/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4230 - accuracy: 0.5614 - val_loss: 1.3013 - val_accuracy: 0.7363
Epoch 66/100
2/2 [==============================] - 0s 53ms/step - loss: 1.4056 - accuracy: 0.6002 - val_loss: 1.2992 - val_accuracy: 0.7363
Epoch 67/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4091 - accuracy: 0.5942 - val_loss: 1.2971 - val_accuracy: 0.7473
Epoch 68/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4130 - accuracy: 0.5930 - val_loss: 1.2950 - val_accuracy: 0.7473
Epoch 69/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3643 - accuracy: 0.5990 - val_loss: 1.2929 - val_accuracy: 0.7582
Epoch 70/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3859 - accuracy: 0.5978 - val_loss: 1.2908 - val_accuracy: 0.7582
Epoch 71/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3756 - accuracy: 0.6002 - val_loss: 1.2887 - val_accuracy: 0.7582
Epoch 72/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3702 - accuracy: 0.6027 - val_loss: 1.2866 - val_accuracy: 0.7582
Epoch 73/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4170 - accuracy: 0.5723 - val_loss: 1.2846 - val_accuracy: 0.7582
Epoch 74/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4144 - accuracy: 0.5869 - val_loss: 1.2825 - val_accuracy: 0.7582
Epoch 75/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3990 - accuracy: 0.6015 - val_loss: 1.2804 - val_accuracy: 0.7582
Epoch 76/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3719 - accuracy: 0.6051 - val_loss: 1.2783 - val_accuracy: 0.7582
Epoch 77/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3331 - accuracy: 0.6039 - val_loss: 1.2763 - val_accuracy: 0.7582
Epoch 78/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3657 - accuracy: 0.6282 - val_loss: 1.2742 - val_accuracy: 0.7582
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3464 - accuracy: 0.6124 - val_loss: 1.2721 - val_accuracy: 0.7692
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3605 - accuracy: 0.6136 - val_loss: 1.2700 - val_accuracy: 0.7692
Epoch 81/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3399 - accuracy: 0.6173 - val_loss: 1.2679 - val_accuracy: 0.7582
Epoch 82/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3647 - accuracy: 0.6197 - val_loss: 1.2658 - val_accuracy: 0.7582
Epoch 83/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3229 - accuracy: 0.6233 - val_loss: 1.2637 - val_accuracy: 0.7582
Epoch 84/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3023 - accuracy: 0.6294 - val_loss: 1.2616 - val_accuracy: 0.7582
Epoch 85/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3491 - accuracy: 0.6197 - val_loss: 1.2594 - val_accuracy: 0.7582
Epoch 86/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3354 - accuracy: 0.6318 - val_loss: 1.2573 - val_accuracy: 0.7692
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3263 - accuracy: 0.6428 - val_loss: 1.2551 - val_accuracy: 0.7692
Epoch 88/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3235 - accuracy: 0.6221 - val_loss: 1.2529 - val_accuracy: 0.7692
Epoch 89/100
2/2 [==============================] - 0s 50ms/step - loss: 1.2899 - accuracy: 0.6452 - val_loss: 1.2507 - val_accuracy: 0.7692
Epoch 90/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3062 - accuracy: 0.6586 - val_loss: 1.2486 - val_accuracy: 0.7802
Epoch 91/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3203 - accuracy: 0.6488 - val_loss: 1.2464 - val_accuracy: 0.7802
Epoch 92/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3326 - accuracy: 0.6464 - val_loss: 1.2441 - val_accuracy: 0.7692
Epoch 93/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3188 - accuracy: 0.6355 - val_loss: 1.2419 - val_accuracy: 0.7692
Epoch 94/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2899 - accuracy: 0.6355 - val_loss: 1.2396 - val_accuracy: 0.7692
Epoch 95/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2691 - accuracy: 0.6561 - val_loss: 1.2373 - val_accuracy: 0.7692
Epoch 96/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3197 - accuracy: 0.6306 - val_loss: 1.2351 - val_accuracy: 0.7692
Epoch 97/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2915 - accuracy: 0.6379 - val_loss: 1.2329 - val_accuracy: 0.7692
Epoch 98/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3195 - accuracy: 0.6233 - val_loss: 1.2307 - val_accuracy: 0.7692
Epoch 99/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2819 - accuracy: 0.6731 - val_loss: 1.2285 - val_accuracy: 0.7692
Epoch 100/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3144 - accuracy: 0.6440 - val_loss: 1.2262 - val_accuracy: 0.7692
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Experiment number: 2
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 41ms/step - loss: 4.4602 - accuracy: 0.5949 - val_loss: 2.1631 - val_accuracy: 0.8370
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 1.7437 - accuracy: 0.8479 - val_loss: 1.9726 - val_accuracy: 0.8370
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 1.5721 - accuracy: 0.8333 - val_loss: 1.3117 - val_accuracy: 0.8370
Epoch 4/100
7/7 [==============================] - 0s 7ms/step - loss: 1.0905 - accuracy: 0.8564 - val_loss: 1.1831 - val_accuracy: 0.8370
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 1.0277 - accuracy: 0.8455 - val_loss: 0.9624 - val_accuracy: 0.8370
Epoch 6/100
7/7 [==============================] - 0s 10ms/step - loss: 0.8687 - accuracy: 0.8504 - val_loss: 0.9728 - val_accuracy: 0.8370
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8567 - accuracy: 0.8504 - val_loss: 0.9992 - val_accuracy: 0.8370
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7856 - accuracy: 0.8564 - val_loss: 0.9057 - val_accuracy: 0.8370
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8206 - accuracy: 0.8333 - val_loss: 0.9617 - val_accuracy: 0.8370
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8244 - accuracy: 0.8528 - val_loss: 0.9834 - val_accuracy: 0.8370
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8051 - accuracy: 0.8552 - val_loss: 0.9001 - val_accuracy: 0.8370
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8113 - accuracy: 0.8406 - val_loss: 1.0726 - val_accuracy: 0.8370
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8711 - accuracy: 0.8577 - val_loss: 0.9341 - val_accuracy: 0.8370
Epoch 14/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7848 - accuracy: 0.8564 - val_loss: 0.8967 - val_accuracy: 0.8370
Epoch 15/100
7/7 [==============================] - 0s 14ms/step - loss: 0.7955 - accuracy: 0.8431 - val_loss: 0.9771 - val_accuracy: 0.8370
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8400 - accuracy: 0.8540 - val_loss: 1.0365 - val_accuracy: 0.8370
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 1.0713 - accuracy: 0.8479 - val_loss: 1.1162 - val_accuracy: 0.8370
Epoch 18/100
7/7 [==============================] - 0s 6ms/step - loss: 0.9208 - accuracy: 0.8662 - val_loss: 0.9435 - val_accuracy: 0.8370
Epoch 19/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7882 - accuracy: 0.8540 - val_loss: 0.9532 - val_accuracy: 0.8370
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8502 - accuracy: 0.8479 - val_loss: 0.9690 - val_accuracy: 0.8370
Epoch 21/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8741 - accuracy: 0.8394 - val_loss: 0.9876 - val_accuracy: 0.8370
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8310 - accuracy: 0.8686 - val_loss: 0.9299 - val_accuracy: 0.8370
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9063 - accuracy: 0.8443 - val_loss: 0.9105 - val_accuracy: 0.8370
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8123 - accuracy: 0.8540 - val_loss: 0.9522 - val_accuracy: 0.8370
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8666 - accuracy: 0.8455 - val_loss: 0.9466 - val_accuracy: 0.8370
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8237 - accuracy: 0.8564 - val_loss: 0.9469 - val_accuracy: 0.8370
Epoch 27/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8405 - accuracy: 0.8516 - val_loss: 0.9591 - val_accuracy: 0.8370
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8176 - accuracy: 0.8564 - val_loss: 0.9634 - val_accuracy: 0.8370
Epoch 29/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8084 - accuracy: 0.8564 - val_loss: 0.9536 - val_accuracy: 0.8370
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8593 - accuracy: 0.8552 - val_loss: 0.9920 - val_accuracy: 0.8370
Epoch 31/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8384 - accuracy: 0.8479 - val_loss: 0.9195 - val_accuracy: 0.8370
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8170 - accuracy: 0.8491 - val_loss: 0.8753 - val_accuracy: 0.8370
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8418 - accuracy: 0.8406 - val_loss: 0.9287 - val_accuracy: 0.8370
Epoch 34/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8108 - accuracy: 0.8625 - val_loss: 0.9380 - val_accuracy: 0.8370
Epoch 35/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7665 - accuracy: 0.8577 - val_loss: 0.9052 - val_accuracy: 0.8370
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7923 - accuracy: 0.8504 - val_loss: 0.8550 - val_accuracy: 0.8370
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7612 - accuracy: 0.8589 - val_loss: 0.9383 - val_accuracy: 0.8370
Epoch 38/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8345 - accuracy: 0.8577 - val_loss: 0.9412 - val_accuracy: 0.8370
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8173 - accuracy: 0.8625 - val_loss: 0.8916 - val_accuracy: 0.8370
Epoch 40/100
7/7 [==============================] - 0s 10ms/step - loss: 0.8043 - accuracy: 0.8504 - val_loss: 0.9075 - val_accuracy: 0.8370
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8078 - accuracy: 0.8504 - val_loss: 0.8777 - val_accuracy: 0.8370
Epoch 42/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8046 - accuracy: 0.8613 - val_loss: 0.8853 - val_accuracy: 0.8370
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7713 - accuracy: 0.8601 - val_loss: 0.8759 - val_accuracy: 0.8370
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8546 - accuracy: 0.8431 - val_loss: 0.8775 - val_accuracy: 0.8370
Epoch 45/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7528 - accuracy: 0.8516 - val_loss: 0.8505 - val_accuracy: 0.8370
Epoch 46/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7889 - accuracy: 0.8577 - val_loss: 0.8760 - val_accuracy: 0.8370
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7554 - accuracy: 0.8686 - val_loss: 0.8669 - val_accuracy: 0.8370
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7747 - accuracy: 0.8479 - val_loss: 0.8788 - val_accuracy: 0.8261
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7911 - accuracy: 0.8674 - val_loss: 0.8936 - val_accuracy: 0.8370
Epoch 50/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8081 - accuracy: 0.8479 - val_loss: 0.8935 - val_accuracy: 0.8370
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8607 - accuracy: 0.8516 - val_loss: 0.8774 - val_accuracy: 0.8370
Epoch 52/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7943 - accuracy: 0.8504 - val_loss: 0.8676 - val_accuracy: 0.8261
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8363 - accuracy: 0.8540 - val_loss: 0.9106 - val_accuracy: 0.8370
Epoch 54/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8356 - accuracy: 0.8577 - val_loss: 0.8140 - val_accuracy: 0.8370
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7611 - accuracy: 0.8516 - val_loss: 0.8306 - val_accuracy: 0.8370
Epoch 56/100
7/7 [==============================] - 0s 15ms/step - loss: 0.7627 - accuracy: 0.8601 - val_loss: 0.8944 - val_accuracy: 0.8370
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7633 - accuracy: 0.8528 - val_loss: 0.7966 - val_accuracy: 0.8261
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7394 - accuracy: 0.8516 - val_loss: 0.7845 - val_accuracy: 0.8370
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7251 - accuracy: 0.8552 - val_loss: 0.8181 - val_accuracy: 0.8370
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7599 - accuracy: 0.8564 - val_loss: 0.8485 - val_accuracy: 0.8261
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7769 - accuracy: 0.8504 - val_loss: 0.8514 - val_accuracy: 0.8370
Epoch 62/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7538 - accuracy: 0.8564 - val_loss: 0.8619 - val_accuracy: 0.8370
Epoch 63/100
7/7 [==============================] - 0s 5ms/step - loss: 0.7622 - accuracy: 0.8601 - val_loss: 0.7946 - val_accuracy: 0.8261
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7639 - accuracy: 0.8564 - val_loss: 0.8291 - val_accuracy: 0.8261
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8395 - accuracy: 0.8577 - val_loss: 0.8175 - val_accuracy: 0.8370
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7864 - accuracy: 0.8528 - val_loss: 0.8753 - val_accuracy: 0.8370
Epoch 67/100
7/7 [==============================] - 0s 5ms/step - loss: 0.8285 - accuracy: 0.8540 - val_loss: 0.8838 - val_accuracy: 0.8587
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8236 - accuracy: 0.8504 - val_loss: 0.7992 - val_accuracy: 0.8478
Epoch 69/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7835 - accuracy: 0.8577 - val_loss: 0.8449 - val_accuracy: 0.8478
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8165 - accuracy: 0.8650 - val_loss: 0.8275 - val_accuracy: 0.8152
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8117 - accuracy: 0.8540 - val_loss: 0.8364 - val_accuracy: 0.8261
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8190 - accuracy: 0.8479 - val_loss: 0.8489 - val_accuracy: 0.8370
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7348 - accuracy: 0.8431 - val_loss: 0.8515 - val_accuracy: 0.8152
Epoch 74/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7965 - accuracy: 0.8601 - val_loss: 0.9958 - val_accuracy: 0.7935
Epoch 75/100
7/7 [==============================] - 0s 11ms/step - loss: 0.8609 - accuracy: 0.8552 - val_loss: 0.9215 - val_accuracy: 0.8370
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8687 - accuracy: 0.8504 - val_loss: 0.8903 - val_accuracy: 0.8152
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7871 - accuracy: 0.8625 - val_loss: 0.8567 - val_accuracy: 0.8370
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7633 - accuracy: 0.8613 - val_loss: 0.9291 - val_accuracy: 0.8370
Epoch 79/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8690 - accuracy: 0.8564 - val_loss: 0.9822 - val_accuracy: 0.8152
Epoch 80/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7978 - accuracy: 0.8686 - val_loss: 0.9884 - val_accuracy: 0.7391
Epoch 81/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8046 - accuracy: 0.8577 - val_loss: 0.8045 - val_accuracy: 0.8478
Epoch 82/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7696 - accuracy: 0.8516 - val_loss: 0.8724 - val_accuracy: 0.7935
Epoch 83/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8114 - accuracy: 0.8577 - val_loss: 0.9273 - val_accuracy: 0.8043
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8264 - accuracy: 0.8552 - val_loss: 0.8534 - val_accuracy: 0.8587
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7773 - accuracy: 0.8431 - val_loss: 0.9164 - val_accuracy: 0.8152
Epoch 86/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7724 - accuracy: 0.8504 - val_loss: 0.7792 - val_accuracy: 0.8478
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7590 - accuracy: 0.8552 - val_loss: 0.7767 - val_accuracy: 0.8478
Epoch 88/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7769 - accuracy: 0.8418 - val_loss: 0.8417 - val_accuracy: 0.8478
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7963 - accuracy: 0.8564 - val_loss: 0.8202 - val_accuracy: 0.8478
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8078 - accuracy: 0.8418 - val_loss: 0.8364 - val_accuracy: 0.8261
Epoch 91/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7687 - accuracy: 0.8516 - val_loss: 0.7943 - val_accuracy: 0.8804
Epoch 92/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8367 - accuracy: 0.8577 - val_loss: 0.9305 - val_accuracy: 0.8152
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7961 - accuracy: 0.8431 - val_loss: 0.8450 - val_accuracy: 0.7935
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7777 - accuracy: 0.8564 - val_loss: 0.9364 - val_accuracy: 0.7717
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 0.9347 - accuracy: 0.8406 - val_loss: 1.0432 - val_accuracy: 0.7500
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8291 - accuracy: 0.8540 - val_loss: 0.8224 - val_accuracy: 0.8370
Epoch 97/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7785 - accuracy: 0.8564 - val_loss: 0.8231 - val_accuracy: 0.8261
Epoch 98/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8236 - accuracy: 0.8491 - val_loss: 0.8062 - val_accuracy: 0.8261
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7394 - accuracy: 0.8613 - val_loss: 0.8375 - val_accuracy: 0.8478
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7924 - accuracy: 0.8528 - val_loss: 0.8116 - val_accuracy: 0.8804
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 41ms/step - loss: 4.1821 - accuracy: 0.5998 - val_loss: 2.2211 - val_accuracy: 0.7935
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 1.8427 - accuracy: 0.8552 - val_loss: 1.8760 - val_accuracy: 0.7935
Epoch 3/100
7/7 [==============================] - 0s 7ms/step - loss: 1.6416 - accuracy: 0.8394 - val_loss: 1.3150 - val_accuracy: 0.7935
Epoch 4/100
7/7 [==============================] - 0s 6ms/step - loss: 1.1529 - accuracy: 0.8491 - val_loss: 1.2196 - val_accuracy: 0.7935
Epoch 5/100
7/7 [==============================] - 0s 5ms/step - loss: 1.0459 - accuracy: 0.8467 - val_loss: 1.0916 - val_accuracy: 0.7935
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9340 - accuracy: 0.8504 - val_loss: 1.1528 - val_accuracy: 0.7935
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9616 - accuracy: 0.8601 - val_loss: 1.0127 - val_accuracy: 0.7935
Epoch 8/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8376 - accuracy: 0.8504 - val_loss: 0.9774 - val_accuracy: 0.7935
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8522 - accuracy: 0.8552 - val_loss: 0.9391 - val_accuracy: 0.7935
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7922 - accuracy: 0.8577 - val_loss: 0.9349 - val_accuracy: 0.7935
Epoch 11/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7649 - accuracy: 0.8564 - val_loss: 0.9171 - val_accuracy: 0.7935
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8063 - accuracy: 0.8418 - val_loss: 0.8414 - val_accuracy: 0.7935
Epoch 13/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7732 - accuracy: 0.8552 - val_loss: 0.8534 - val_accuracy: 0.7935
Epoch 14/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7930 - accuracy: 0.8552 - val_loss: 0.8882 - val_accuracy: 0.7935
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7682 - accuracy: 0.8528 - val_loss: 0.8816 - val_accuracy: 0.7935
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7718 - accuracy: 0.8637 - val_loss: 0.8342 - val_accuracy: 0.7935
Epoch 17/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7789 - accuracy: 0.8479 - val_loss: 0.8883 - val_accuracy: 0.7935
Epoch 18/100
7/7 [==============================] - 0s 11ms/step - loss: 0.7574 - accuracy: 0.8625 - val_loss: 0.8230 - val_accuracy: 0.7935
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8103 - accuracy: 0.8370 - val_loss: 0.8529 - val_accuracy: 0.7935
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7488 - accuracy: 0.8589 - val_loss: 0.8550 - val_accuracy: 0.7935
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7655 - accuracy: 0.8431 - val_loss: 0.8929 - val_accuracy: 0.7935
Epoch 22/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7673 - accuracy: 0.8504 - val_loss: 0.8709 - val_accuracy: 0.7935
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7934 - accuracy: 0.8394 - val_loss: 0.9466 - val_accuracy: 0.7935
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8322 - accuracy: 0.8564 - val_loss: 0.8558 - val_accuracy: 0.7935
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8164 - accuracy: 0.8418 - val_loss: 0.8563 - val_accuracy: 0.7935
Epoch 26/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7275 - accuracy: 0.8528 - val_loss: 0.7841 - val_accuracy: 0.7935
Epoch 27/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7294 - accuracy: 0.8637 - val_loss: 0.8979 - val_accuracy: 0.7935
Epoch 28/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7403 - accuracy: 0.8601 - val_loss: 0.7993 - val_accuracy: 0.7935
Epoch 29/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7649 - accuracy: 0.8528 - val_loss: 0.8817 - val_accuracy: 0.7935
Epoch 30/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7707 - accuracy: 0.8601 - val_loss: 0.8561 - val_accuracy: 0.7935
Epoch 31/100
7/7 [==============================] - 0s 5ms/step - loss: 0.7621 - accuracy: 0.8479 - val_loss: 0.8727 - val_accuracy: 0.7935
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7514 - accuracy: 0.8528 - val_loss: 0.8276 - val_accuracy: 0.7935
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7546 - accuracy: 0.8601 - val_loss: 0.9279 - val_accuracy: 0.7935
Epoch 34/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7926 - accuracy: 0.8528 - val_loss: 0.8237 - val_accuracy: 0.7935
Epoch 35/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7572 - accuracy: 0.8637 - val_loss: 0.7874 - val_accuracy: 0.7935
Epoch 36/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7581 - accuracy: 0.8577 - val_loss: 0.8139 - val_accuracy: 0.7935
Epoch 37/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7384 - accuracy: 0.8467 - val_loss: 0.8149 - val_accuracy: 0.7935
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8053 - accuracy: 0.8467 - val_loss: 0.8531 - val_accuracy: 0.7935
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7235 - accuracy: 0.8540 - val_loss: 0.8436 - val_accuracy: 0.7935
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7650 - accuracy: 0.8552 - val_loss: 0.7713 - val_accuracy: 0.7935
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7243 - accuracy: 0.8504 - val_loss: 0.7992 - val_accuracy: 0.7935
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7154 - accuracy: 0.8552 - val_loss: 0.7563 - val_accuracy: 0.7935
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7287 - accuracy: 0.8467 - val_loss: 0.7435 - val_accuracy: 0.8261
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8139 - accuracy: 0.8528 - val_loss: 0.8751 - val_accuracy: 0.7935
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7287 - accuracy: 0.8552 - val_loss: 0.7628 - val_accuracy: 0.7935
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7704 - accuracy: 0.8491 - val_loss: 0.7886 - val_accuracy: 0.8043
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7665 - accuracy: 0.8516 - val_loss: 0.8405 - val_accuracy: 0.7935
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7542 - accuracy: 0.8504 - val_loss: 0.8153 - val_accuracy: 0.8043
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7139 - accuracy: 0.8577 - val_loss: 0.7902 - val_accuracy: 0.7935
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7121 - accuracy: 0.8491 - val_loss: 0.7377 - val_accuracy: 0.7935
Epoch 51/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7782 - accuracy: 0.8577 - val_loss: 0.7442 - val_accuracy: 0.8043
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7565 - accuracy: 0.8613 - val_loss: 0.8920 - val_accuracy: 0.7826
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7631 - accuracy: 0.8601 - val_loss: 0.7951 - val_accuracy: 0.7935
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7598 - accuracy: 0.8625 - val_loss: 0.7256 - val_accuracy: 0.8043
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7365 - accuracy: 0.8698 - val_loss: 0.8219 - val_accuracy: 0.7935
Epoch 56/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7384 - accuracy: 0.8577 - val_loss: 0.8481 - val_accuracy: 0.7717
Epoch 57/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8248 - accuracy: 0.8516 - val_loss: 0.8396 - val_accuracy: 0.7717
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7282 - accuracy: 0.8601 - val_loss: 0.7134 - val_accuracy: 0.7935
Epoch 59/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7113 - accuracy: 0.8564 - val_loss: 0.7274 - val_accuracy: 0.8043
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7241 - accuracy: 0.8662 - val_loss: 0.7697 - val_accuracy: 0.8043
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8106 - accuracy: 0.8467 - val_loss: 0.7918 - val_accuracy: 0.8043
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7536 - accuracy: 0.8650 - val_loss: 0.7257 - val_accuracy: 0.7935
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7194 - accuracy: 0.8564 - val_loss: 0.7328 - val_accuracy: 0.8043
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7408 - accuracy: 0.8662 - val_loss: 0.7042 - val_accuracy: 0.8152
Epoch 65/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7201 - accuracy: 0.8601 - val_loss: 0.8490 - val_accuracy: 0.7935
Epoch 66/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7333 - accuracy: 0.8564 - val_loss: 0.7282 - val_accuracy: 0.7935
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7186 - accuracy: 0.8589 - val_loss: 0.7148 - val_accuracy: 0.8043
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7167 - accuracy: 0.8540 - val_loss: 0.7848 - val_accuracy: 0.7935
Epoch 69/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7759 - accuracy: 0.8467 - val_loss: 0.7184 - val_accuracy: 0.8152
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7005 - accuracy: 0.8577 - val_loss: 0.7874 - val_accuracy: 0.7935
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7751 - accuracy: 0.8504 - val_loss: 0.7061 - val_accuracy: 0.8152
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7242 - accuracy: 0.8528 - val_loss: 0.9419 - val_accuracy: 0.7391
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7568 - accuracy: 0.8601 - val_loss: 0.7612 - val_accuracy: 0.7935
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7072 - accuracy: 0.8613 - val_loss: 0.7155 - val_accuracy: 0.7935
Epoch 75/100
7/7 [==============================] - 0s 7ms/step - loss: 0.6717 - accuracy: 0.8552 - val_loss: 0.7378 - val_accuracy: 0.8152
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7410 - accuracy: 0.8540 - val_loss: 0.7290 - val_accuracy: 0.7391
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7539 - accuracy: 0.8479 - val_loss: 0.7829 - val_accuracy: 0.7935
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7260 - accuracy: 0.8528 - val_loss: 0.7241 - val_accuracy: 0.7935
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7347 - accuracy: 0.8467 - val_loss: 0.7713 - val_accuracy: 0.7935
Epoch 80/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7294 - accuracy: 0.8650 - val_loss: 0.7974 - val_accuracy: 0.8043
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7227 - accuracy: 0.8552 - val_loss: 0.7492 - val_accuracy: 0.7935
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7468 - accuracy: 0.8504 - val_loss: 0.7703 - val_accuracy: 0.7935
Epoch 83/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7351 - accuracy: 0.8564 - val_loss: 0.7511 - val_accuracy: 0.7935
Epoch 84/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7562 - accuracy: 0.8528 - val_loss: 0.7324 - val_accuracy: 0.8261
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7868 - accuracy: 0.8516 - val_loss: 0.8543 - val_accuracy: 0.7826
Epoch 86/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7502 - accuracy: 0.8613 - val_loss: 0.8100 - val_accuracy: 0.7935
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 0.6973 - accuracy: 0.8637 - val_loss: 0.7331 - val_accuracy: 0.7935
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7698 - accuracy: 0.8552 - val_loss: 0.7548 - val_accuracy: 0.7935
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7377 - accuracy: 0.8552 - val_loss: 0.7091 - val_accuracy: 0.8152
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7534 - accuracy: 0.8613 - val_loss: 0.7355 - val_accuracy: 0.8478
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7360 - accuracy: 0.8637 - val_loss: 0.8211 - val_accuracy: 0.7826
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7545 - accuracy: 0.8564 - val_loss: 0.7378 - val_accuracy: 0.8043
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7247 - accuracy: 0.8589 - val_loss: 0.8204 - val_accuracy: 0.7826
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7388 - accuracy: 0.8455 - val_loss: 0.7640 - val_accuracy: 0.7935
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7503 - accuracy: 0.8589 - val_loss: 0.7349 - val_accuracy: 0.7935
Epoch 96/100
7/7 [==============================] - 0s 9ms/step - loss: 0.6872 - accuracy: 0.8650 - val_loss: 0.7379 - val_accuracy: 0.7935
Epoch 97/100
7/7 [==============================] - 0s 6ms/step - loss: 0.6850 - accuracy: 0.8674 - val_loss: 0.7304 - val_accuracy: 0.7935
Epoch 98/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7120 - accuracy: 0.8601 - val_loss: 0.6508 - val_accuracy: 0.8478
Epoch 99/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7351 - accuracy: 0.8479 - val_loss: 0.7413 - val_accuracy: 0.8261
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7146 - accuracy: 0.8491 - val_loss: 0.6836 - val_accuracy: 0.8261
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 4.1614 - accuracy: 0.5742 - val_loss: 2.0147 - val_accuracy: 0.8152
Epoch 2/100
7/7 [==============================] - 0s 7ms/step - loss: 1.7059 - accuracy: 0.8552 - val_loss: 2.1029 - val_accuracy: 0.8152
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 1.6021 - accuracy: 0.8552 - val_loss: 1.4015 - val_accuracy: 0.8152
Epoch 4/100
7/7 [==============================] - 0s 6ms/step - loss: 1.2613 - accuracy: 0.8443 - val_loss: 1.3468 - val_accuracy: 0.8152
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 1.0790 - accuracy: 0.8637 - val_loss: 1.1113 - val_accuracy: 0.8152
Epoch 6/100
7/7 [==============================] - 0s 7ms/step - loss: 0.9213 - accuracy: 0.8491 - val_loss: 1.0396 - val_accuracy: 0.8152
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8600 - accuracy: 0.8577 - val_loss: 0.9995 - val_accuracy: 0.8152
Epoch 8/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8332 - accuracy: 0.8467 - val_loss: 0.9558 - val_accuracy: 0.8152
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8071 - accuracy: 0.8406 - val_loss: 0.9789 - val_accuracy: 0.8152
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7893 - accuracy: 0.8516 - val_loss: 0.9874 - val_accuracy: 0.8152
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8336 - accuracy: 0.8613 - val_loss: 0.9558 - val_accuracy: 0.8152
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8272 - accuracy: 0.8577 - val_loss: 1.1053 - val_accuracy: 0.8152
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8310 - accuracy: 0.8577 - val_loss: 0.9809 - val_accuracy: 0.8152
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8279 - accuracy: 0.8577 - val_loss: 1.0286 - val_accuracy: 0.8152
Epoch 15/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8072 - accuracy: 0.8650 - val_loss: 0.9497 - val_accuracy: 0.8152
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7389 - accuracy: 0.8601 - val_loss: 0.9228 - val_accuracy: 0.8152
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8013 - accuracy: 0.8418 - val_loss: 0.9381 - val_accuracy: 0.8152
Epoch 18/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8195 - accuracy: 0.8504 - val_loss: 0.9650 - val_accuracy: 0.8152
Epoch 19/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8202 - accuracy: 0.8479 - val_loss: 0.9125 - val_accuracy: 0.8152
Epoch 20/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7935 - accuracy: 0.8491 - val_loss: 0.8727 - val_accuracy: 0.8152
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7566 - accuracy: 0.8577 - val_loss: 0.8627 - val_accuracy: 0.8152
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7564 - accuracy: 0.8564 - val_loss: 0.8644 - val_accuracy: 0.8152
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7763 - accuracy: 0.8479 - val_loss: 0.9264 - val_accuracy: 0.8152
Epoch 24/100
7/7 [==============================] - 0s 17ms/step - loss: 0.8063 - accuracy: 0.8455 - val_loss: 0.9084 - val_accuracy: 0.8152
Epoch 25/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7979 - accuracy: 0.8552 - val_loss: 0.8844 - val_accuracy: 0.8152
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7819 - accuracy: 0.8491 - val_loss: 0.9111 - val_accuracy: 0.8152
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7864 - accuracy: 0.8467 - val_loss: 0.9412 - val_accuracy: 0.8152
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7914 - accuracy: 0.8516 - val_loss: 0.9402 - val_accuracy: 0.8152
Epoch 29/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8114 - accuracy: 0.8552 - val_loss: 0.8982 - val_accuracy: 0.8152
Epoch 30/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8327 - accuracy: 0.8564 - val_loss: 0.9131 - val_accuracy: 0.8152
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8092 - accuracy: 0.8564 - val_loss: 0.8701 - val_accuracy: 0.8152
Epoch 32/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7320 - accuracy: 0.8516 - val_loss: 0.8640 - val_accuracy: 0.8152
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7859 - accuracy: 0.8577 - val_loss: 0.9013 - val_accuracy: 0.8152
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7643 - accuracy: 0.8552 - val_loss: 0.9189 - val_accuracy: 0.8152
Epoch 35/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7902 - accuracy: 0.8443 - val_loss: 0.9761 - val_accuracy: 0.8152
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8667 - accuracy: 0.8491 - val_loss: 0.8571 - val_accuracy: 0.8152
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7835 - accuracy: 0.8589 - val_loss: 0.9076 - val_accuracy: 0.8152
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8187 - accuracy: 0.8491 - val_loss: 0.9269 - val_accuracy: 0.8152
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7724 - accuracy: 0.8625 - val_loss: 0.8446 - val_accuracy: 0.8152
Epoch 40/100
7/7 [==============================] - 0s 11ms/step - loss: 0.8084 - accuracy: 0.8589 - val_loss: 0.9387 - val_accuracy: 0.8152
Epoch 41/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8277 - accuracy: 0.8504 - val_loss: 0.9255 - val_accuracy: 0.8152
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8017 - accuracy: 0.8491 - val_loss: 0.9008 - val_accuracy: 0.8152
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8032 - accuracy: 0.8589 - val_loss: 0.9225 - val_accuracy: 0.8152
Epoch 44/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7982 - accuracy: 0.8528 - val_loss: 0.8895 - val_accuracy: 0.8152
Epoch 45/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7723 - accuracy: 0.8552 - val_loss: 0.9010 - val_accuracy: 0.8152
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7482 - accuracy: 0.8564 - val_loss: 0.8814 - val_accuracy: 0.8152
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7325 - accuracy: 0.8577 - val_loss: 0.9119 - val_accuracy: 0.8152
Epoch 48/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7643 - accuracy: 0.8613 - val_loss: 0.8794 - val_accuracy: 0.8152
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7215 - accuracy: 0.8540 - val_loss: 0.8267 - val_accuracy: 0.8152
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7495 - accuracy: 0.8491 - val_loss: 0.8520 - val_accuracy: 0.8152
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7988 - accuracy: 0.8406 - val_loss: 0.8410 - val_accuracy: 0.8152
Epoch 52/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7218 - accuracy: 0.8491 - val_loss: 0.8069 - val_accuracy: 0.8152
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 0.6738 - accuracy: 0.8577 - val_loss: 0.8826 - val_accuracy: 0.8261
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8285 - accuracy: 0.8625 - val_loss: 0.9889 - val_accuracy: 0.8370
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7990 - accuracy: 0.8552 - val_loss: 0.8634 - val_accuracy: 0.8261
Epoch 56/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7999 - accuracy: 0.8504 - val_loss: 0.8959 - val_accuracy: 0.8370
Epoch 57/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8087 - accuracy: 0.8528 - val_loss: 0.8818 - val_accuracy: 0.8152
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7819 - accuracy: 0.8625 - val_loss: 0.8559 - val_accuracy: 0.8152
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7639 - accuracy: 0.8564 - val_loss: 0.8271 - val_accuracy: 0.8261
Epoch 60/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7710 - accuracy: 0.8552 - val_loss: 0.8637 - val_accuracy: 0.8152
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7709 - accuracy: 0.8552 - val_loss: 0.8731 - val_accuracy: 0.8152
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7717 - accuracy: 0.8637 - val_loss: 0.8555 - val_accuracy: 0.8152
Epoch 63/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7317 - accuracy: 0.8491 - val_loss: 0.8383 - val_accuracy: 0.8152
Epoch 64/100
7/7 [==============================] - 0s 7ms/step - loss: 0.6860 - accuracy: 0.8613 - val_loss: 0.9802 - val_accuracy: 0.8261
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7808 - accuracy: 0.8613 - val_loss: 0.7915 - val_accuracy: 0.8152
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7421 - accuracy: 0.8455 - val_loss: 0.7598 - val_accuracy: 0.8370
Epoch 67/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7139 - accuracy: 0.8637 - val_loss: 0.7431 - val_accuracy: 0.8478
Epoch 68/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7412 - accuracy: 0.8479 - val_loss: 0.7824 - val_accuracy: 0.8261
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7608 - accuracy: 0.8528 - val_loss: 0.8183 - val_accuracy: 0.8152
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7581 - accuracy: 0.8564 - val_loss: 0.8132 - val_accuracy: 0.8152
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7676 - accuracy: 0.8479 - val_loss: 0.8138 - val_accuracy: 0.8261
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7743 - accuracy: 0.8528 - val_loss: 0.7797 - val_accuracy: 0.8370
Epoch 73/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7005 - accuracy: 0.8577 - val_loss: 0.8472 - val_accuracy: 0.8152
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7783 - accuracy: 0.8613 - val_loss: 0.8012 - val_accuracy: 0.8152
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7548 - accuracy: 0.8540 - val_loss: 0.8464 - val_accuracy: 0.8478
Epoch 76/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7459 - accuracy: 0.8491 - val_loss: 0.8316 - val_accuracy: 0.8261
Epoch 77/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7462 - accuracy: 0.8601 - val_loss: 0.8065 - val_accuracy: 0.8043
Epoch 78/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7866 - accuracy: 0.8467 - val_loss: 0.8290 - val_accuracy: 0.8478
Epoch 79/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7689 - accuracy: 0.8540 - val_loss: 0.8397 - val_accuracy: 0.8370
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7902 - accuracy: 0.8504 - val_loss: 0.8475 - val_accuracy: 0.8261
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7442 - accuracy: 0.8552 - val_loss: 0.8594 - val_accuracy: 0.8043
Epoch 82/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8808 - accuracy: 0.8370 - val_loss: 0.9249 - val_accuracy: 0.8152
Epoch 83/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7993 - accuracy: 0.8625 - val_loss: 0.8826 - val_accuracy: 0.8152
Epoch 84/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7811 - accuracy: 0.8577 - val_loss: 0.8579 - val_accuracy: 0.8370
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7365 - accuracy: 0.8577 - val_loss: 0.8435 - val_accuracy: 0.8587
Epoch 86/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7654 - accuracy: 0.8589 - val_loss: 0.7888 - val_accuracy: 0.8152
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7163 - accuracy: 0.8552 - val_loss: 0.8483 - val_accuracy: 0.8152
Epoch 88/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7934 - accuracy: 0.8540 - val_loss: 0.9380 - val_accuracy: 0.8152
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7847 - accuracy: 0.8564 - val_loss: 0.8657 - val_accuracy: 0.8370
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7944 - accuracy: 0.8443 - val_loss: 0.9090 - val_accuracy: 0.8370
Epoch 91/100
7/7 [==============================] - 0s 5ms/step - loss: 0.7936 - accuracy: 0.8528 - val_loss: 0.8433 - val_accuracy: 0.8261
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7666 - accuracy: 0.8491 - val_loss: 0.8552 - val_accuracy: 0.8152
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7255 - accuracy: 0.8577 - val_loss: 0.9008 - val_accuracy: 0.8152
Epoch 94/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8293 - accuracy: 0.8467 - val_loss: 0.9362 - val_accuracy: 0.8152
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7584 - accuracy: 0.8601 - val_loss: 0.8185 - val_accuracy: 0.8152
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7116 - accuracy: 0.8540 - val_loss: 0.8368 - val_accuracy: 0.8152
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7116 - accuracy: 0.8552 - val_loss: 0.8137 - val_accuracy: 0.8152
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7780 - accuracy: 0.8467 - val_loss: 0.8884 - val_accuracy: 0.8261
Epoch 99/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7608 - accuracy: 0.8564 - val_loss: 0.7850 - val_accuracy: 0.8478
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7547 - accuracy: 0.8491 - val_loss: 0.9227 - val_accuracy: 0.8152
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 4.3743 - accuracy: 0.5620 - val_loss: 1.9835 - val_accuracy: 0.8587
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 1.7693 - accuracy: 0.8528 - val_loss: 1.7431 - val_accuracy: 0.8587
Epoch 3/100
7/7 [==============================] - 0s 7ms/step - loss: 1.5768 - accuracy: 0.8163 - val_loss: 1.2064 - val_accuracy: 0.8587
Epoch 4/100
7/7 [==============================] - 0s 6ms/step - loss: 1.1235 - accuracy: 0.8443 - val_loss: 1.0787 - val_accuracy: 0.8587
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9930 - accuracy: 0.8370 - val_loss: 0.9087 - val_accuracy: 0.8587
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9040 - accuracy: 0.8467 - val_loss: 0.8579 - val_accuracy: 0.8587
Epoch 7/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8943 - accuracy: 0.8418 - val_loss: 0.8633 - val_accuracy: 0.8587
Epoch 8/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8249 - accuracy: 0.8504 - val_loss: 0.8866 - val_accuracy: 0.8587
Epoch 9/100
7/7 [==============================] - 0s 5ms/step - loss: 0.8260 - accuracy: 0.8516 - val_loss: 0.8652 - val_accuracy: 0.8587
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8797 - accuracy: 0.8431 - val_loss: 0.9054 - val_accuracy: 0.8587
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9411 - accuracy: 0.8467 - val_loss: 0.8509 - val_accuracy: 0.8587
Epoch 12/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8880 - accuracy: 0.8467 - val_loss: 0.8943 - val_accuracy: 0.8587
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8478 - accuracy: 0.8491 - val_loss: 0.8426 - val_accuracy: 0.8587
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8538 - accuracy: 0.8467 - val_loss: 0.8217 - val_accuracy: 0.8587
Epoch 15/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8430 - accuracy: 0.8455 - val_loss: 0.8151 - val_accuracy: 0.8587
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8220 - accuracy: 0.8479 - val_loss: 0.7768 - val_accuracy: 0.8587
Epoch 17/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7704 - accuracy: 0.8516 - val_loss: 0.7753 - val_accuracy: 0.8587
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8026 - accuracy: 0.8491 - val_loss: 0.8203 - val_accuracy: 0.8587
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8085 - accuracy: 0.8431 - val_loss: 0.7942 - val_accuracy: 0.8587
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8311 - accuracy: 0.8491 - val_loss: 0.7545 - val_accuracy: 0.8587
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7675 - accuracy: 0.8431 - val_loss: 0.7370 - val_accuracy: 0.8587
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8042 - accuracy: 0.8528 - val_loss: 0.7442 - val_accuracy: 0.8587
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7788 - accuracy: 0.8418 - val_loss: 0.7684 - val_accuracy: 0.8587
Epoch 24/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8116 - accuracy: 0.8370 - val_loss: 0.7611 - val_accuracy: 0.8587
Epoch 25/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8146 - accuracy: 0.8479 - val_loss: 0.7838 - val_accuracy: 0.8587
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7874 - accuracy: 0.8467 - val_loss: 0.7874 - val_accuracy: 0.8587
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7860 - accuracy: 0.8467 - val_loss: 0.7378 - val_accuracy: 0.8587
Epoch 28/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8076 - accuracy: 0.8467 - val_loss: 0.7603 - val_accuracy: 0.8587
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7967 - accuracy: 0.8418 - val_loss: 0.7439 - val_accuracy: 0.8587
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8160 - accuracy: 0.8394 - val_loss: 0.7615 - val_accuracy: 0.8587
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7732 - accuracy: 0.8431 - val_loss: 0.7399 - val_accuracy: 0.8587
Epoch 32/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7987 - accuracy: 0.8479 - val_loss: 0.7689 - val_accuracy: 0.8587
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7866 - accuracy: 0.8358 - val_loss: 0.7396 - val_accuracy: 0.8587
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7715 - accuracy: 0.8552 - val_loss: 0.7911 - val_accuracy: 0.8587
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7948 - accuracy: 0.8504 - val_loss: 0.7195 - val_accuracy: 0.8587
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7899 - accuracy: 0.8467 - val_loss: 0.7108 - val_accuracy: 0.8587
Epoch 37/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7478 - accuracy: 0.8504 - val_loss: 0.7033 - val_accuracy: 0.8587
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7812 - accuracy: 0.8406 - val_loss: 0.7093 - val_accuracy: 0.8587
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7687 - accuracy: 0.8479 - val_loss: 0.7063 - val_accuracy: 0.8587
Epoch 40/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7329 - accuracy: 0.8467 - val_loss: 0.6246 - val_accuracy: 0.8587
Epoch 41/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7366 - accuracy: 0.8516 - val_loss: 0.6628 - val_accuracy: 0.8587
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7676 - accuracy: 0.8431 - val_loss: 0.6879 - val_accuracy: 0.8587
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7738 - accuracy: 0.8479 - val_loss: 0.7734 - val_accuracy: 0.8587
Epoch 44/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8297 - accuracy: 0.8455 - val_loss: 0.6434 - val_accuracy: 0.8587
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8177 - accuracy: 0.8455 - val_loss: 0.8036 - val_accuracy: 0.8587
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8156 - accuracy: 0.8431 - val_loss: 0.7419 - val_accuracy: 0.8587
Epoch 47/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7667 - accuracy: 0.8504 - val_loss: 0.6601 - val_accuracy: 0.8587
Epoch 48/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7983 - accuracy: 0.8394 - val_loss: 0.6907 - val_accuracy: 0.8587
Epoch 49/100
7/7 [==============================] - 0s 5ms/step - loss: 0.7807 - accuracy: 0.8552 - val_loss: 0.6689 - val_accuracy: 0.8587
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7623 - accuracy: 0.8577 - val_loss: 0.6713 - val_accuracy: 0.8587
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7559 - accuracy: 0.8382 - val_loss: 0.7296 - val_accuracy: 0.8587
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7646 - accuracy: 0.8540 - val_loss: 0.6917 - val_accuracy: 0.8804
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7730 - accuracy: 0.8345 - val_loss: 0.6811 - val_accuracy: 0.8587
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7305 - accuracy: 0.8528 - val_loss: 0.6789 - val_accuracy: 0.8587
Epoch 55/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7041 - accuracy: 0.8601 - val_loss: 0.6829 - val_accuracy: 0.8587
Epoch 56/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7714 - accuracy: 0.8394 - val_loss: 0.6845 - val_accuracy: 0.8587
Epoch 57/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7603 - accuracy: 0.8504 - val_loss: 0.6578 - val_accuracy: 0.8804
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7737 - accuracy: 0.8455 - val_loss: 0.6976 - val_accuracy: 0.8478
Epoch 59/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7688 - accuracy: 0.8443 - val_loss: 0.6601 - val_accuracy: 0.8804
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7654 - accuracy: 0.8491 - val_loss: 0.6733 - val_accuracy: 0.8804
Epoch 61/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8077 - accuracy: 0.8443 - val_loss: 0.6584 - val_accuracy: 0.8587
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7669 - accuracy: 0.8479 - val_loss: 0.6346 - val_accuracy: 0.8804
Epoch 63/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7464 - accuracy: 0.8418 - val_loss: 0.7185 - val_accuracy: 0.8587
Epoch 64/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7597 - accuracy: 0.8491 - val_loss: 0.6439 - val_accuracy: 0.8696
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 0.6997 - accuracy: 0.8443 - val_loss: 0.6267 - val_accuracy: 0.8696
Epoch 66/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7919 - accuracy: 0.8309 - val_loss: 0.6377 - val_accuracy: 0.8696
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7496 - accuracy: 0.8443 - val_loss: 0.6932 - val_accuracy: 0.8804
Epoch 68/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7738 - accuracy: 0.8455 - val_loss: 0.6377 - val_accuracy: 0.8696
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7418 - accuracy: 0.8443 - val_loss: 0.6032 - val_accuracy: 0.9239
Epoch 70/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7176 - accuracy: 0.8601 - val_loss: 0.7286 - val_accuracy: 0.8587
Epoch 71/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8059 - accuracy: 0.8370 - val_loss: 0.6393 - val_accuracy: 0.8587
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7491 - accuracy: 0.8491 - val_loss: 0.6984 - val_accuracy: 0.8587
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7419 - accuracy: 0.8504 - val_loss: 0.6149 - val_accuracy: 0.9239
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 0.6943 - accuracy: 0.8564 - val_loss: 0.6148 - val_accuracy: 0.8913
Epoch 75/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7300 - accuracy: 0.8443 - val_loss: 0.6642 - val_accuracy: 0.8696
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7553 - accuracy: 0.8443 - val_loss: 0.6734 - val_accuracy: 0.8587
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7736 - accuracy: 0.8455 - val_loss: 0.6364 - val_accuracy: 0.9022
Epoch 78/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7390 - accuracy: 0.8394 - val_loss: 0.6257 - val_accuracy: 0.9457
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7099 - accuracy: 0.8650 - val_loss: 0.6628 - val_accuracy: 0.8804
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7917 - accuracy: 0.8504 - val_loss: 0.6879 - val_accuracy: 0.9022
Epoch 81/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7978 - accuracy: 0.8394 - val_loss: 0.6642 - val_accuracy: 0.9348
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8092 - accuracy: 0.8443 - val_loss: 0.7857 - val_accuracy: 0.8913
Epoch 83/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7805 - accuracy: 0.8528 - val_loss: 0.6948 - val_accuracy: 0.8696
Epoch 84/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7509 - accuracy: 0.8516 - val_loss: 0.6082 - val_accuracy: 0.8804
Epoch 85/100
7/7 [==============================] - 0s 16ms/step - loss: 0.7055 - accuracy: 0.8504 - val_loss: 0.6335 - val_accuracy: 0.9457
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7078 - accuracy: 0.8455 - val_loss: 0.7160 - val_accuracy: 0.8587
Epoch 87/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8395 - accuracy: 0.8443 - val_loss: 0.7886 - val_accuracy: 0.8370
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7944 - accuracy: 0.8528 - val_loss: 0.6847 - val_accuracy: 0.8696
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7200 - accuracy: 0.8589 - val_loss: 0.6893 - val_accuracy: 0.8804
Epoch 90/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7887 - accuracy: 0.8540 - val_loss: 0.6771 - val_accuracy: 0.8696
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7535 - accuracy: 0.8418 - val_loss: 0.6687 - val_accuracy: 0.9239
Epoch 92/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7374 - accuracy: 0.8491 - val_loss: 0.6164 - val_accuracy: 0.9022
Epoch 93/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7217 - accuracy: 0.8491 - val_loss: 0.6570 - val_accuracy: 0.9457
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7519 - accuracy: 0.8540 - val_loss: 0.6256 - val_accuracy: 0.9130
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7327 - accuracy: 0.8467 - val_loss: 0.7143 - val_accuracy: 0.9130
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7899 - accuracy: 0.8528 - val_loss: 0.6711 - val_accuracy: 0.9022
Epoch 97/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8248 - accuracy: 0.8345 - val_loss: 0.6880 - val_accuracy: 0.8587
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8077 - accuracy: 0.8394 - val_loss: 0.6533 - val_accuracy: 0.8696
Epoch 99/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7673 - accuracy: 0.8467 - val_loss: 0.6721 - val_accuracy: 0.8587
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7096 - accuracy: 0.8540 - val_loss: 0.6825 - val_accuracy: 0.8587
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 7ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 4.5564 - accuracy: 0.5650 - val_loss: 2.0382 - val_accuracy: 0.8352
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 1.8757 - accuracy: 0.8530 - val_loss: 2.0470 - val_accuracy: 0.8352
Epoch 3/100
7/7 [==============================] - 0s 7ms/step - loss: 1.6890 - accuracy: 0.8518 - val_loss: 1.2337 - val_accuracy: 0.8352
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 1.2447 - accuracy: 0.8420 - val_loss: 1.1461 - val_accuracy: 0.8352
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 1.0402 - accuracy: 0.8469 - val_loss: 0.9522 - val_accuracy: 0.8352
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9518 - accuracy: 0.8408 - val_loss: 0.8883 - val_accuracy: 0.8352
Epoch 7/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8824 - accuracy: 0.8396 - val_loss: 0.8860 - val_accuracy: 0.8352
Epoch 8/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8655 - accuracy: 0.8372 - val_loss: 0.9110 - val_accuracy: 0.8352
Epoch 9/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8585 - accuracy: 0.8530 - val_loss: 0.8428 - val_accuracy: 0.8352
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7870 - accuracy: 0.8554 - val_loss: 0.7915 - val_accuracy: 0.8352
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8119 - accuracy: 0.8445 - val_loss: 0.8190 - val_accuracy: 0.8352
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7903 - accuracy: 0.8372 - val_loss: 0.8021 - val_accuracy: 0.8352
Epoch 13/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8214 - accuracy: 0.8493 - val_loss: 0.8548 - val_accuracy: 0.8352
Epoch 14/100
7/7 [==============================] - 0s 10ms/step - loss: 0.8025 - accuracy: 0.8433 - val_loss: 0.8547 - val_accuracy: 0.8352
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8413 - accuracy: 0.8518 - val_loss: 0.8267 - val_accuracy: 0.8352
Epoch 16/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7695 - accuracy: 0.8493 - val_loss: 0.8233 - val_accuracy: 0.8352
Epoch 17/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7771 - accuracy: 0.8663 - val_loss: 0.8160 - val_accuracy: 0.8352
Epoch 18/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8222 - accuracy: 0.8275 - val_loss: 0.8075 - val_accuracy: 0.8352
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8140 - accuracy: 0.8505 - val_loss: 0.8127 - val_accuracy: 0.8352
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7429 - accuracy: 0.8505 - val_loss: 0.8002 - val_accuracy: 0.8352
Epoch 21/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7547 - accuracy: 0.8603 - val_loss: 0.7922 - val_accuracy: 0.8352
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8096 - accuracy: 0.8469 - val_loss: 0.8360 - val_accuracy: 0.8352
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7916 - accuracy: 0.8481 - val_loss: 0.8500 - val_accuracy: 0.8352
Epoch 24/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7898 - accuracy: 0.8372 - val_loss: 0.8195 - val_accuracy: 0.8352
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7805 - accuracy: 0.8591 - val_loss: 0.8460 - val_accuracy: 0.8352
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8173 - accuracy: 0.8493 - val_loss: 0.8000 - val_accuracy: 0.8352
Epoch 27/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8087 - accuracy: 0.8493 - val_loss: 0.8764 - val_accuracy: 0.8352
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7930 - accuracy: 0.8578 - val_loss: 0.9293 - val_accuracy: 0.8352
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8154 - accuracy: 0.8591 - val_loss: 0.8085 - val_accuracy: 0.8352
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7968 - accuracy: 0.8530 - val_loss: 0.7836 - val_accuracy: 0.8352
Epoch 31/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7718 - accuracy: 0.8518 - val_loss: 0.8095 - val_accuracy: 0.8352
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7697 - accuracy: 0.8542 - val_loss: 0.7804 - val_accuracy: 0.8352
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7047 - accuracy: 0.8651 - val_loss: 0.7914 - val_accuracy: 0.8352
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7285 - accuracy: 0.8566 - val_loss: 0.8717 - val_accuracy: 0.8352
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8238 - accuracy: 0.8481 - val_loss: 0.9026 - val_accuracy: 0.8352
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8097 - accuracy: 0.8433 - val_loss: 0.8974 - val_accuracy: 0.8352
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8130 - accuracy: 0.8505 - val_loss: 0.8415 - val_accuracy: 0.8352
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7886 - accuracy: 0.8505 - val_loss: 0.7772 - val_accuracy: 0.8352
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8037 - accuracy: 0.8554 - val_loss: 0.8578 - val_accuracy: 0.8352
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8231 - accuracy: 0.8505 - val_loss: 0.8113 - val_accuracy: 0.8352
Epoch 41/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8128 - accuracy: 0.8445 - val_loss: 0.8333 - val_accuracy: 0.8352
Epoch 42/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7983 - accuracy: 0.8493 - val_loss: 0.7591 - val_accuracy: 0.8462
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7896 - accuracy: 0.8493 - val_loss: 0.7468 - val_accuracy: 0.8352
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7431 - accuracy: 0.8591 - val_loss: 0.7874 - val_accuracy: 0.8571
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8702 - accuracy: 0.8518 - val_loss: 0.7577 - val_accuracy: 0.8571
Epoch 46/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8161 - accuracy: 0.8457 - val_loss: 0.7554 - val_accuracy: 0.8352
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7899 - accuracy: 0.8518 - val_loss: 0.8109 - val_accuracy: 0.8352
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7828 - accuracy: 0.8554 - val_loss: 0.7416 - val_accuracy: 0.8352
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7259 - accuracy: 0.8578 - val_loss: 0.7728 - val_accuracy: 0.8352
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8035 - accuracy: 0.8554 - val_loss: 0.7889 - val_accuracy: 0.8352
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7872 - accuracy: 0.8396 - val_loss: 0.7860 - val_accuracy: 0.8352
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7878 - accuracy: 0.8469 - val_loss: 0.7836 - val_accuracy: 0.8352
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7789 - accuracy: 0.8603 - val_loss: 0.7713 - val_accuracy: 0.8352
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7869 - accuracy: 0.8445 - val_loss: 0.8082 - val_accuracy: 0.8352
Epoch 55/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8214 - accuracy: 0.8493 - val_loss: 0.7187 - val_accuracy: 0.8352
Epoch 56/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7830 - accuracy: 0.8615 - val_loss: 0.7203 - val_accuracy: 0.8352
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7525 - accuracy: 0.8493 - val_loss: 0.7277 - val_accuracy: 0.8681
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7758 - accuracy: 0.8469 - val_loss: 0.7215 - val_accuracy: 0.8352
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7842 - accuracy: 0.8578 - val_loss: 0.6984 - val_accuracy: 0.8352
Epoch 60/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7394 - accuracy: 0.8578 - val_loss: 0.7003 - val_accuracy: 0.8352
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7403 - accuracy: 0.8469 - val_loss: 0.7009 - val_accuracy: 0.8352
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7594 - accuracy: 0.8591 - val_loss: 0.7822 - val_accuracy: 0.8352
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8514 - accuracy: 0.8445 - val_loss: 0.8784 - val_accuracy: 0.8462
Epoch 64/100
7/7 [==============================] - 0s 5ms/step - loss: 0.8301 - accuracy: 0.8469 - val_loss: 0.7348 - val_accuracy: 0.8352
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7625 - accuracy: 0.8530 - val_loss: 0.6878 - val_accuracy: 0.8352
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7581 - accuracy: 0.8554 - val_loss: 0.7874 - val_accuracy: 0.8681
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8407 - accuracy: 0.8554 - val_loss: 0.6988 - val_accuracy: 0.8681
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8112 - accuracy: 0.8578 - val_loss: 0.7096 - val_accuracy: 0.8352
Epoch 69/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8747 - accuracy: 0.8420 - val_loss: 0.7154 - val_accuracy: 0.8462
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7632 - accuracy: 0.8651 - val_loss: 0.7527 - val_accuracy: 0.8681
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8388 - accuracy: 0.8554 - val_loss: 0.7800 - val_accuracy: 0.8352
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8104 - accuracy: 0.8505 - val_loss: 0.7230 - val_accuracy: 0.8352
Epoch 73/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7716 - accuracy: 0.8603 - val_loss: 0.7140 - val_accuracy: 0.8352
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8139 - accuracy: 0.8408 - val_loss: 0.7146 - val_accuracy: 0.8352
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8030 - accuracy: 0.8384 - val_loss: 0.7706 - val_accuracy: 0.8791
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7927 - accuracy: 0.8530 - val_loss: 0.7395 - val_accuracy: 0.8352
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8210 - accuracy: 0.8469 - val_loss: 0.7781 - val_accuracy: 0.8352
Epoch 78/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7505 - accuracy: 0.8542 - val_loss: 0.7741 - val_accuracy: 0.8462
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7994 - accuracy: 0.8505 - val_loss: 0.7426 - val_accuracy: 0.8462
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7760 - accuracy: 0.8469 - val_loss: 0.6947 - val_accuracy: 0.8571
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8017 - accuracy: 0.8530 - val_loss: 0.7667 - val_accuracy: 0.8352
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7976 - accuracy: 0.8554 - val_loss: 0.7436 - val_accuracy: 0.8352
Epoch 83/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7652 - accuracy: 0.8554 - val_loss: 0.7503 - val_accuracy: 0.8352
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7812 - accuracy: 0.8433 - val_loss: 0.7626 - val_accuracy: 0.8352
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7738 - accuracy: 0.8530 - val_loss: 0.6882 - val_accuracy: 0.8352
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7189 - accuracy: 0.8554 - val_loss: 0.7035 - val_accuracy: 0.8242
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7374 - accuracy: 0.8530 - val_loss: 0.7115 - val_accuracy: 0.8352
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7557 - accuracy: 0.8542 - val_loss: 0.7213 - val_accuracy: 0.8352
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7589 - accuracy: 0.8457 - val_loss: 0.7403 - val_accuracy: 0.8681
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7850 - accuracy: 0.8433 - val_loss: 0.7805 - val_accuracy: 0.8352
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7588 - accuracy: 0.8578 - val_loss: 0.7050 - val_accuracy: 0.8352
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7281 - accuracy: 0.8530 - val_loss: 0.6933 - val_accuracy: 0.8352
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7416 - accuracy: 0.8469 - val_loss: 0.6502 - val_accuracy: 0.8462
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7599 - accuracy: 0.8481 - val_loss: 0.7135 - val_accuracy: 0.8462
Epoch 95/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7745 - accuracy: 0.8578 - val_loss: 0.7611 - val_accuracy: 0.8462
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7418 - accuracy: 0.8469 - val_loss: 0.7272 - val_accuracy: 0.8462
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7318 - accuracy: 0.8530 - val_loss: 0.6555 - val_accuracy: 0.8352
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7254 - accuracy: 0.8493 - val_loss: 0.7534 - val_accuracy: 0.9121
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7986 - accuracy: 0.8505 - val_loss: 0.6716 - val_accuracy: 0.8901
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7422 - accuracy: 0.8578 - val_loss: 0.7401 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 45ms/step - loss: 4.1517 - accuracy: 0.5395 - val_loss: 1.8072 - val_accuracy: 0.8681
Epoch 2/100
7/7 [==============================] - 0s 7ms/step - loss: 1.7856 - accuracy: 0.8420 - val_loss: 1.8958 - val_accuracy: 0.8681
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 1.5763 - accuracy: 0.8420 - val_loss: 1.1787 - val_accuracy: 0.8681
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 1.2211 - accuracy: 0.8275 - val_loss: 1.1990 - val_accuracy: 0.8681
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 1.0610 - accuracy: 0.8481 - val_loss: 0.9817 - val_accuracy: 0.8681
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9175 - accuracy: 0.8384 - val_loss: 0.9346 - val_accuracy: 0.8681
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8211 - accuracy: 0.8615 - val_loss: 0.8356 - val_accuracy: 0.8681
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7886 - accuracy: 0.8591 - val_loss: 0.8210 - val_accuracy: 0.8681
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8008 - accuracy: 0.8518 - val_loss: 0.8325 - val_accuracy: 0.8681
Epoch 10/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8193 - accuracy: 0.8505 - val_loss: 0.8571 - val_accuracy: 0.8681
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8270 - accuracy: 0.8396 - val_loss: 0.8618 - val_accuracy: 0.8681
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8695 - accuracy: 0.8457 - val_loss: 0.8675 - val_accuracy: 0.8681
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7768 - accuracy: 0.8493 - val_loss: 0.8369 - val_accuracy: 0.8681
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7711 - accuracy: 0.8566 - val_loss: 0.8433 - val_accuracy: 0.8681
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8236 - accuracy: 0.8518 - val_loss: 0.8082 - val_accuracy: 0.8681
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8057 - accuracy: 0.8530 - val_loss: 0.8295 - val_accuracy: 0.8681
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7633 - accuracy: 0.8615 - val_loss: 0.8227 - val_accuracy: 0.8681
Epoch 18/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7961 - accuracy: 0.8445 - val_loss: 0.8304 - val_accuracy: 0.8681
Epoch 19/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8024 - accuracy: 0.8542 - val_loss: 0.8812 - val_accuracy: 0.8681
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8268 - accuracy: 0.8457 - val_loss: 0.7856 - val_accuracy: 0.8681
Epoch 21/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7710 - accuracy: 0.8469 - val_loss: 0.7993 - val_accuracy: 0.8681
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7847 - accuracy: 0.8457 - val_loss: 0.8454 - val_accuracy: 0.8681
Epoch 23/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7497 - accuracy: 0.8469 - val_loss: 0.8025 - val_accuracy: 0.8681
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7901 - accuracy: 0.8493 - val_loss: 0.8644 - val_accuracy: 0.8681
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8154 - accuracy: 0.8420 - val_loss: 0.8509 - val_accuracy: 0.8681
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7707 - accuracy: 0.8554 - val_loss: 0.7749 - val_accuracy: 0.8681
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7935 - accuracy: 0.8408 - val_loss: 0.7931 - val_accuracy: 0.8681
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7839 - accuracy: 0.8420 - val_loss: 0.8206 - val_accuracy: 0.8681
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7750 - accuracy: 0.8530 - val_loss: 0.7928 - val_accuracy: 0.8681
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7925 - accuracy: 0.8457 - val_loss: 0.7895 - val_accuracy: 0.8681
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7694 - accuracy: 0.8566 - val_loss: 0.7974 - val_accuracy: 0.8681
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7695 - accuracy: 0.8518 - val_loss: 0.7381 - val_accuracy: 0.8681
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7398 - accuracy: 0.8493 - val_loss: 0.7871 - val_accuracy: 0.8681
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8397 - accuracy: 0.8457 - val_loss: 0.8177 - val_accuracy: 0.8681
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7508 - accuracy: 0.8566 - val_loss: 0.7840 - val_accuracy: 0.8681
Epoch 36/100
7/7 [==============================] - 0s 7ms/step - loss: 0.9030 - accuracy: 0.8372 - val_loss: 0.8472 - val_accuracy: 0.8681
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7695 - accuracy: 0.8396 - val_loss: 0.7257 - val_accuracy: 0.8681
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7655 - accuracy: 0.8554 - val_loss: 0.7739 - val_accuracy: 0.8681
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7800 - accuracy: 0.8433 - val_loss: 0.7919 - val_accuracy: 0.8681
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7875 - accuracy: 0.8554 - val_loss: 0.7746 - val_accuracy: 0.8681
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8111 - accuracy: 0.8408 - val_loss: 0.7916 - val_accuracy: 0.8681
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7887 - accuracy: 0.8457 - val_loss: 0.7989 - val_accuracy: 0.8681
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7879 - accuracy: 0.8493 - val_loss: 0.7927 - val_accuracy: 0.8681
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7700 - accuracy: 0.8518 - val_loss: 0.7666 - val_accuracy: 0.8681
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7700 - accuracy: 0.8408 - val_loss: 0.7656 - val_accuracy: 0.8681
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7691 - accuracy: 0.8457 - val_loss: 0.7862 - val_accuracy: 0.8681
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7948 - accuracy: 0.8323 - val_loss: 0.7571 - val_accuracy: 0.8681
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7585 - accuracy: 0.8518 - val_loss: 0.7479 - val_accuracy: 0.8681
Epoch 49/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7567 - accuracy: 0.8530 - val_loss: 0.7917 - val_accuracy: 0.8681
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7938 - accuracy: 0.8445 - val_loss: 0.7909 - val_accuracy: 0.8681
Epoch 51/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8263 - accuracy: 0.8542 - val_loss: 0.9311 - val_accuracy: 0.8681
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 0.9136 - accuracy: 0.8481 - val_loss: 0.8465 - val_accuracy: 0.8571
Epoch 53/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8541 - accuracy: 0.8469 - val_loss: 0.7987 - val_accuracy: 0.8681
Epoch 54/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7802 - accuracy: 0.8505 - val_loss: 0.7771 - val_accuracy: 0.8681
Epoch 55/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7488 - accuracy: 0.8457 - val_loss: 0.7802 - val_accuracy: 0.8681
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7428 - accuracy: 0.8469 - val_loss: 0.7438 - val_accuracy: 0.8791
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7272 - accuracy: 0.8518 - val_loss: 0.7057 - val_accuracy: 0.8681
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7209 - accuracy: 0.8518 - val_loss: 0.6877 - val_accuracy: 0.8681
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7401 - accuracy: 0.8542 - val_loss: 0.7366 - val_accuracy: 0.8681
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7341 - accuracy: 0.8445 - val_loss: 0.7692 - val_accuracy: 0.8681
Epoch 61/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7902 - accuracy: 0.8505 - val_loss: 0.7373 - val_accuracy: 0.8571
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8037 - accuracy: 0.8493 - val_loss: 0.8284 - val_accuracy: 0.8791
Epoch 63/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7938 - accuracy: 0.8663 - val_loss: 0.7707 - val_accuracy: 0.8571
Epoch 64/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7822 - accuracy: 0.8457 - val_loss: 0.8289 - val_accuracy: 0.8462
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8032 - accuracy: 0.8469 - val_loss: 0.7151 - val_accuracy: 0.8681
Epoch 66/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7901 - accuracy: 0.8384 - val_loss: 0.8056 - val_accuracy: 0.8571
Epoch 67/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7962 - accuracy: 0.8481 - val_loss: 0.7580 - val_accuracy: 0.8681
Epoch 68/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7269 - accuracy: 0.8578 - val_loss: 0.7361 - val_accuracy: 0.8681
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7292 - accuracy: 0.8518 - val_loss: 0.7071 - val_accuracy: 0.8571
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7234 - accuracy: 0.8457 - val_loss: 0.7464 - val_accuracy: 0.8571
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7652 - accuracy: 0.8578 - val_loss: 0.8627 - val_accuracy: 0.7912
Epoch 72/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7641 - accuracy: 0.8420 - val_loss: 0.6951 - val_accuracy: 0.8462
Epoch 73/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7556 - accuracy: 0.8469 - val_loss: 0.6958 - val_accuracy: 0.8571
Epoch 74/100
7/7 [==============================] - 0s 17ms/step - loss: 0.7120 - accuracy: 0.8469 - val_loss: 0.7408 - val_accuracy: 0.8352
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7342 - accuracy: 0.8627 - val_loss: 0.7091 - val_accuracy: 0.8791
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7467 - accuracy: 0.8554 - val_loss: 0.7572 - val_accuracy: 0.8352
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7657 - accuracy: 0.8518 - val_loss: 0.7631 - val_accuracy: 0.8681
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7708 - accuracy: 0.8518 - val_loss: 0.7730 - val_accuracy: 0.8571
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7806 - accuracy: 0.8505 - val_loss: 0.7519 - val_accuracy: 0.8571
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8170 - accuracy: 0.8457 - val_loss: 0.8256 - val_accuracy: 0.8462
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7587 - accuracy: 0.8505 - val_loss: 0.7423 - val_accuracy: 0.8352
Epoch 82/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7476 - accuracy: 0.8554 - val_loss: 0.7907 - val_accuracy: 0.8681
Epoch 83/100
7/7 [==============================] - 0s 12ms/step - loss: 0.7651 - accuracy: 0.8372 - val_loss: 0.7324 - val_accuracy: 0.8681
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7270 - accuracy: 0.8530 - val_loss: 0.6768 - val_accuracy: 0.8791
Epoch 85/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7205 - accuracy: 0.8554 - val_loss: 0.7049 - val_accuracy: 0.8681
Epoch 86/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7352 - accuracy: 0.8542 - val_loss: 0.7419 - val_accuracy: 0.8462
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7118 - accuracy: 0.8554 - val_loss: 0.7061 - val_accuracy: 0.8352
Epoch 88/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7315 - accuracy: 0.8542 - val_loss: 0.8294 - val_accuracy: 0.8462
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8349 - accuracy: 0.8554 - val_loss: 0.8421 - val_accuracy: 0.8242
Epoch 90/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8065 - accuracy: 0.8578 - val_loss: 0.7133 - val_accuracy: 0.8681
Epoch 91/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7721 - accuracy: 0.8493 - val_loss: 0.7313 - val_accuracy: 0.8571
Epoch 92/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7559 - accuracy: 0.8566 - val_loss: 0.7647 - val_accuracy: 0.8681
Epoch 93/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7799 - accuracy: 0.8578 - val_loss: 0.7749 - val_accuracy: 0.8681
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7523 - accuracy: 0.8505 - val_loss: 0.7764 - val_accuracy: 0.8462
Epoch 95/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7697 - accuracy: 0.8372 - val_loss: 0.7300 - val_accuracy: 0.8681
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7251 - accuracy: 0.8615 - val_loss: 0.8105 - val_accuracy: 0.8791
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7495 - accuracy: 0.8603 - val_loss: 0.7264 - val_accuracy: 0.8791
Epoch 98/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7363 - accuracy: 0.8396 - val_loss: 0.7849 - val_accuracy: 0.8901
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7176 - accuracy: 0.8578 - val_loss: 0.7399 - val_accuracy: 0.8681
Epoch 100/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7065 - accuracy: 0.8578 - val_loss: 0.7161 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 4.5662 - accuracy: 0.5225 - val_loss: 2.1069 - val_accuracy: 0.9011
Epoch 2/100
7/7 [==============================] - 0s 7ms/step - loss: 1.8503 - accuracy: 0.8372 - val_loss: 1.9396 - val_accuracy: 0.9011
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 1.7193 - accuracy: 0.8433 - val_loss: 1.1432 - val_accuracy: 0.9011
Epoch 4/100
7/7 [==============================] - 0s 7ms/step - loss: 1.1966 - accuracy: 0.8348 - val_loss: 0.9824 - val_accuracy: 0.9011
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9786 - accuracy: 0.8433 - val_loss: 0.8298 - val_accuracy: 0.9011
Epoch 6/100
7/7 [==============================] - 0s 7ms/step - loss: 0.9372 - accuracy: 0.8420 - val_loss: 0.8768 - val_accuracy: 0.9011
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9519 - accuracy: 0.8481 - val_loss: 0.8157 - val_accuracy: 0.9011
Epoch 8/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8207 - accuracy: 0.8445 - val_loss: 0.7568 - val_accuracy: 0.9011
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8359 - accuracy: 0.8433 - val_loss: 0.7604 - val_accuracy: 0.9011
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8308 - accuracy: 0.8481 - val_loss: 0.7559 - val_accuracy: 0.9011
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8171 - accuracy: 0.8433 - val_loss: 0.7604 - val_accuracy: 0.9011
Epoch 12/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7817 - accuracy: 0.8360 - val_loss: 0.7638 - val_accuracy: 0.9011
Epoch 13/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8170 - accuracy: 0.8566 - val_loss: 0.7211 - val_accuracy: 0.9011
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8143 - accuracy: 0.8323 - val_loss: 0.7429 - val_accuracy: 0.9011
Epoch 15/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7672 - accuracy: 0.8566 - val_loss: 0.7431 - val_accuracy: 0.9011
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8348 - accuracy: 0.8445 - val_loss: 0.7240 - val_accuracy: 0.9011
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8223 - accuracy: 0.8469 - val_loss: 0.7407 - val_accuracy: 0.9011
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7890 - accuracy: 0.8396 - val_loss: 0.7416 - val_accuracy: 0.9011
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7584 - accuracy: 0.8530 - val_loss: 0.7284 - val_accuracy: 0.9011
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7258 - accuracy: 0.8420 - val_loss: 0.6946 - val_accuracy: 0.9011
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7975 - accuracy: 0.8360 - val_loss: 0.7389 - val_accuracy: 0.9011
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8044 - accuracy: 0.8335 - val_loss: 0.7187 - val_accuracy: 0.9011
Epoch 23/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7902 - accuracy: 0.8457 - val_loss: 0.7479 - val_accuracy: 0.9011
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8305 - accuracy: 0.8433 - val_loss: 0.8006 - val_accuracy: 0.9011
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8634 - accuracy: 0.8360 - val_loss: 0.7526 - val_accuracy: 0.9011
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8280 - accuracy: 0.8457 - val_loss: 0.7342 - val_accuracy: 0.9011
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8054 - accuracy: 0.8518 - val_loss: 0.7542 - val_accuracy: 0.9011
Epoch 28/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7647 - accuracy: 0.8408 - val_loss: 0.7415 - val_accuracy: 0.9011
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8493 - accuracy: 0.8299 - val_loss: 0.7932 - val_accuracy: 0.9011
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8220 - accuracy: 0.8493 - val_loss: 0.7377 - val_accuracy: 0.8901
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8702 - accuracy: 0.8275 - val_loss: 0.7839 - val_accuracy: 0.9011
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7979 - accuracy: 0.8457 - val_loss: 0.6957 - val_accuracy: 0.9011
Epoch 33/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7467 - accuracy: 0.8615 - val_loss: 0.6797 - val_accuracy: 0.9011
Epoch 34/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8440 - accuracy: 0.8335 - val_loss: 0.7933 - val_accuracy: 0.9011
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8314 - accuracy: 0.8445 - val_loss: 0.7330 - val_accuracy: 0.9011
Epoch 36/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7983 - accuracy: 0.8396 - val_loss: 0.7605 - val_accuracy: 0.9011
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7967 - accuracy: 0.8542 - val_loss: 0.6607 - val_accuracy: 0.9011
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7585 - accuracy: 0.8591 - val_loss: 0.6581 - val_accuracy: 0.9011
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7144 - accuracy: 0.8457 - val_loss: 0.7211 - val_accuracy: 0.8901
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8013 - accuracy: 0.8348 - val_loss: 0.7034 - val_accuracy: 0.9011
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7750 - accuracy: 0.8408 - val_loss: 0.7062 - val_accuracy: 0.9011
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7592 - accuracy: 0.8518 - val_loss: 0.6829 - val_accuracy: 0.9011
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7466 - accuracy: 0.8433 - val_loss: 0.6922 - val_accuracy: 0.9011
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7941 - accuracy: 0.8457 - val_loss: 0.7455 - val_accuracy: 0.9011
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7698 - accuracy: 0.8518 - val_loss: 0.6611 - val_accuracy: 0.9011
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7602 - accuracy: 0.8505 - val_loss: 0.6764 - val_accuracy: 0.9011
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7453 - accuracy: 0.8505 - val_loss: 0.6843 - val_accuracy: 0.9011
Epoch 48/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7657 - accuracy: 0.8481 - val_loss: 0.7222 - val_accuracy: 0.9011
Epoch 49/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7933 - accuracy: 0.8408 - val_loss: 0.6991 - val_accuracy: 0.9011
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7833 - accuracy: 0.8457 - val_loss: 0.6680 - val_accuracy: 0.9011
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7695 - accuracy: 0.8433 - val_loss: 0.6812 - val_accuracy: 0.8901
Epoch 52/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8489 - accuracy: 0.8408 - val_loss: 0.7060 - val_accuracy: 0.9011
Epoch 53/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7767 - accuracy: 0.8481 - val_loss: 0.7023 - val_accuracy: 0.9011
Epoch 54/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8590 - accuracy: 0.8578 - val_loss: 0.8562 - val_accuracy: 0.8901
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8510 - accuracy: 0.8420 - val_loss: 0.7221 - val_accuracy: 0.9011
Epoch 56/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8138 - accuracy: 0.8481 - val_loss: 0.7472 - val_accuracy: 0.9011
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7977 - accuracy: 0.8566 - val_loss: 0.7732 - val_accuracy: 0.8791
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8203 - accuracy: 0.8360 - val_loss: 0.7575 - val_accuracy: 0.8791
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8110 - accuracy: 0.8433 - val_loss: 0.7297 - val_accuracy: 0.8901
Epoch 60/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8004 - accuracy: 0.8469 - val_loss: 0.7574 - val_accuracy: 0.8901
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8004 - accuracy: 0.8433 - val_loss: 0.7234 - val_accuracy: 0.9121
Epoch 62/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7526 - accuracy: 0.8433 - val_loss: 0.6794 - val_accuracy: 0.9011
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7846 - accuracy: 0.8396 - val_loss: 0.7741 - val_accuracy: 0.8901
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7770 - accuracy: 0.8481 - val_loss: 0.6384 - val_accuracy: 0.9011
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7153 - accuracy: 0.8518 - val_loss: 0.6673 - val_accuracy: 0.9121
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7475 - accuracy: 0.8505 - val_loss: 0.6781 - val_accuracy: 0.8791
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7472 - accuracy: 0.8396 - val_loss: 0.7005 - val_accuracy: 0.9011
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7575 - accuracy: 0.8530 - val_loss: 0.6910 - val_accuracy: 0.9121
Epoch 69/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7482 - accuracy: 0.8433 - val_loss: 0.7351 - val_accuracy: 0.8791
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8001 - accuracy: 0.8396 - val_loss: 0.7477 - val_accuracy: 0.8681
Epoch 71/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8221 - accuracy: 0.8408 - val_loss: 0.6573 - val_accuracy: 0.9011
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7535 - accuracy: 0.8408 - val_loss: 0.6588 - val_accuracy: 0.9011
Epoch 73/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7641 - accuracy: 0.8433 - val_loss: 0.6625 - val_accuracy: 0.9011
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7435 - accuracy: 0.8493 - val_loss: 0.6524 - val_accuracy: 0.9011
Epoch 75/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7490 - accuracy: 0.8384 - val_loss: 0.7423 - val_accuracy: 0.9011
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7697 - accuracy: 0.8457 - val_loss: 0.7285 - val_accuracy: 0.8791
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7915 - accuracy: 0.8505 - val_loss: 0.6526 - val_accuracy: 0.9011
Epoch 78/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7264 - accuracy: 0.8493 - val_loss: 0.7001 - val_accuracy: 0.9121
Epoch 79/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7362 - accuracy: 0.8493 - val_loss: 0.6557 - val_accuracy: 0.9011
Epoch 80/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7880 - accuracy: 0.8433 - val_loss: 0.6732 - val_accuracy: 0.8791
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8036 - accuracy: 0.8469 - val_loss: 0.6812 - val_accuracy: 0.9231
Epoch 82/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7766 - accuracy: 0.8603 - val_loss: 0.6531 - val_accuracy: 0.9011
Epoch 83/100
7/7 [==============================] - 0s 5ms/step - loss: 0.7485 - accuracy: 0.8445 - val_loss: 0.7353 - val_accuracy: 0.9011
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7761 - accuracy: 0.8481 - val_loss: 0.6669 - val_accuracy: 0.9121
Epoch 85/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7593 - accuracy: 0.8578 - val_loss: 0.6896 - val_accuracy: 0.9121
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7875 - accuracy: 0.8481 - val_loss: 0.6843 - val_accuracy: 0.9011
Epoch 87/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7716 - accuracy: 0.8445 - val_loss: 0.7085 - val_accuracy: 0.9011
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7361 - accuracy: 0.8578 - val_loss: 0.6979 - val_accuracy: 0.9011
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7203 - accuracy: 0.8445 - val_loss: 0.6267 - val_accuracy: 0.9011
Epoch 90/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7025 - accuracy: 0.8481 - val_loss: 0.6423 - val_accuracy: 0.9121
Epoch 91/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7207 - accuracy: 0.8396 - val_loss: 0.6675 - val_accuracy: 0.8791
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7262 - accuracy: 0.8530 - val_loss: 0.6705 - val_accuracy: 0.9011
Epoch 93/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7169 - accuracy: 0.8493 - val_loss: 0.6270 - val_accuracy: 0.9011
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7206 - accuracy: 0.8481 - val_loss: 0.6492 - val_accuracy: 0.8901
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7186 - accuracy: 0.8396 - val_loss: 0.6571 - val_accuracy: 0.8901
Epoch 96/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7091 - accuracy: 0.8469 - val_loss: 0.6860 - val_accuracy: 0.8791
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7629 - accuracy: 0.8384 - val_loss: 0.6594 - val_accuracy: 0.8791
Epoch 98/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7203 - accuracy: 0.8457 - val_loss: 0.7050 - val_accuracy: 0.9011
Epoch 99/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7699 - accuracy: 0.8445 - val_loss: 0.6852 - val_accuracy: 0.9011
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7430 - accuracy: 0.8493 - val_loss: 0.7209 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 40ms/step - loss: 4.3002 - accuracy: 0.5917 - val_loss: 1.9738 - val_accuracy: 0.8681
Epoch 2/100
7/7 [==============================] - 0s 10ms/step - loss: 1.7648 - accuracy: 0.8433 - val_loss: 1.9695 - val_accuracy: 0.8681
Epoch 3/100
7/7 [==============================] - 0s 7ms/step - loss: 1.6371 - accuracy: 0.8457 - val_loss: 1.2182 - val_accuracy: 0.8681
Epoch 4/100
7/7 [==============================] - 0s 6ms/step - loss: 1.1201 - accuracy: 0.8505 - val_loss: 1.0995 - val_accuracy: 0.8681
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 1.0371 - accuracy: 0.8433 - val_loss: 1.0017 - val_accuracy: 0.8681
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9715 - accuracy: 0.8518 - val_loss: 0.9158 - val_accuracy: 0.8681
Epoch 7/100
7/7 [==============================] - 0s 6ms/step - loss: 0.9100 - accuracy: 0.8542 - val_loss: 1.0223 - val_accuracy: 0.8681
Epoch 8/100
7/7 [==============================] - 0s 5ms/step - loss: 0.9426 - accuracy: 0.8481 - val_loss: 0.9444 - val_accuracy: 0.8681
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8800 - accuracy: 0.8408 - val_loss: 0.9440 - val_accuracy: 0.8681
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8951 - accuracy: 0.8457 - val_loss: 0.8823 - val_accuracy: 0.8681
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8432 - accuracy: 0.8505 - val_loss: 0.9125 - val_accuracy: 0.8681
Epoch 12/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8346 - accuracy: 0.8761 - val_loss: 0.8773 - val_accuracy: 0.8681
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8037 - accuracy: 0.8505 - val_loss: 0.8282 - val_accuracy: 0.8681
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8468 - accuracy: 0.8493 - val_loss: 0.9109 - val_accuracy: 0.8681
Epoch 15/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8681 - accuracy: 0.8469 - val_loss: 0.9154 - val_accuracy: 0.8681
Epoch 16/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8390 - accuracy: 0.8603 - val_loss: 0.8615 - val_accuracy: 0.8681
Epoch 17/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7779 - accuracy: 0.8578 - val_loss: 0.8120 - val_accuracy: 0.8681
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8252 - accuracy: 0.8639 - val_loss: 0.9441 - val_accuracy: 0.8681
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8427 - accuracy: 0.8493 - val_loss: 0.8501 - val_accuracy: 0.8681
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8427 - accuracy: 0.8591 - val_loss: 0.8732 - val_accuracy: 0.8681
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8634 - accuracy: 0.8457 - val_loss: 0.8728 - val_accuracy: 0.8681
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7883 - accuracy: 0.8603 - val_loss: 0.7803 - val_accuracy: 0.8681
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7963 - accuracy: 0.8591 - val_loss: 0.8452 - val_accuracy: 0.8681
Epoch 24/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7832 - accuracy: 0.8542 - val_loss: 0.8543 - val_accuracy: 0.8681
Epoch 25/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7865 - accuracy: 0.8505 - val_loss: 0.8942 - val_accuracy: 0.8681
Epoch 26/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8175 - accuracy: 0.8542 - val_loss: 0.8094 - val_accuracy: 0.8681
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7777 - accuracy: 0.8603 - val_loss: 0.7875 - val_accuracy: 0.8681
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7722 - accuracy: 0.8408 - val_loss: 0.7230 - val_accuracy: 0.8681
Epoch 29/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7745 - accuracy: 0.8627 - val_loss: 0.7957 - val_accuracy: 0.8681
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7707 - accuracy: 0.8469 - val_loss: 0.8019 - val_accuracy: 0.8681
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7293 - accuracy: 0.8542 - val_loss: 0.7706 - val_accuracy: 0.8681
Epoch 32/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7684 - accuracy: 0.8554 - val_loss: 0.8166 - val_accuracy: 0.8681
Epoch 33/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8471 - accuracy: 0.8420 - val_loss: 0.8018 - val_accuracy: 0.8681
Epoch 34/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7662 - accuracy: 0.8615 - val_loss: 0.8554 - val_accuracy: 0.8681
Epoch 35/100
7/7 [==============================] - 0s 7ms/step - loss: 0.9046 - accuracy: 0.8323 - val_loss: 0.8500 - val_accuracy: 0.8571
Epoch 36/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8365 - accuracy: 0.8530 - val_loss: 0.8561 - val_accuracy: 0.8681
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7899 - accuracy: 0.8457 - val_loss: 0.8051 - val_accuracy: 0.8681
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7821 - accuracy: 0.8591 - val_loss: 0.8759 - val_accuracy: 0.8681
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9201 - accuracy: 0.8396 - val_loss: 0.8428 - val_accuracy: 0.8681
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8082 - accuracy: 0.8457 - val_loss: 0.8112 - val_accuracy: 0.8681
Epoch 41/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7950 - accuracy: 0.8554 - val_loss: 0.8524 - val_accuracy: 0.8681
Epoch 42/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7855 - accuracy: 0.8542 - val_loss: 0.7319 - val_accuracy: 0.8681
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7511 - accuracy: 0.8566 - val_loss: 0.8633 - val_accuracy: 0.8681
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7975 - accuracy: 0.8518 - val_loss: 0.7238 - val_accuracy: 0.8681
Epoch 45/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7359 - accuracy: 0.8542 - val_loss: 0.7423 - val_accuracy: 0.8681
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7303 - accuracy: 0.8566 - val_loss: 0.7876 - val_accuracy: 0.8462
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8197 - accuracy: 0.8323 - val_loss: 0.8393 - val_accuracy: 0.8681
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7629 - accuracy: 0.8542 - val_loss: 0.7769 - val_accuracy: 0.8681
Epoch 49/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7635 - accuracy: 0.8518 - val_loss: 0.8084 - val_accuracy: 0.8681
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7398 - accuracy: 0.8530 - val_loss: 0.7485 - val_accuracy: 0.8681
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7416 - accuracy: 0.8542 - val_loss: 0.7261 - val_accuracy: 0.8681
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7385 - accuracy: 0.8651 - val_loss: 0.7425 - val_accuracy: 0.8681
Epoch 53/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7347 - accuracy: 0.8530 - val_loss: 0.7107 - val_accuracy: 0.8681
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7462 - accuracy: 0.8433 - val_loss: 0.8755 - val_accuracy: 0.8791
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7814 - accuracy: 0.8505 - val_loss: 0.7737 - val_accuracy: 0.8681
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7491 - accuracy: 0.8651 - val_loss: 0.8111 - val_accuracy: 0.8571
Epoch 57/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7745 - accuracy: 0.8469 - val_loss: 0.8270 - val_accuracy: 0.8571
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8035 - accuracy: 0.8554 - val_loss: 0.7848 - val_accuracy: 0.8681
Epoch 59/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7928 - accuracy: 0.8542 - val_loss: 0.8508 - val_accuracy: 0.8571
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8685 - accuracy: 0.8384 - val_loss: 0.7632 - val_accuracy: 0.8681
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7465 - accuracy: 0.8566 - val_loss: 0.7391 - val_accuracy: 0.8681
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 0.6971 - accuracy: 0.8651 - val_loss: 0.7456 - val_accuracy: 0.8681
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7343 - accuracy: 0.8493 - val_loss: 0.7688 - val_accuracy: 0.8462
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7784 - accuracy: 0.8335 - val_loss: 0.7734 - val_accuracy: 0.8681
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7116 - accuracy: 0.8615 - val_loss: 0.7742 - val_accuracy: 0.8462
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7116 - accuracy: 0.8542 - val_loss: 0.7242 - val_accuracy: 0.8681
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7573 - accuracy: 0.8554 - val_loss: 0.8127 - val_accuracy: 0.7912
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7125 - accuracy: 0.8530 - val_loss: 0.7906 - val_accuracy: 0.8571
Epoch 69/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7625 - accuracy: 0.8469 - val_loss: 0.7095 - val_accuracy: 0.8681
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7121 - accuracy: 0.8591 - val_loss: 0.7631 - val_accuracy: 0.8462
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7804 - accuracy: 0.8615 - val_loss: 0.8161 - val_accuracy: 0.8571
Epoch 72/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7824 - accuracy: 0.8530 - val_loss: 0.8825 - val_accuracy: 0.7912
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8072 - accuracy: 0.8335 - val_loss: 0.8082 - val_accuracy: 0.8681
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7956 - accuracy: 0.8396 - val_loss: 0.8196 - val_accuracy: 0.8462
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7373 - accuracy: 0.8481 - val_loss: 0.7278 - val_accuracy: 0.8571
Epoch 76/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7331 - accuracy: 0.8457 - val_loss: 0.8410 - val_accuracy: 0.8352
Epoch 77/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7548 - accuracy: 0.8615 - val_loss: 0.7669 - val_accuracy: 0.8681
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7322 - accuracy: 0.8578 - val_loss: 0.7903 - val_accuracy: 0.8352
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7088 - accuracy: 0.8578 - val_loss: 0.8019 - val_accuracy: 0.8571
Epoch 80/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8173 - accuracy: 0.8493 - val_loss: 0.7526 - val_accuracy: 0.8571
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7485 - accuracy: 0.8433 - val_loss: 0.8306 - val_accuracy: 0.8571
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8221 - accuracy: 0.8530 - val_loss: 0.8046 - val_accuracy: 0.8352
Epoch 83/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7589 - accuracy: 0.8469 - val_loss: 0.8560 - val_accuracy: 0.7912
Epoch 84/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7708 - accuracy: 0.8615 - val_loss: 0.7844 - val_accuracy: 0.8462
Epoch 85/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7926 - accuracy: 0.8360 - val_loss: 0.8925 - val_accuracy: 0.8132
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7934 - accuracy: 0.8433 - val_loss: 0.7579 - val_accuracy: 0.8681
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7401 - accuracy: 0.8615 - val_loss: 0.7927 - val_accuracy: 0.8352
Epoch 88/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7707 - accuracy: 0.8445 - val_loss: 0.7602 - val_accuracy: 0.8571
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7394 - accuracy: 0.8469 - val_loss: 0.7864 - val_accuracy: 0.8462
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7821 - accuracy: 0.8578 - val_loss: 0.7983 - val_accuracy: 0.8571
Epoch 91/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7760 - accuracy: 0.8554 - val_loss: 0.8270 - val_accuracy: 0.8462
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7960 - accuracy: 0.8603 - val_loss: 0.8167 - val_accuracy: 0.8681
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7477 - accuracy: 0.8518 - val_loss: 0.7652 - val_accuracy: 0.8681
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7557 - accuracy: 0.8591 - val_loss: 0.8319 - val_accuracy: 0.8571
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7689 - accuracy: 0.8591 - val_loss: 0.8064 - val_accuracy: 0.8462
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7335 - accuracy: 0.8542 - val_loss: 0.8024 - val_accuracy: 0.8462
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7761 - accuracy: 0.8457 - val_loss: 0.8866 - val_accuracy: 0.8681
Epoch 98/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8101 - accuracy: 0.8323 - val_loss: 0.9003 - val_accuracy: 0.8571
Epoch 99/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7959 - accuracy: 0.8542 - val_loss: 0.8003 - val_accuracy: 0.8571
Epoch 100/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7971 - accuracy: 0.8493 - val_loss: 0.8000 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 4.3986 - accuracy: 0.5832 - val_loss: 1.8842 - val_accuracy: 0.8901
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 1.8441 - accuracy: 0.8408 - val_loss: 1.8541 - val_accuracy: 0.8901
Epoch 3/100
7/7 [==============================] - 0s 7ms/step - loss: 1.6347 - accuracy: 0.8299 - val_loss: 1.1720 - val_accuracy: 0.8901
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 1.2081 - accuracy: 0.8433 - val_loss: 1.0142 - val_accuracy: 0.8901
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 1.0644 - accuracy: 0.8384 - val_loss: 0.8967 - val_accuracy: 0.8901
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9461 - accuracy: 0.8457 - val_loss: 0.8254 - val_accuracy: 0.8901
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9032 - accuracy: 0.8457 - val_loss: 0.8180 - val_accuracy: 0.8901
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8621 - accuracy: 0.8445 - val_loss: 0.8006 - val_accuracy: 0.8901
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8352 - accuracy: 0.8457 - val_loss: 0.7931 - val_accuracy: 0.8901
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8755 - accuracy: 0.8420 - val_loss: 0.8122 - val_accuracy: 0.8901
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8736 - accuracy: 0.8481 - val_loss: 0.7566 - val_accuracy: 0.8901
Epoch 12/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7862 - accuracy: 0.8542 - val_loss: 0.8032 - val_accuracy: 0.8901
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8398 - accuracy: 0.8469 - val_loss: 0.7279 - val_accuracy: 0.8901
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8030 - accuracy: 0.8530 - val_loss: 0.7730 - val_accuracy: 0.8901
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7897 - accuracy: 0.8457 - val_loss: 0.7295 - val_accuracy: 0.8901
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8269 - accuracy: 0.8396 - val_loss: 0.7910 - val_accuracy: 0.8901
Epoch 17/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7757 - accuracy: 0.8530 - val_loss: 0.7268 - val_accuracy: 0.8901
Epoch 18/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8786 - accuracy: 0.8481 - val_loss: 0.7563 - val_accuracy: 0.8901
Epoch 19/100
7/7 [==============================] - 0s 5ms/step - loss: 0.7777 - accuracy: 0.8469 - val_loss: 0.7470 - val_accuracy: 0.8901
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7948 - accuracy: 0.8408 - val_loss: 0.6881 - val_accuracy: 0.8901
Epoch 21/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7869 - accuracy: 0.8505 - val_loss: 0.7404 - val_accuracy: 0.8901
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8122 - accuracy: 0.8433 - val_loss: 0.7431 - val_accuracy: 0.8901
Epoch 23/100
7/7 [==============================] - 0s 5ms/step - loss: 0.7768 - accuracy: 0.8396 - val_loss: 0.7322 - val_accuracy: 0.8901
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8167 - accuracy: 0.8275 - val_loss: 0.7487 - val_accuracy: 0.8901
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8143 - accuracy: 0.8530 - val_loss: 0.7331 - val_accuracy: 0.8901
Epoch 26/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8021 - accuracy: 0.8372 - val_loss: 0.7975 - val_accuracy: 0.8901
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8138 - accuracy: 0.8445 - val_loss: 0.6943 - val_accuracy: 0.8901
Epoch 28/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7828 - accuracy: 0.8481 - val_loss: 0.7240 - val_accuracy: 0.8901
Epoch 29/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8202 - accuracy: 0.8372 - val_loss: 0.7230 - val_accuracy: 0.8791
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8241 - accuracy: 0.8335 - val_loss: 0.6846 - val_accuracy: 0.8901
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7825 - accuracy: 0.8481 - val_loss: 0.7724 - val_accuracy: 0.8901
Epoch 32/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7714 - accuracy: 0.8578 - val_loss: 0.7168 - val_accuracy: 0.8901
Epoch 33/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7331 - accuracy: 0.8505 - val_loss: 0.7324 - val_accuracy: 0.8901
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8400 - accuracy: 0.8408 - val_loss: 0.7261 - val_accuracy: 0.8901
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8155 - accuracy: 0.8348 - val_loss: 0.7280 - val_accuracy: 0.8901
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8302 - accuracy: 0.8433 - val_loss: 0.7686 - val_accuracy: 0.8791
Epoch 37/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8327 - accuracy: 0.8408 - val_loss: 0.7255 - val_accuracy: 0.8901
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7748 - accuracy: 0.8505 - val_loss: 0.7169 - val_accuracy: 0.9011
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7911 - accuracy: 0.8481 - val_loss: 0.7656 - val_accuracy: 0.9011
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7969 - accuracy: 0.8433 - val_loss: 0.7186 - val_accuracy: 0.8901
Epoch 41/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7595 - accuracy: 0.8481 - val_loss: 0.7101 - val_accuracy: 0.8901
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7847 - accuracy: 0.8518 - val_loss: 0.7436 - val_accuracy: 0.8901
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7514 - accuracy: 0.8554 - val_loss: 0.7363 - val_accuracy: 0.8901
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7726 - accuracy: 0.8530 - val_loss: 0.7072 - val_accuracy: 0.8901
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7744 - accuracy: 0.8420 - val_loss: 0.6900 - val_accuracy: 0.8791
Epoch 46/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7747 - accuracy: 0.8408 - val_loss: 0.7081 - val_accuracy: 0.9011
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7516 - accuracy: 0.8469 - val_loss: 0.6890 - val_accuracy: 0.8901
Epoch 48/100
7/7 [==============================] - 0s 5ms/step - loss: 0.8174 - accuracy: 0.8505 - val_loss: 0.7259 - val_accuracy: 0.8901
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7807 - accuracy: 0.8408 - val_loss: 0.7054 - val_accuracy: 0.8901
Epoch 50/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7924 - accuracy: 0.8433 - val_loss: 0.6988 - val_accuracy: 0.8901
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7931 - accuracy: 0.8384 - val_loss: 0.7458 - val_accuracy: 0.8901
Epoch 52/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8398 - accuracy: 0.8505 - val_loss: 0.7334 - val_accuracy: 0.8901
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8083 - accuracy: 0.8554 - val_loss: 0.7327 - val_accuracy: 0.8791
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8028 - accuracy: 0.8396 - val_loss: 0.7223 - val_accuracy: 0.8901
Epoch 55/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7833 - accuracy: 0.8469 - val_loss: 0.6227 - val_accuracy: 0.8901
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7197 - accuracy: 0.8433 - val_loss: 0.7154 - val_accuracy: 0.9011
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8287 - accuracy: 0.8348 - val_loss: 0.7269 - val_accuracy: 0.8791
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7703 - accuracy: 0.8433 - val_loss: 0.7009 - val_accuracy: 0.8901
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8122 - accuracy: 0.8505 - val_loss: 0.6895 - val_accuracy: 0.8901
Epoch 60/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7818 - accuracy: 0.8408 - val_loss: 0.6944 - val_accuracy: 0.9011
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7966 - accuracy: 0.8384 - val_loss: 0.7304 - val_accuracy: 0.8901
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8272 - accuracy: 0.8481 - val_loss: 0.7873 - val_accuracy: 0.8571
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7930 - accuracy: 0.8408 - val_loss: 0.6816 - val_accuracy: 0.9011
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7960 - accuracy: 0.8493 - val_loss: 0.7959 - val_accuracy: 0.8681
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8091 - accuracy: 0.8505 - val_loss: 0.7242 - val_accuracy: 0.8791
Epoch 66/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8651 - accuracy: 0.8299 - val_loss: 0.8886 - val_accuracy: 0.8901
Epoch 67/100
7/7 [==============================] - 0s 6ms/step - loss: 0.9142 - accuracy: 0.8420 - val_loss: 0.7445 - val_accuracy: 0.8901
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8319 - accuracy: 0.8433 - val_loss: 0.8727 - val_accuracy: 0.8901
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9236 - accuracy: 0.8481 - val_loss: 0.8496 - val_accuracy: 0.9011
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8391 - accuracy: 0.8481 - val_loss: 0.7729 - val_accuracy: 0.9011
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8234 - accuracy: 0.8481 - val_loss: 0.6932 - val_accuracy: 0.8901
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8021 - accuracy: 0.8639 - val_loss: 0.6876 - val_accuracy: 0.9011
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7573 - accuracy: 0.8542 - val_loss: 0.7394 - val_accuracy: 0.8901
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8061 - accuracy: 0.8554 - val_loss: 0.6959 - val_accuracy: 0.8901
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8080 - accuracy: 0.8420 - val_loss: 0.7129 - val_accuracy: 0.8901
Epoch 76/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8228 - accuracy: 0.8408 - val_loss: 0.7301 - val_accuracy: 0.8791
Epoch 77/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7954 - accuracy: 0.8408 - val_loss: 0.7309 - val_accuracy: 0.8901
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7523 - accuracy: 0.8493 - val_loss: 0.7219 - val_accuracy: 0.9121
Epoch 79/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7856 - accuracy: 0.8396 - val_loss: 0.6632 - val_accuracy: 0.9011
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7226 - accuracy: 0.8566 - val_loss: 0.6466 - val_accuracy: 0.8901
Epoch 81/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7544 - accuracy: 0.8566 - val_loss: 0.7047 - val_accuracy: 0.9011
Epoch 82/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7670 - accuracy: 0.8530 - val_loss: 0.6984 - val_accuracy: 0.9011
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7715 - accuracy: 0.8335 - val_loss: 0.6723 - val_accuracy: 0.9121
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7479 - accuracy: 0.8445 - val_loss: 0.6737 - val_accuracy: 0.8791
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7201 - accuracy: 0.8530 - val_loss: 0.6845 - val_accuracy: 0.9121
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7317 - accuracy: 0.8518 - val_loss: 0.6815 - val_accuracy: 0.8901
Epoch 87/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7507 - accuracy: 0.8566 - val_loss: 0.7364 - val_accuracy: 0.8571
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7581 - accuracy: 0.8384 - val_loss: 0.6927 - val_accuracy: 0.9011
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7998 - accuracy: 0.8505 - val_loss: 0.8489 - val_accuracy: 0.8571
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8282 - accuracy: 0.8433 - val_loss: 0.7869 - val_accuracy: 0.8901
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7874 - accuracy: 0.8554 - val_loss: 0.6545 - val_accuracy: 0.8791
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7971 - accuracy: 0.8408 - val_loss: 0.7021 - val_accuracy: 0.8901
Epoch 93/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7626 - accuracy: 0.8420 - val_loss: 0.6892 - val_accuracy: 0.9121
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7996 - accuracy: 0.8505 - val_loss: 0.7237 - val_accuracy: 0.8901
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7921 - accuracy: 0.8481 - val_loss: 0.7121 - val_accuracy: 0.9011
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7941 - accuracy: 0.8469 - val_loss: 0.7343 - val_accuracy: 0.9011
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8476 - accuracy: 0.8299 - val_loss: 0.7839 - val_accuracy: 0.8901
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8324 - accuracy: 0.8420 - val_loss: 0.7614 - val_accuracy: 0.9121
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8003 - accuracy: 0.8372 - val_loss: 0.6749 - val_accuracy: 0.8791
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7763 - accuracy: 0.8663 - val_loss: 0.7038 - val_accuracy: 0.8901
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 4.3900 - accuracy: 0.5808 - val_loss: 1.9953 - val_accuracy: 0.8352
Epoch 2/100
7/7 [==============================] - 0s 6ms/step - loss: 1.7552 - accuracy: 0.8408 - val_loss: 1.9358 - val_accuracy: 0.8352
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 1.5300 - accuracy: 0.8445 - val_loss: 1.2201 - val_accuracy: 0.8352
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 1.1812 - accuracy: 0.8591 - val_loss: 1.2080 - val_accuracy: 0.8352
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 0.9905 - accuracy: 0.8493 - val_loss: 0.9813 - val_accuracy: 0.8352
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8494 - accuracy: 0.8542 - val_loss: 0.9514 - val_accuracy: 0.8352
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8143 - accuracy: 0.8445 - val_loss: 0.9002 - val_accuracy: 0.8352
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8261 - accuracy: 0.8530 - val_loss: 0.9127 - val_accuracy: 0.8352
Epoch 9/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8420 - accuracy: 0.8493 - val_loss: 0.9466 - val_accuracy: 0.8352
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8220 - accuracy: 0.8469 - val_loss: 0.9060 - val_accuracy: 0.8352
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8387 - accuracy: 0.8396 - val_loss: 0.9152 - val_accuracy: 0.8352
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7770 - accuracy: 0.8578 - val_loss: 0.8551 - val_accuracy: 0.8352
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7663 - accuracy: 0.8542 - val_loss: 0.8688 - val_accuracy: 0.8352
Epoch 14/100
7/7 [==============================] - 0s 11ms/step - loss: 0.7467 - accuracy: 0.8493 - val_loss: 0.8662 - val_accuracy: 0.8352
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8387 - accuracy: 0.8396 - val_loss: 0.9161 - val_accuracy: 0.8352
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8334 - accuracy: 0.8554 - val_loss: 0.9466 - val_accuracy: 0.8352
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8069 - accuracy: 0.8566 - val_loss: 0.9218 - val_accuracy: 0.8352
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8531 - accuracy: 0.8372 - val_loss: 0.8806 - val_accuracy: 0.8352
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7393 - accuracy: 0.8505 - val_loss: 0.8888 - val_accuracy: 0.8352
Epoch 20/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7638 - accuracy: 0.8651 - val_loss: 0.8623 - val_accuracy: 0.8352
Epoch 21/100
7/7 [==============================] - 0s 7ms/step - loss: 0.8109 - accuracy: 0.8481 - val_loss: 0.8436 - val_accuracy: 0.8352
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7197 - accuracy: 0.8530 - val_loss: 0.8618 - val_accuracy: 0.8352
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7966 - accuracy: 0.8554 - val_loss: 0.8816 - val_accuracy: 0.8352
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8357 - accuracy: 0.8505 - val_loss: 0.9120 - val_accuracy: 0.8352
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8089 - accuracy: 0.8505 - val_loss: 0.8602 - val_accuracy: 0.8352
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8164 - accuracy: 0.8505 - val_loss: 0.8886 - val_accuracy: 0.8352
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7347 - accuracy: 0.8578 - val_loss: 0.8218 - val_accuracy: 0.8352
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7456 - accuracy: 0.8578 - val_loss: 0.8879 - val_accuracy: 0.8352
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7998 - accuracy: 0.8469 - val_loss: 0.9007 - val_accuracy: 0.8352
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8292 - accuracy: 0.8433 - val_loss: 0.9207 - val_accuracy: 0.8352
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8304 - accuracy: 0.8481 - val_loss: 0.9291 - val_accuracy: 0.8352
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7634 - accuracy: 0.8591 - val_loss: 0.8604 - val_accuracy: 0.8352
Epoch 33/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7268 - accuracy: 0.8566 - val_loss: 0.8375 - val_accuracy: 0.8352
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7695 - accuracy: 0.8566 - val_loss: 0.8040 - val_accuracy: 0.8352
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7693 - accuracy: 0.8518 - val_loss: 0.8747 - val_accuracy: 0.8352
Epoch 36/100
7/7 [==============================] - 0s 7ms/step - loss: 0.7682 - accuracy: 0.8603 - val_loss: 0.8584 - val_accuracy: 0.8352
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7763 - accuracy: 0.8530 - val_loss: 0.9021 - val_accuracy: 0.8352
Epoch 38/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7751 - accuracy: 0.8578 - val_loss: 0.8411 - val_accuracy: 0.8352
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7290 - accuracy: 0.8566 - val_loss: 0.7899 - val_accuracy: 0.8352
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7582 - accuracy: 0.8493 - val_loss: 0.8774 - val_accuracy: 0.8352
Epoch 41/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7954 - accuracy: 0.8566 - val_loss: 0.9097 - val_accuracy: 0.8352
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7901 - accuracy: 0.8505 - val_loss: 0.8305 - val_accuracy: 0.8352
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7134 - accuracy: 0.8566 - val_loss: 0.8256 - val_accuracy: 0.8352
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7253 - accuracy: 0.8639 - val_loss: 0.8459 - val_accuracy: 0.8352
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7322 - accuracy: 0.8505 - val_loss: 0.9804 - val_accuracy: 0.8352
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8071 - accuracy: 0.8663 - val_loss: 0.9264 - val_accuracy: 0.8242
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8405 - accuracy: 0.8408 - val_loss: 0.9193 - val_accuracy: 0.8352
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8058 - accuracy: 0.8615 - val_loss: 0.8844 - val_accuracy: 0.8352
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7478 - accuracy: 0.8603 - val_loss: 0.8027 - val_accuracy: 0.8352
Epoch 50/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7281 - accuracy: 0.8578 - val_loss: 0.9325 - val_accuracy: 0.8242
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8140 - accuracy: 0.8457 - val_loss: 0.9666 - val_accuracy: 0.7912
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 0.8982 - accuracy: 0.8433 - val_loss: 0.8031 - val_accuracy: 0.8352
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7651 - accuracy: 0.8518 - val_loss: 0.8397 - val_accuracy: 0.8242
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7581 - accuracy: 0.8639 - val_loss: 0.7943 - val_accuracy: 0.8352
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7899 - accuracy: 0.8457 - val_loss: 0.8718 - val_accuracy: 0.8242
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 0.8282 - accuracy: 0.8481 - val_loss: 0.8275 - val_accuracy: 0.8352
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7882 - accuracy: 0.8566 - val_loss: 0.8325 - val_accuracy: 0.8352
Epoch 58/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7401 - accuracy: 0.8566 - val_loss: 0.8381 - val_accuracy: 0.8242
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7752 - accuracy: 0.8457 - val_loss: 0.8502 - val_accuracy: 0.8242
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7483 - accuracy: 0.8542 - val_loss: 0.8339 - val_accuracy: 0.8132
Epoch 61/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7204 - accuracy: 0.8591 - val_loss: 0.8088 - val_accuracy: 0.8352
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7304 - accuracy: 0.8554 - val_loss: 0.7919 - val_accuracy: 0.8242
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7617 - accuracy: 0.8518 - val_loss: 0.8196 - val_accuracy: 0.8242
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7010 - accuracy: 0.8530 - val_loss: 0.7673 - val_accuracy: 0.8242
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7001 - accuracy: 0.8481 - val_loss: 0.7795 - val_accuracy: 0.8352
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7143 - accuracy: 0.8518 - val_loss: 0.7873 - val_accuracy: 0.8352
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7469 - accuracy: 0.8372 - val_loss: 0.7882 - val_accuracy: 0.7912
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7667 - accuracy: 0.8615 - val_loss: 0.8252 - val_accuracy: 0.8352
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7636 - accuracy: 0.8566 - val_loss: 0.8203 - val_accuracy: 0.8352
Epoch 70/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7673 - accuracy: 0.8481 - val_loss: 0.8489 - val_accuracy: 0.8462
Epoch 71/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7764 - accuracy: 0.8603 - val_loss: 0.8480 - val_accuracy: 0.8242
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7649 - accuracy: 0.8505 - val_loss: 0.8449 - val_accuracy: 0.8352
Epoch 73/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7684 - accuracy: 0.8493 - val_loss: 0.8735 - val_accuracy: 0.8352
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7415 - accuracy: 0.8615 - val_loss: 0.8660 - val_accuracy: 0.8242
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7506 - accuracy: 0.8591 - val_loss: 0.9091 - val_accuracy: 0.8132
Epoch 76/100
7/7 [==============================] - 0s 6ms/step - loss: 0.8473 - accuracy: 0.8433 - val_loss: 0.8143 - val_accuracy: 0.8352
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7533 - accuracy: 0.8542 - val_loss: 0.7847 - val_accuracy: 0.8352
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7472 - accuracy: 0.8736 - val_loss: 0.8523 - val_accuracy: 0.8352
Epoch 79/100
7/7 [==============================] - 0s 10ms/step - loss: 0.7501 - accuracy: 0.8554 - val_loss: 0.8388 - val_accuracy: 0.8352
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7708 - accuracy: 0.8603 - val_loss: 0.8773 - val_accuracy: 0.8022
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7596 - accuracy: 0.8530 - val_loss: 0.8017 - val_accuracy: 0.8352
Epoch 82/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7166 - accuracy: 0.8469 - val_loss: 0.7602 - val_accuracy: 0.8352
Epoch 83/100
7/7 [==============================] - 0s 5ms/step - loss: 0.7225 - accuracy: 0.8542 - val_loss: 0.8379 - val_accuracy: 0.8132
Epoch 84/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7445 - accuracy: 0.8542 - val_loss: 0.7581 - val_accuracy: 0.8352
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7540 - accuracy: 0.8505 - val_loss: 0.8805 - val_accuracy: 0.8242
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7540 - accuracy: 0.8542 - val_loss: 0.7765 - val_accuracy: 0.8352
Epoch 87/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7354 - accuracy: 0.8566 - val_loss: 0.8027 - val_accuracy: 0.8352
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7271 - accuracy: 0.8554 - val_loss: 0.8263 - val_accuracy: 0.8132
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7419 - accuracy: 0.8481 - val_loss: 0.7821 - val_accuracy: 0.8462
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7489 - accuracy: 0.8469 - val_loss: 0.7639 - val_accuracy: 0.8242
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7485 - accuracy: 0.8639 - val_loss: 0.7843 - val_accuracy: 0.8352
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7275 - accuracy: 0.8554 - val_loss: 0.8452 - val_accuracy: 0.7912
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7649 - accuracy: 0.8663 - val_loss: 0.7642 - val_accuracy: 0.8022
Epoch 94/100
7/7 [==============================] - 0s 6ms/step - loss: 0.7434 - accuracy: 0.8554 - val_loss: 0.7937 - val_accuracy: 0.8462
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7174 - accuracy: 0.8578 - val_loss: 0.7517 - val_accuracy: 0.7912
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7014 - accuracy: 0.8542 - val_loss: 0.7700 - val_accuracy: 0.8022
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7011 - accuracy: 0.8578 - val_loss: 0.7079 - val_accuracy: 0.8462
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7029 - accuracy: 0.8481 - val_loss: 0.7686 - val_accuracy: 0.7912
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 0.7433 - accuracy: 0.8469 - val_loss: 0.8605 - val_accuracy: 0.8352
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 0.7195 - accuracy: 0.8627 - val_loss: 0.7777 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Experiment number: 3
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
4/4 [==============================] - 1s 84ms/step - loss: 16.1639 - accuracy: 0.2968 - val_loss: 15.1150 - val_accuracy: 0.4130
Epoch 2/100
4/4 [==============================] - 0s 17ms/step - loss: 15.5175 - accuracy: 0.3212 - val_loss: 14.5769 - val_accuracy: 0.5326
Epoch 3/100
4/4 [==============================] - 0s 16ms/step - loss: 14.8270 - accuracy: 0.3735 - val_loss: 14.0466 - val_accuracy: 0.6848
Epoch 4/100
4/4 [==============================] - 0s 17ms/step - loss: 14.2168 - accuracy: 0.4343 - val_loss: 13.5292 - val_accuracy: 0.7174
Epoch 5/100
4/4 [==============================] - 0s 12ms/step - loss: 13.6448 - accuracy: 0.4757 - val_loss: 13.0218 - val_accuracy: 0.7609
Epoch 6/100
4/4 [==============================] - 0s 16ms/step - loss: 13.1250 - accuracy: 0.5109 - val_loss: 12.5250 - val_accuracy: 0.7717
Epoch 7/100
4/4 [==============================] - 0s 17ms/step - loss: 12.6802 - accuracy: 0.5511 - val_loss: 12.0424 - val_accuracy: 0.7826
Epoch 8/100
4/4 [==============================] - 0s 11ms/step - loss: 12.1426 - accuracy: 0.5937 - val_loss: 11.5710 - val_accuracy: 0.7717
Epoch 9/100
4/4 [==============================] - 0s 15ms/step - loss: 11.6432 - accuracy: 0.6022 - val_loss: 11.1079 - val_accuracy: 0.7935
Epoch 10/100
4/4 [==============================] - 0s 17ms/step - loss: 11.1492 - accuracy: 0.6363 - val_loss: 10.6553 - val_accuracy: 0.8261
Epoch 11/100
4/4 [==============================] - 0s 17ms/step - loss: 10.6732 - accuracy: 0.6484 - val_loss: 10.2073 - val_accuracy: 0.8587
Epoch 12/100
4/4 [==============================] - 0s 17ms/step - loss: 10.2061 - accuracy: 0.6837 - val_loss: 9.7668 - val_accuracy: 0.8370
Epoch 13/100
4/4 [==============================] - 0s 12ms/step - loss: 9.7826 - accuracy: 0.6764 - val_loss: 9.3424 - val_accuracy: 0.8370
Epoch 14/100
4/4 [==============================] - 0s 17ms/step - loss: 9.3468 - accuracy: 0.6764 - val_loss: 8.9314 - val_accuracy: 0.8370
Epoch 15/100
4/4 [==============================] - 0s 17ms/step - loss: 8.9255 - accuracy: 0.6849 - val_loss: 8.5290 - val_accuracy: 0.8370
Epoch 16/100
4/4 [==============================] - 0s 16ms/step - loss: 8.5432 - accuracy: 0.7117 - val_loss: 8.1347 - val_accuracy: 0.8370
Epoch 17/100
4/4 [==============================] - 0s 15ms/step - loss: 8.1596 - accuracy: 0.7153 - val_loss: 7.7506 - val_accuracy: 0.8370
Epoch 18/100
4/4 [==============================] - 0s 12ms/step - loss: 7.7642 - accuracy: 0.7445 - val_loss: 7.3750 - val_accuracy: 0.8370
Epoch 19/100
4/4 [==============================] - 0s 17ms/step - loss: 7.3673 - accuracy: 0.7482 - val_loss: 7.0100 - val_accuracy: 0.8370
Epoch 20/100
4/4 [==============================] - 0s 16ms/step - loss: 6.9764 - accuracy: 0.7603 - val_loss: 6.6619 - val_accuracy: 0.8370
Epoch 21/100
4/4 [==============================] - 0s 17ms/step - loss: 6.6291 - accuracy: 0.7810 - val_loss: 6.3219 - val_accuracy: 0.8370
Epoch 22/100
4/4 [==============================] - 0s 17ms/step - loss: 6.2720 - accuracy: 0.7871 - val_loss: 5.9921 - val_accuracy: 0.8370
Epoch 23/100
4/4 [==============================] - 0s 16ms/step - loss: 5.9363 - accuracy: 0.7859 - val_loss: 5.6669 - val_accuracy: 0.8370
Epoch 24/100
4/4 [==============================] - 0s 16ms/step - loss: 5.6291 - accuracy: 0.7859 - val_loss: 5.3546 - val_accuracy: 0.8370
Epoch 25/100
4/4 [==============================] - 0s 15ms/step - loss: 5.2924 - accuracy: 0.8236 - val_loss: 5.0572 - val_accuracy: 0.8370
Epoch 26/100
4/4 [==============================] - 0s 10ms/step - loss: 4.9714 - accuracy: 0.8236 - val_loss: 4.7679 - val_accuracy: 0.8370
Epoch 27/100
4/4 [==============================] - 0s 11ms/step - loss: 4.7348 - accuracy: 0.8029 - val_loss: 4.4901 - val_accuracy: 0.8370
Epoch 28/100
4/4 [==============================] - 0s 17ms/step - loss: 4.3948 - accuracy: 0.8224 - val_loss: 4.2211 - val_accuracy: 0.8370
Epoch 29/100
4/4 [==============================] - 0s 16ms/step - loss: 4.1364 - accuracy: 0.8309 - val_loss: 3.9694 - val_accuracy: 0.8370
Epoch 30/100
4/4 [==============================] - 0s 16ms/step - loss: 3.8610 - accuracy: 0.8516 - val_loss: 3.7259 - val_accuracy: 0.8370
Epoch 31/100
4/4 [==============================] - 0s 17ms/step - loss: 3.6060 - accuracy: 0.8455 - val_loss: 3.4935 - val_accuracy: 0.8370
Epoch 32/100
4/4 [==============================] - 0s 12ms/step - loss: 3.3915 - accuracy: 0.8418 - val_loss: 3.2778 - val_accuracy: 0.8370
Epoch 33/100
4/4 [==============================] - 0s 18ms/step - loss: 3.1502 - accuracy: 0.8564 - val_loss: 3.0765 - val_accuracy: 0.8370
Epoch 34/100
4/4 [==============================] - 0s 12ms/step - loss: 2.9668 - accuracy: 0.8236 - val_loss: 2.8886 - val_accuracy: 0.8370
Epoch 35/100
4/4 [==============================] - 0s 11ms/step - loss: 2.7255 - accuracy: 0.8589 - val_loss: 2.7079 - val_accuracy: 0.8370
Epoch 36/100
4/4 [==============================] - 0s 14ms/step - loss: 2.5658 - accuracy: 0.8528 - val_loss: 2.5295 - val_accuracy: 0.8370
Epoch 37/100
4/4 [==============================] - 0s 14ms/step - loss: 2.3633 - accuracy: 0.8783 - val_loss: 2.3524 - val_accuracy: 0.8370
Epoch 38/100
4/4 [==============================] - 0s 16ms/step - loss: 2.1735 - accuracy: 0.8759 - val_loss: 2.1870 - val_accuracy: 0.8370
Epoch 39/100
4/4 [==============================] - 0s 11ms/step - loss: 2.0321 - accuracy: 0.8674 - val_loss: 2.0274 - val_accuracy: 0.8370
Epoch 40/100
4/4 [==============================] - 0s 17ms/step - loss: 1.8599 - accuracy: 0.8686 - val_loss: 1.8802 - val_accuracy: 0.8370
Epoch 41/100
4/4 [==============================] - 0s 19ms/step - loss: 1.7049 - accuracy: 0.8613 - val_loss: 1.7455 - val_accuracy: 0.8370
Epoch 42/100
4/4 [==============================] - 0s 10ms/step - loss: 1.5560 - accuracy: 0.8759 - val_loss: 1.6211 - val_accuracy: 0.8370
Epoch 43/100
4/4 [==============================] - 0s 11ms/step - loss: 1.4230 - accuracy: 0.8820 - val_loss: 1.5011 - val_accuracy: 0.8370
Epoch 44/100
4/4 [==============================] - 0s 15ms/step - loss: 1.2900 - accuracy: 0.8735 - val_loss: 1.3903 - val_accuracy: 0.8370
Epoch 45/100
4/4 [==============================] - 0s 13ms/step - loss: 1.1955 - accuracy: 0.8723 - val_loss: 1.2862 - val_accuracy: 0.8370
Epoch 46/100
4/4 [==============================] - 0s 12ms/step - loss: 1.0930 - accuracy: 0.8601 - val_loss: 1.1988 - val_accuracy: 0.8370
Epoch 47/100
4/4 [==============================] - 0s 11ms/step - loss: 0.9998 - accuracy: 0.8601 - val_loss: 1.1155 - val_accuracy: 0.8370
Epoch 48/100
4/4 [==============================] - 0s 15ms/step - loss: 0.9015 - accuracy: 0.8759 - val_loss: 1.0373 - val_accuracy: 0.8370
Epoch 49/100
4/4 [==============================] - 0s 13ms/step - loss: 0.8159 - accuracy: 0.8674 - val_loss: 0.9767 - val_accuracy: 0.8370
Epoch 50/100
4/4 [==============================] - 0s 12ms/step - loss: 0.7799 - accuracy: 0.8735 - val_loss: 0.9281 - val_accuracy: 0.8370
Epoch 51/100
4/4 [==============================] - 0s 11ms/step - loss: 0.7360 - accuracy: 0.8674 - val_loss: 0.8849 - val_accuracy: 0.8370
Epoch 52/100
4/4 [==============================] - 0s 11ms/step - loss: 0.6859 - accuracy: 0.8613 - val_loss: 0.8469 - val_accuracy: 0.8370
Epoch 53/100
4/4 [==============================] - 0s 10ms/step - loss: 0.6371 - accuracy: 0.8759 - val_loss: 0.8205 - val_accuracy: 0.8370
Epoch 54/100
4/4 [==============================] - 0s 10ms/step - loss: 0.6146 - accuracy: 0.8674 - val_loss: 0.8003 - val_accuracy: 0.8370
Epoch 55/100
4/4 [==============================] - 0s 14ms/step - loss: 0.5817 - accuracy: 0.8820 - val_loss: 0.7750 - val_accuracy: 0.8370
Epoch 56/100
4/4 [==============================] - 0s 12ms/step - loss: 0.5600 - accuracy: 0.8674 - val_loss: 0.7504 - val_accuracy: 0.8370
Epoch 57/100
4/4 [==============================] - 0s 12ms/step - loss: 0.5393 - accuracy: 0.8674 - val_loss: 0.7300 - val_accuracy: 0.8370
Epoch 58/100
4/4 [==============================] - 0s 11ms/step - loss: 0.5204 - accuracy: 0.8710 - val_loss: 0.7162 - val_accuracy: 0.8370
Epoch 59/100
4/4 [==============================] - 0s 15ms/step - loss: 0.5013 - accuracy: 0.8771 - val_loss: 0.6965 - val_accuracy: 0.8370
Epoch 60/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4869 - accuracy: 0.8759 - val_loss: 0.6829 - val_accuracy: 0.8370
Epoch 61/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4839 - accuracy: 0.8710 - val_loss: 0.6776 - val_accuracy: 0.8370
Epoch 62/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4756 - accuracy: 0.8698 - val_loss: 0.6684 - val_accuracy: 0.8370
Epoch 63/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4641 - accuracy: 0.8674 - val_loss: 0.6600 - val_accuracy: 0.8370
Epoch 64/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4542 - accuracy: 0.8686 - val_loss: 0.6520 - val_accuracy: 0.8370
Epoch 65/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4371 - accuracy: 0.8796 - val_loss: 0.6471 - val_accuracy: 0.8370
Epoch 66/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4350 - accuracy: 0.8771 - val_loss: 0.6410 - val_accuracy: 0.8370
Epoch 67/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4399 - accuracy: 0.8637 - val_loss: 0.6310 - val_accuracy: 0.8370
Epoch 68/100
4/4 [==============================] - 0s 10ms/step - loss: 0.4330 - accuracy: 0.8613 - val_loss: 0.6253 - val_accuracy: 0.8370
Epoch 69/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4298 - accuracy: 0.8710 - val_loss: 0.6271 - val_accuracy: 0.8370
Epoch 70/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4257 - accuracy: 0.8662 - val_loss: 0.6238 - val_accuracy: 0.8370
Epoch 71/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4293 - accuracy: 0.8674 - val_loss: 0.6170 - val_accuracy: 0.8370
Epoch 72/100
4/4 [==============================] - 0s 10ms/step - loss: 0.4330 - accuracy: 0.8528 - val_loss: 0.6141 - val_accuracy: 0.8370
Epoch 73/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4223 - accuracy: 0.8710 - val_loss: 0.6080 - val_accuracy: 0.8370
Epoch 74/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4176 - accuracy: 0.8674 - val_loss: 0.6083 - val_accuracy: 0.8370
Epoch 75/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4197 - accuracy: 0.8637 - val_loss: 0.6054 - val_accuracy: 0.8370
Epoch 76/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4064 - accuracy: 0.8710 - val_loss: 0.6028 - val_accuracy: 0.8370
Epoch 77/100
4/4 [==============================] - 0s 10ms/step - loss: 0.4081 - accuracy: 0.8771 - val_loss: 0.5959 - val_accuracy: 0.8370
Epoch 78/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4128 - accuracy: 0.8747 - val_loss: 0.5951 - val_accuracy: 0.8370
Epoch 79/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4155 - accuracy: 0.8710 - val_loss: 0.5961 - val_accuracy: 0.8370
Epoch 80/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4060 - accuracy: 0.8686 - val_loss: 0.5936 - val_accuracy: 0.8370
Epoch 81/100
4/4 [==============================] - 0s 10ms/step - loss: 0.4056 - accuracy: 0.8723 - val_loss: 0.5835 - val_accuracy: 0.8370
Epoch 82/100
4/4 [==============================] - 0s 10ms/step - loss: 0.3974 - accuracy: 0.8637 - val_loss: 0.5794 - val_accuracy: 0.8370
Epoch 83/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3859 - accuracy: 0.8808 - val_loss: 0.5774 - val_accuracy: 0.8370
Epoch 84/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3921 - accuracy: 0.8783 - val_loss: 0.5742 - val_accuracy: 0.8370
Epoch 85/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3865 - accuracy: 0.8783 - val_loss: 0.5739 - val_accuracy: 0.8370
Epoch 86/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3956 - accuracy: 0.8625 - val_loss: 0.5737 - val_accuracy: 0.8370
Epoch 87/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3865 - accuracy: 0.8735 - val_loss: 0.5667 - val_accuracy: 0.8370
Epoch 88/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3796 - accuracy: 0.8783 - val_loss: 0.5623 - val_accuracy: 0.8370
Epoch 89/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3839 - accuracy: 0.8662 - val_loss: 0.5648 - val_accuracy: 0.8370
Epoch 90/100
4/4 [==============================] - 0s 10ms/step - loss: 0.3831 - accuracy: 0.8747 - val_loss: 0.5604 - val_accuracy: 0.8370
Epoch 91/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3762 - accuracy: 0.8674 - val_loss: 0.5576 - val_accuracy: 0.8370
Epoch 92/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3933 - accuracy: 0.8613 - val_loss: 0.5551 - val_accuracy: 0.8370
Epoch 93/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3788 - accuracy: 0.8723 - val_loss: 0.5557 - val_accuracy: 0.8370
Epoch 94/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3845 - accuracy: 0.8625 - val_loss: 0.5509 - val_accuracy: 0.8370
Epoch 95/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3884 - accuracy: 0.8662 - val_loss: 0.5475 - val_accuracy: 0.8370
Epoch 96/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3860 - accuracy: 0.8747 - val_loss: 0.5491 - val_accuracy: 0.8370
Epoch 97/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3797 - accuracy: 0.8796 - val_loss: 0.5505 - val_accuracy: 0.8370
Epoch 98/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3858 - accuracy: 0.8698 - val_loss: 0.5442 - val_accuracy: 0.8370
Epoch 99/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3873 - accuracy: 0.8747 - val_loss: 0.5369 - val_accuracy: 0.8370
Epoch 100/100
4/4 [==============================] - 0s 10ms/step - loss: 0.3887 - accuracy: 0.8686 - val_loss: 0.5369 - val_accuracy: 0.8370
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
4/4 [==============================] - 1s 91ms/step - loss: 16.4256 - accuracy: 0.2470 - val_loss: 15.2329 - val_accuracy: 0.3587
Epoch 2/100
4/4 [==============================] - 0s 15ms/step - loss: 15.6395 - accuracy: 0.3090 - val_loss: 14.6803 - val_accuracy: 0.4891
Epoch 3/100
4/4 [==============================] - 0s 13ms/step - loss: 15.0734 - accuracy: 0.3394 - val_loss: 14.1390 - val_accuracy: 0.6739
Epoch 4/100
4/4 [==============================] - 0s 12ms/step - loss: 14.3764 - accuracy: 0.3869 - val_loss: 13.6094 - val_accuracy: 0.7065
Epoch 5/100
4/4 [==============================] - 0s 11ms/step - loss: 13.7552 - accuracy: 0.4319 - val_loss: 13.0900 - val_accuracy: 0.7609
Epoch 6/100
4/4 [==============================] - 0s 16ms/step - loss: 13.2823 - accuracy: 0.4623 - val_loss: 12.5847 - val_accuracy: 0.7717
Epoch 7/100
4/4 [==============================] - 0s 13ms/step - loss: 12.7371 - accuracy: 0.5219 - val_loss: 12.0848 - val_accuracy: 0.7935
Epoch 8/100
4/4 [==============================] - 0s 12ms/step - loss: 12.1609 - accuracy: 0.5511 - val_loss: 11.5993 - val_accuracy: 0.7826
Epoch 9/100
4/4 [==============================] - 0s 11ms/step - loss: 11.6572 - accuracy: 0.5572 - val_loss: 11.1245 - val_accuracy: 0.7935
Epoch 10/100
4/4 [==============================] - 0s 15ms/step - loss: 11.1833 - accuracy: 0.5876 - val_loss: 10.6616 - val_accuracy: 0.7935
Epoch 11/100
4/4 [==============================] - 0s 14ms/step - loss: 10.7009 - accuracy: 0.6095 - val_loss: 10.2133 - val_accuracy: 0.7826
Epoch 12/100
4/4 [==============================] - 0s 12ms/step - loss: 10.2700 - accuracy: 0.6180 - val_loss: 9.7799 - val_accuracy: 0.7935
Epoch 13/100
4/4 [==============================] - 0s 11ms/step - loss: 9.7763 - accuracy: 0.6423 - val_loss: 9.3597 - val_accuracy: 0.7935
Epoch 14/100
4/4 [==============================] - 0s 15ms/step - loss: 9.4123 - accuracy: 0.6375 - val_loss: 8.9458 - val_accuracy: 0.7935
Epoch 15/100
4/4 [==============================] - 0s 13ms/step - loss: 8.9641 - accuracy: 0.6630 - val_loss: 8.5395 - val_accuracy: 0.7935
Epoch 16/100
4/4 [==============================] - 0s 12ms/step - loss: 8.5313 - accuracy: 0.6691 - val_loss: 8.1438 - val_accuracy: 0.7935
Epoch 17/100
4/4 [==============================] - 0s 12ms/step - loss: 8.1355 - accuracy: 0.6934 - val_loss: 7.7556 - val_accuracy: 0.7935
Epoch 18/100
4/4 [==============================] - 0s 15ms/step - loss: 7.7096 - accuracy: 0.6959 - val_loss: 7.3744 - val_accuracy: 0.7935
Epoch 19/100
4/4 [==============================] - 0s 14ms/step - loss: 7.3179 - accuracy: 0.7275 - val_loss: 7.0081 - val_accuracy: 0.7935
Epoch 20/100
4/4 [==============================] - 0s 12ms/step - loss: 6.9420 - accuracy: 0.7336 - val_loss: 6.6535 - val_accuracy: 0.7935
Epoch 21/100
4/4 [==============================] - 0s 14ms/step - loss: 6.6499 - accuracy: 0.7263 - val_loss: 6.3145 - val_accuracy: 0.7935
Epoch 22/100
4/4 [==============================] - 0s 17ms/step - loss: 6.2246 - accuracy: 0.7725 - val_loss: 5.9855 - val_accuracy: 0.7935
Epoch 23/100
4/4 [==============================] - 0s 15ms/step - loss: 5.8969 - accuracy: 0.7725 - val_loss: 5.6666 - val_accuracy: 0.7935
Epoch 24/100
4/4 [==============================] - 0s 15ms/step - loss: 5.5900 - accuracy: 0.7628 - val_loss: 5.3558 - val_accuracy: 0.7935
Epoch 25/100
4/4 [==============================] - 0s 16ms/step - loss: 5.2788 - accuracy: 0.7506 - val_loss: 5.0558 - val_accuracy: 0.7935
Epoch 26/100
4/4 [==============================] - 0s 14ms/step - loss: 4.9198 - accuracy: 0.8090 - val_loss: 4.7682 - val_accuracy: 0.7935
Epoch 27/100
4/4 [==============================] - 0s 11ms/step - loss: 4.6452 - accuracy: 0.7883 - val_loss: 4.4872 - val_accuracy: 0.7935
Epoch 28/100
4/4 [==============================] - 0s 16ms/step - loss: 4.3634 - accuracy: 0.8102 - val_loss: 4.2165 - val_accuracy: 0.7935
Epoch 29/100
4/4 [==============================] - 0s 16ms/step - loss: 4.0758 - accuracy: 0.8139 - val_loss: 3.9542 - val_accuracy: 0.7935
Epoch 30/100
4/4 [==============================] - 0s 18ms/step - loss: 3.7979 - accuracy: 0.8297 - val_loss: 3.7043 - val_accuracy: 0.7935
Epoch 31/100
4/4 [==============================] - 0s 14ms/step - loss: 3.5626 - accuracy: 0.8200 - val_loss: 3.4627 - val_accuracy: 0.7935
Epoch 32/100
4/4 [==============================] - 0s 11ms/step - loss: 3.3081 - accuracy: 0.8455 - val_loss: 3.2325 - val_accuracy: 0.7935
Epoch 33/100
4/4 [==============================] - 0s 16ms/step - loss: 3.0605 - accuracy: 0.8431 - val_loss: 3.0168 - val_accuracy: 0.7935
Epoch 34/100
4/4 [==============================] - 0s 17ms/step - loss: 2.8290 - accuracy: 0.8516 - val_loss: 2.8128 - val_accuracy: 0.7935
Epoch 35/100
4/4 [==============================] - 0s 16ms/step - loss: 2.6058 - accuracy: 0.8455 - val_loss: 2.6178 - val_accuracy: 0.7935
Epoch 36/100
4/4 [==============================] - 0s 19ms/step - loss: 2.4461 - accuracy: 0.8406 - val_loss: 2.4278 - val_accuracy: 0.7935
Epoch 37/100
4/4 [==============================] - 0s 11ms/step - loss: 2.1957 - accuracy: 0.8552 - val_loss: 2.2505 - val_accuracy: 0.7935
Epoch 38/100
4/4 [==============================] - 0s 11ms/step - loss: 2.0209 - accuracy: 0.8637 - val_loss: 2.0787 - val_accuracy: 0.7935
Epoch 39/100
4/4 [==============================] - 0s 16ms/step - loss: 1.8401 - accuracy: 0.8601 - val_loss: 1.9195 - val_accuracy: 0.7935
Epoch 40/100
4/4 [==============================] - 0s 15ms/step - loss: 1.6931 - accuracy: 0.8552 - val_loss: 1.7741 - val_accuracy: 0.7935
Epoch 41/100
4/4 [==============================] - 0s 11ms/step - loss: 1.5299 - accuracy: 0.8686 - val_loss: 1.6334 - val_accuracy: 0.7935
Epoch 42/100
4/4 [==============================] - 0s 10ms/step - loss: 1.4007 - accuracy: 0.8589 - val_loss: 1.5045 - val_accuracy: 0.7935
Epoch 43/100
4/4 [==============================] - 0s 16ms/step - loss: 1.2811 - accuracy: 0.8467 - val_loss: 1.3959 - val_accuracy: 0.7935
Epoch 44/100
4/4 [==============================] - 0s 15ms/step - loss: 1.1524 - accuracy: 0.8662 - val_loss: 1.2983 - val_accuracy: 0.7935
Epoch 45/100
4/4 [==============================] - 0s 18ms/step - loss: 1.0536 - accuracy: 0.8625 - val_loss: 1.2070 - val_accuracy: 0.7935
Epoch 46/100
4/4 [==============================] - 0s 16ms/step - loss: 0.9588 - accuracy: 0.8686 - val_loss: 1.1264 - val_accuracy: 0.7935
Epoch 47/100
4/4 [==============================] - 0s 15ms/step - loss: 0.8807 - accuracy: 0.8540 - val_loss: 1.0576 - val_accuracy: 0.7935
Epoch 48/100
4/4 [==============================] - 0s 17ms/step - loss: 0.7961 - accuracy: 0.8662 - val_loss: 1.0012 - val_accuracy: 0.7935
Epoch 49/100
4/4 [==============================] - 0s 12ms/step - loss: 0.7398 - accuracy: 0.8637 - val_loss: 0.9482 - val_accuracy: 0.7935
Epoch 50/100
4/4 [==============================] - 0s 16ms/step - loss: 0.6824 - accuracy: 0.8674 - val_loss: 0.8963 - val_accuracy: 0.7935
Epoch 51/100
4/4 [==============================] - 0s 15ms/step - loss: 0.6326 - accuracy: 0.8637 - val_loss: 0.8570 - val_accuracy: 0.7935
Epoch 52/100
4/4 [==============================] - 0s 11ms/step - loss: 0.5927 - accuracy: 0.8686 - val_loss: 0.8306 - val_accuracy: 0.7935
Epoch 53/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5779 - accuracy: 0.8589 - val_loss: 0.8180 - val_accuracy: 0.7935
Epoch 54/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5575 - accuracy: 0.8650 - val_loss: 0.8030 - val_accuracy: 0.7935
Epoch 55/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5446 - accuracy: 0.8698 - val_loss: 0.7855 - val_accuracy: 0.7935
Epoch 56/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5202 - accuracy: 0.8771 - val_loss: 0.7774 - val_accuracy: 0.7935
Epoch 57/100
4/4 [==============================] - 0s 12ms/step - loss: 0.5224 - accuracy: 0.8698 - val_loss: 0.7691 - val_accuracy: 0.7935
Epoch 58/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5007 - accuracy: 0.8662 - val_loss: 0.7513 - val_accuracy: 0.7935
Epoch 59/100
4/4 [==============================] - 0s 22ms/step - loss: 0.5012 - accuracy: 0.8723 - val_loss: 0.7291 - val_accuracy: 0.7935
Epoch 60/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4754 - accuracy: 0.8735 - val_loss: 0.7273 - val_accuracy: 0.7935
Epoch 61/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4885 - accuracy: 0.8504 - val_loss: 0.7235 - val_accuracy: 0.7935
Epoch 62/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4552 - accuracy: 0.8686 - val_loss: 0.7113 - val_accuracy: 0.7935
Epoch 63/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4664 - accuracy: 0.8686 - val_loss: 0.6984 - val_accuracy: 0.7935
Epoch 64/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4501 - accuracy: 0.8698 - val_loss: 0.6939 - val_accuracy: 0.7935
Epoch 65/100
4/4 [==============================] - 0s 19ms/step - loss: 0.4490 - accuracy: 0.8662 - val_loss: 0.6929 - val_accuracy: 0.7935
Epoch 66/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4401 - accuracy: 0.8662 - val_loss: 0.6894 - val_accuracy: 0.7935
Epoch 67/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4276 - accuracy: 0.8674 - val_loss: 0.6783 - val_accuracy: 0.7935
Epoch 68/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4247 - accuracy: 0.8698 - val_loss: 0.6681 - val_accuracy: 0.7935
Epoch 69/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4225 - accuracy: 0.8674 - val_loss: 0.6650 - val_accuracy: 0.7935
Epoch 70/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4162 - accuracy: 0.8637 - val_loss: 0.6639 - val_accuracy: 0.7935
Epoch 71/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4183 - accuracy: 0.8698 - val_loss: 0.6581 - val_accuracy: 0.7935
Epoch 72/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4075 - accuracy: 0.8723 - val_loss: 0.6497 - val_accuracy: 0.7935
Epoch 73/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3986 - accuracy: 0.8771 - val_loss: 0.6437 - val_accuracy: 0.7935
Epoch 74/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4021 - accuracy: 0.8747 - val_loss: 0.6431 - val_accuracy: 0.7935
Epoch 75/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3948 - accuracy: 0.8783 - val_loss: 0.6428 - val_accuracy: 0.7935
Epoch 76/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4060 - accuracy: 0.8637 - val_loss: 0.6391 - val_accuracy: 0.7935
Epoch 77/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3972 - accuracy: 0.8710 - val_loss: 0.6350 - val_accuracy: 0.7935
Epoch 78/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3943 - accuracy: 0.8735 - val_loss: 0.6313 - val_accuracy: 0.7935
Epoch 79/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3982 - accuracy: 0.8674 - val_loss: 0.6318 - val_accuracy: 0.7935
Epoch 80/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3957 - accuracy: 0.8698 - val_loss: 0.6322 - val_accuracy: 0.7935
Epoch 81/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3908 - accuracy: 0.8723 - val_loss: 0.6346 - val_accuracy: 0.7935
Epoch 82/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4001 - accuracy: 0.8662 - val_loss: 0.6241 - val_accuracy: 0.7935
Epoch 83/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3883 - accuracy: 0.8747 - val_loss: 0.6227 - val_accuracy: 0.7935
Epoch 84/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3910 - accuracy: 0.8637 - val_loss: 0.6222 - val_accuracy: 0.7935
Epoch 85/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3909 - accuracy: 0.8613 - val_loss: 0.6257 - val_accuracy: 0.7935
Epoch 86/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3883 - accuracy: 0.8747 - val_loss: 0.6150 - val_accuracy: 0.7935
Epoch 87/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3918 - accuracy: 0.8747 - val_loss: 0.6078 - val_accuracy: 0.7935
Epoch 88/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4011 - accuracy: 0.8650 - val_loss: 0.6054 - val_accuracy: 0.7935
Epoch 89/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3898 - accuracy: 0.8674 - val_loss: 0.6091 - val_accuracy: 0.7935
Epoch 90/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3876 - accuracy: 0.8747 - val_loss: 0.6111 - val_accuracy: 0.7935
Epoch 91/100
4/4 [==============================] - 0s 19ms/step - loss: 0.3861 - accuracy: 0.8686 - val_loss: 0.6035 - val_accuracy: 0.7935
Epoch 92/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3859 - accuracy: 0.8674 - val_loss: 0.5968 - val_accuracy: 0.7935
Epoch 93/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3912 - accuracy: 0.8613 - val_loss: 0.6003 - val_accuracy: 0.7935
Epoch 94/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3877 - accuracy: 0.8650 - val_loss: 0.5952 - val_accuracy: 0.7935
Epoch 95/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3815 - accuracy: 0.8710 - val_loss: 0.5889 - val_accuracy: 0.7935
Epoch 96/100
4/4 [==============================] - 0s 19ms/step - loss: 0.3817 - accuracy: 0.8783 - val_loss: 0.5818 - val_accuracy: 0.7935
Epoch 97/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3870 - accuracy: 0.8650 - val_loss: 0.5835 - val_accuracy: 0.7935
Epoch 98/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3841 - accuracy: 0.8698 - val_loss: 0.5861 - val_accuracy: 0.7935
Epoch 99/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3802 - accuracy: 0.8662 - val_loss: 0.5787 - val_accuracy: 0.7935
Epoch 100/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3819 - accuracy: 0.8674 - val_loss: 0.5776 - val_accuracy: 0.7935
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
4/4 [==============================] - 1s 85ms/step - loss: 16.7850 - accuracy: 0.3589 - val_loss: 15.8544 - val_accuracy: 0.3043
Epoch 2/100
4/4 [==============================] - 0s 12ms/step - loss: 16.1147 - accuracy: 0.3917 - val_loss: 15.2991 - val_accuracy: 0.4565
Epoch 3/100
4/4 [==============================] - 0s 16ms/step - loss: 15.4781 - accuracy: 0.3990 - val_loss: 14.7533 - val_accuracy: 0.5435
Epoch 4/100
4/4 [==============================] - 0s 14ms/step - loss: 14.8374 - accuracy: 0.4635 - val_loss: 14.2145 - val_accuracy: 0.6196
Epoch 5/100
4/4 [==============================] - 0s 16ms/step - loss: 14.2349 - accuracy: 0.4927 - val_loss: 13.6839 - val_accuracy: 0.7391
Epoch 6/100
4/4 [==============================] - 0s 11ms/step - loss: 13.7503 - accuracy: 0.4951 - val_loss: 13.1688 - val_accuracy: 0.7717
Epoch 7/100
4/4 [==============================] - 0s 10ms/step - loss: 13.2269 - accuracy: 0.5219 - val_loss: 12.6636 - val_accuracy: 0.7935
Epoch 8/100
4/4 [==============================] - 0s 17ms/step - loss: 12.6736 - accuracy: 0.5620 - val_loss: 12.1668 - val_accuracy: 0.8370
Epoch 9/100
4/4 [==============================] - 0s 17ms/step - loss: 12.1653 - accuracy: 0.5791 - val_loss: 11.6779 - val_accuracy: 0.8478
Epoch 10/100
4/4 [==============================] - 0s 17ms/step - loss: 11.6460 - accuracy: 0.6022 - val_loss: 11.1974 - val_accuracy: 0.8587
Epoch 11/100
4/4 [==============================] - 0s 12ms/step - loss: 11.2096 - accuracy: 0.5985 - val_loss: 10.7234 - val_accuracy: 0.8370
Epoch 12/100
4/4 [==============================] - 0s 15ms/step - loss: 10.7036 - accuracy: 0.6496 - val_loss: 10.2610 - val_accuracy: 0.8370
Epoch 13/100
4/4 [==============================] - 0s 17ms/step - loss: 10.2431 - accuracy: 0.6448 - val_loss: 9.8114 - val_accuracy: 0.8478
Epoch 14/100
4/4 [==============================] - 0s 19ms/step - loss: 9.7797 - accuracy: 0.6740 - val_loss: 9.3763 - val_accuracy: 0.8261
Epoch 15/100
4/4 [==============================] - 0s 13ms/step - loss: 9.3325 - accuracy: 0.6922 - val_loss: 8.9535 - val_accuracy: 0.8261
Epoch 16/100
4/4 [==============================] - 0s 10ms/step - loss: 8.9286 - accuracy: 0.6922 - val_loss: 8.5399 - val_accuracy: 0.8152
Epoch 17/100
4/4 [==============================] - 0s 17ms/step - loss: 8.5020 - accuracy: 0.7092 - val_loss: 8.1360 - val_accuracy: 0.8152
Epoch 18/100
4/4 [==============================] - 0s 17ms/step - loss: 8.1085 - accuracy: 0.7238 - val_loss: 7.7448 - val_accuracy: 0.8152
Epoch 19/100
4/4 [==============================] - 0s 12ms/step - loss: 7.6893 - accuracy: 0.7506 - val_loss: 7.3622 - val_accuracy: 0.8152
Epoch 20/100
4/4 [==============================] - 0s 11ms/step - loss: 7.2919 - accuracy: 0.7591 - val_loss: 6.9909 - val_accuracy: 0.8152
Epoch 21/100
4/4 [==============================] - 0s 16ms/step - loss: 6.9059 - accuracy: 0.7883 - val_loss: 6.6293 - val_accuracy: 0.8152
Epoch 22/100
4/4 [==============================] - 0s 17ms/step - loss: 6.5489 - accuracy: 0.7725 - val_loss: 6.2766 - val_accuracy: 0.8152
Epoch 23/100
4/4 [==============================] - 0s 17ms/step - loss: 6.1729 - accuracy: 0.8005 - val_loss: 5.9352 - val_accuracy: 0.8152
Epoch 24/100
4/4 [==============================] - 0s 10ms/step - loss: 5.8305 - accuracy: 0.8041 - val_loss: 5.6090 - val_accuracy: 0.8152
Epoch 25/100
4/4 [==============================] - 0s 16ms/step - loss: 5.5261 - accuracy: 0.7895 - val_loss: 5.2933 - val_accuracy: 0.8152
Epoch 26/100
4/4 [==============================] - 0s 16ms/step - loss: 5.1965 - accuracy: 0.8102 - val_loss: 4.9904 - val_accuracy: 0.8152
Epoch 27/100
4/4 [==============================] - 0s 16ms/step - loss: 4.8891 - accuracy: 0.8139 - val_loss: 4.6995 - val_accuracy: 0.8152
Epoch 28/100
4/4 [==============================] - 0s 17ms/step - loss: 4.6126 - accuracy: 0.8017 - val_loss: 4.4239 - val_accuracy: 0.8152
Epoch 29/100
4/4 [==============================] - 0s 16ms/step - loss: 4.3177 - accuracy: 0.8285 - val_loss: 4.1612 - val_accuracy: 0.8152
Epoch 30/100
4/4 [==============================] - 0s 15ms/step - loss: 4.0544 - accuracy: 0.8260 - val_loss: 3.9075 - val_accuracy: 0.8152
Epoch 31/100
4/4 [==============================] - 0s 17ms/step - loss: 3.7688 - accuracy: 0.8370 - val_loss: 3.6617 - val_accuracy: 0.8152
Epoch 32/100
4/4 [==============================] - 0s 16ms/step - loss: 3.5143 - accuracy: 0.8260 - val_loss: 3.4256 - val_accuracy: 0.8152
Epoch 33/100
4/4 [==============================] - 0s 17ms/step - loss: 3.2518 - accuracy: 0.8552 - val_loss: 3.2019 - val_accuracy: 0.8152
Epoch 34/100
4/4 [==============================] - 0s 12ms/step - loss: 3.0358 - accuracy: 0.8637 - val_loss: 2.9840 - val_accuracy: 0.8152
Epoch 35/100
4/4 [==============================] - 0s 12ms/step - loss: 2.7968 - accuracy: 0.8637 - val_loss: 2.7723 - val_accuracy: 0.8152
Epoch 36/100
4/4 [==============================] - 0s 17ms/step - loss: 2.6113 - accuracy: 0.8564 - val_loss: 2.5723 - val_accuracy: 0.8152
Epoch 37/100
4/4 [==============================] - 0s 15ms/step - loss: 2.3767 - accuracy: 0.8723 - val_loss: 2.3774 - val_accuracy: 0.8152
Epoch 38/100
4/4 [==============================] - 0s 11ms/step - loss: 2.1926 - accuracy: 0.8662 - val_loss: 2.1992 - val_accuracy: 0.8152
Epoch 39/100
4/4 [==============================] - 0s 11ms/step - loss: 1.9979 - accuracy: 0.8674 - val_loss: 2.0335 - val_accuracy: 0.8152
Epoch 40/100
4/4 [==============================] - 0s 15ms/step - loss: 1.8245 - accuracy: 0.8601 - val_loss: 1.8783 - val_accuracy: 0.8152
Epoch 41/100
4/4 [==============================] - 0s 16ms/step - loss: 1.6532 - accuracy: 0.8808 - val_loss: 1.7275 - val_accuracy: 0.8152
Epoch 42/100
4/4 [==============================] - 0s 17ms/step - loss: 1.4948 - accuracy: 0.8735 - val_loss: 1.5889 - val_accuracy: 0.8152
Epoch 43/100
4/4 [==============================] - 0s 17ms/step - loss: 1.3685 - accuracy: 0.8650 - val_loss: 1.4613 - val_accuracy: 0.8152
Epoch 44/100
4/4 [==============================] - 0s 16ms/step - loss: 1.2303 - accuracy: 0.8723 - val_loss: 1.3475 - val_accuracy: 0.8152
Epoch 45/100
4/4 [==============================] - 0s 16ms/step - loss: 1.1024 - accuracy: 0.8674 - val_loss: 1.2376 - val_accuracy: 0.8152
Epoch 46/100
4/4 [==============================] - 0s 14ms/step - loss: 0.9939 - accuracy: 0.8698 - val_loss: 1.1413 - val_accuracy: 0.8152
Epoch 47/100
4/4 [==============================] - 0s 16ms/step - loss: 0.9118 - accuracy: 0.8625 - val_loss: 1.0585 - val_accuracy: 0.8152
Epoch 48/100
4/4 [==============================] - 0s 17ms/step - loss: 0.8116 - accuracy: 0.8698 - val_loss: 0.9875 - val_accuracy: 0.8152
Epoch 49/100
4/4 [==============================] - 0s 16ms/step - loss: 0.7379 - accuracy: 0.8686 - val_loss: 0.9236 - val_accuracy: 0.8152
Epoch 50/100
4/4 [==============================] - 0s 18ms/step - loss: 0.6755 - accuracy: 0.8723 - val_loss: 0.8695 - val_accuracy: 0.8152
Epoch 51/100
4/4 [==============================] - 0s 12ms/step - loss: 0.6277 - accuracy: 0.8710 - val_loss: 0.8364 - val_accuracy: 0.8152
Epoch 52/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5964 - accuracy: 0.8747 - val_loss: 0.8133 - val_accuracy: 0.8152
Epoch 53/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5697 - accuracy: 0.8783 - val_loss: 0.7902 - val_accuracy: 0.8152
Epoch 54/100
4/4 [==============================] - 0s 15ms/step - loss: 0.5540 - accuracy: 0.8601 - val_loss: 0.7712 - val_accuracy: 0.8152
Epoch 55/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5311 - accuracy: 0.8735 - val_loss: 0.7620 - val_accuracy: 0.8152
Epoch 56/100
4/4 [==============================] - 0s 18ms/step - loss: 0.5285 - accuracy: 0.8674 - val_loss: 0.7539 - val_accuracy: 0.8152
Epoch 57/100
4/4 [==============================] - 0s 11ms/step - loss: 0.5199 - accuracy: 0.8662 - val_loss: 0.7426 - val_accuracy: 0.8152
Epoch 58/100
4/4 [==============================] - 0s 11ms/step - loss: 0.5016 - accuracy: 0.8601 - val_loss: 0.7261 - val_accuracy: 0.8152
Epoch 59/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4927 - accuracy: 0.8589 - val_loss: 0.7129 - val_accuracy: 0.8152
Epoch 60/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4794 - accuracy: 0.8589 - val_loss: 0.7097 - val_accuracy: 0.8152
Epoch 61/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4868 - accuracy: 0.8613 - val_loss: 0.7023 - val_accuracy: 0.8152
Epoch 62/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4566 - accuracy: 0.8759 - val_loss: 0.6942 - val_accuracy: 0.8152
Epoch 63/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4634 - accuracy: 0.8723 - val_loss: 0.6903 - val_accuracy: 0.8152
Epoch 64/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4505 - accuracy: 0.8735 - val_loss: 0.6817 - val_accuracy: 0.8152
Epoch 65/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4427 - accuracy: 0.8686 - val_loss: 0.6716 - val_accuracy: 0.8152
Epoch 66/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4325 - accuracy: 0.8723 - val_loss: 0.6598 - val_accuracy: 0.8152
Epoch 67/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4292 - accuracy: 0.8698 - val_loss: 0.6584 - val_accuracy: 0.8152
Epoch 68/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4227 - accuracy: 0.8613 - val_loss: 0.6549 - val_accuracy: 0.8152
Epoch 69/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4132 - accuracy: 0.8710 - val_loss: 0.6450 - val_accuracy: 0.8152
Epoch 70/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4026 - accuracy: 0.8832 - val_loss: 0.6427 - val_accuracy: 0.8152
Epoch 71/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4076 - accuracy: 0.8662 - val_loss: 0.6414 - val_accuracy: 0.8152
Epoch 72/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4103 - accuracy: 0.8735 - val_loss: 0.6422 - val_accuracy: 0.8152
Epoch 73/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4064 - accuracy: 0.8723 - val_loss: 0.6373 - val_accuracy: 0.8152
Epoch 74/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4087 - accuracy: 0.8613 - val_loss: 0.6339 - val_accuracy: 0.8152
Epoch 75/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4049 - accuracy: 0.8759 - val_loss: 0.6364 - val_accuracy: 0.8152
Epoch 76/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4077 - accuracy: 0.8674 - val_loss: 0.6435 - val_accuracy: 0.8152
Epoch 77/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4092 - accuracy: 0.8710 - val_loss: 0.6328 - val_accuracy: 0.8152
Epoch 78/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3945 - accuracy: 0.8783 - val_loss: 0.6266 - val_accuracy: 0.8152
Epoch 79/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3982 - accuracy: 0.8723 - val_loss: 0.6291 - val_accuracy: 0.8152
Epoch 80/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3849 - accuracy: 0.8771 - val_loss: 0.6337 - val_accuracy: 0.8152
Epoch 81/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3980 - accuracy: 0.8698 - val_loss: 0.6242 - val_accuracy: 0.8152
Epoch 82/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3935 - accuracy: 0.8735 - val_loss: 0.6186 - val_accuracy: 0.8152
Epoch 83/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3943 - accuracy: 0.8759 - val_loss: 0.6168 - val_accuracy: 0.8152
Epoch 84/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3925 - accuracy: 0.8710 - val_loss: 0.6178 - val_accuracy: 0.8152
Epoch 85/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3906 - accuracy: 0.8662 - val_loss: 0.6109 - val_accuracy: 0.8152
Epoch 86/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3841 - accuracy: 0.8747 - val_loss: 0.6088 - val_accuracy: 0.8152
Epoch 87/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3857 - accuracy: 0.8589 - val_loss: 0.6083 - val_accuracy: 0.8152
Epoch 88/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3788 - accuracy: 0.8771 - val_loss: 0.6024 - val_accuracy: 0.8152
Epoch 89/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3755 - accuracy: 0.8759 - val_loss: 0.5990 - val_accuracy: 0.8152
Epoch 90/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3877 - accuracy: 0.8674 - val_loss: 0.5990 - val_accuracy: 0.8152
Epoch 91/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3865 - accuracy: 0.8698 - val_loss: 0.5953 - val_accuracy: 0.8152
Epoch 92/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3797 - accuracy: 0.8759 - val_loss: 0.5975 - val_accuracy: 0.8152
Epoch 93/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3803 - accuracy: 0.8783 - val_loss: 0.5949 - val_accuracy: 0.8152
Epoch 94/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3836 - accuracy: 0.8796 - val_loss: 0.5924 - val_accuracy: 0.8152
Epoch 95/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3787 - accuracy: 0.8625 - val_loss: 0.5989 - val_accuracy: 0.8152
Epoch 96/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3917 - accuracy: 0.8710 - val_loss: 0.5997 - val_accuracy: 0.8152
Epoch 97/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3802 - accuracy: 0.8735 - val_loss: 0.5982 - val_accuracy: 0.8152
Epoch 98/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3898 - accuracy: 0.8723 - val_loss: 0.5902 - val_accuracy: 0.8152
Epoch 99/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3790 - accuracy: 0.8759 - val_loss: 0.5912 - val_accuracy: 0.8152
Epoch 100/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3826 - accuracy: 0.8735 - val_loss: 0.5978 - val_accuracy: 0.8152
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
4/4 [==============================] - 1s 78ms/step - loss: 16.3309 - accuracy: 0.2762 - val_loss: 15.2051 - val_accuracy: 0.5326
Epoch 2/100
4/4 [==============================] - 0s 12ms/step - loss: 15.6500 - accuracy: 0.3273 - val_loss: 14.6623 - val_accuracy: 0.6413
Epoch 3/100
4/4 [==============================] - 0s 10ms/step - loss: 15.0461 - accuracy: 0.3394 - val_loss: 14.1204 - val_accuracy: 0.7391
Epoch 4/100
4/4 [==============================] - 0s 16ms/step - loss: 14.4186 - accuracy: 0.3796 - val_loss: 13.5933 - val_accuracy: 0.8478
Epoch 5/100
4/4 [==============================] - 0s 16ms/step - loss: 13.8371 - accuracy: 0.4209 - val_loss: 13.0761 - val_accuracy: 0.8804
Epoch 6/100
4/4 [==============================] - 0s 19ms/step - loss: 13.2357 - accuracy: 0.4805 - val_loss: 12.5666 - val_accuracy: 0.8913
Epoch 7/100
4/4 [==============================] - 0s 12ms/step - loss: 12.7365 - accuracy: 0.5024 - val_loss: 12.0686 - val_accuracy: 0.8804
Epoch 8/100
4/4 [==============================] - 0s 11ms/step - loss: 12.1946 - accuracy: 0.5353 - val_loss: 11.5795 - val_accuracy: 0.8587
Epoch 9/100
4/4 [==============================] - 0s 12ms/step - loss: 11.6924 - accuracy: 0.5450 - val_loss: 11.1056 - val_accuracy: 0.8696
Epoch 10/100
4/4 [==============================] - 0s 16ms/step - loss: 11.2078 - accuracy: 0.5912 - val_loss: 10.6404 - val_accuracy: 0.8696
Epoch 11/100
4/4 [==============================] - 0s 18ms/step - loss: 10.7223 - accuracy: 0.6071 - val_loss: 10.1861 - val_accuracy: 0.8696
Epoch 12/100
4/4 [==============================] - 0s 12ms/step - loss: 10.2723 - accuracy: 0.6034 - val_loss: 9.7438 - val_accuracy: 0.8696
Epoch 13/100
4/4 [==============================] - 0s 12ms/step - loss: 9.7965 - accuracy: 0.6569 - val_loss: 9.3086 - val_accuracy: 0.8587
Epoch 14/100
4/4 [==============================] - 0s 17ms/step - loss: 9.3614 - accuracy: 0.6606 - val_loss: 8.8826 - val_accuracy: 0.8587
Epoch 15/100
4/4 [==============================] - 0s 17ms/step - loss: 8.9392 - accuracy: 0.6655 - val_loss: 8.4679 - val_accuracy: 0.8587
Epoch 16/100
4/4 [==============================] - 0s 11ms/step - loss: 8.5316 - accuracy: 0.6764 - val_loss: 8.0696 - val_accuracy: 0.8587
Epoch 17/100
4/4 [==============================] - 0s 16ms/step - loss: 8.1204 - accuracy: 0.6934 - val_loss: 7.6885 - val_accuracy: 0.8587
Epoch 18/100
4/4 [==============================] - 0s 17ms/step - loss: 7.7173 - accuracy: 0.6983 - val_loss: 7.3199 - val_accuracy: 0.8587
Epoch 19/100
4/4 [==============================] - 0s 16ms/step - loss: 7.3479 - accuracy: 0.7433 - val_loss: 6.9548 - val_accuracy: 0.8587
Epoch 20/100
4/4 [==============================] - 0s 17ms/step - loss: 6.9970 - accuracy: 0.7360 - val_loss: 6.6006 - val_accuracy: 0.8587
Epoch 21/100
4/4 [==============================] - 0s 17ms/step - loss: 6.6384 - accuracy: 0.7311 - val_loss: 6.2536 - val_accuracy: 0.8587
Epoch 22/100
4/4 [==============================] - 0s 16ms/step - loss: 6.2389 - accuracy: 0.7762 - val_loss: 5.9149 - val_accuracy: 0.8587
Epoch 23/100
4/4 [==============================] - 0s 16ms/step - loss: 5.9184 - accuracy: 0.7555 - val_loss: 5.5893 - val_accuracy: 0.8587
Epoch 24/100
4/4 [==============================] - 0s 17ms/step - loss: 5.5987 - accuracy: 0.7883 - val_loss: 5.2724 - val_accuracy: 0.8587
Epoch 25/100
4/4 [==============================] - 0s 17ms/step - loss: 5.2891 - accuracy: 0.7847 - val_loss: 4.9689 - val_accuracy: 0.8587
Epoch 26/100
4/4 [==============================] - 0s 15ms/step - loss: 4.9922 - accuracy: 0.8005 - val_loss: 4.6771 - val_accuracy: 0.8587
Epoch 27/100
4/4 [==============================] - 0s 15ms/step - loss: 4.6713 - accuracy: 0.8054 - val_loss: 4.3926 - val_accuracy: 0.8587
Epoch 28/100
4/4 [==============================] - 0s 14ms/step - loss: 4.4071 - accuracy: 0.8139 - val_loss: 4.1171 - val_accuracy: 0.8587
Epoch 29/100
4/4 [==============================] - 0s 12ms/step - loss: 4.1126 - accuracy: 0.8200 - val_loss: 3.8487 - val_accuracy: 0.8587
Epoch 30/100
4/4 [==============================] - 0s 17ms/step - loss: 3.8162 - accuracy: 0.8212 - val_loss: 3.5927 - val_accuracy: 0.8587
Epoch 31/100
4/4 [==============================] - 0s 21ms/step - loss: 3.6203 - accuracy: 0.7920 - val_loss: 3.3471 - val_accuracy: 0.8587
Epoch 32/100
4/4 [==============================] - 0s 16ms/step - loss: 3.3415 - accuracy: 0.8236 - val_loss: 3.1152 - val_accuracy: 0.8587
Epoch 33/100
4/4 [==============================] - 0s 17ms/step - loss: 3.0763 - accuracy: 0.8431 - val_loss: 2.8955 - val_accuracy: 0.8587
Epoch 34/100
4/4 [==============================] - 0s 17ms/step - loss: 2.8679 - accuracy: 0.8418 - val_loss: 2.6882 - val_accuracy: 0.8587
Epoch 35/100
4/4 [==============================] - 0s 15ms/step - loss: 2.6398 - accuracy: 0.8516 - val_loss: 2.4840 - val_accuracy: 0.8587
Epoch 36/100
4/4 [==============================] - 0s 18ms/step - loss: 2.4483 - accuracy: 0.8382 - val_loss: 2.2897 - val_accuracy: 0.8587
Epoch 37/100
4/4 [==============================] - 0s 11ms/step - loss: 2.2279 - accuracy: 0.8431 - val_loss: 2.1113 - val_accuracy: 0.8587
Epoch 38/100
4/4 [==============================] - 0s 16ms/step - loss: 2.0491 - accuracy: 0.8577 - val_loss: 1.9484 - val_accuracy: 0.8587
Epoch 39/100
4/4 [==============================] - 0s 34ms/step - loss: 1.8795 - accuracy: 0.8564 - val_loss: 1.7951 - val_accuracy: 0.8587
Epoch 40/100
4/4 [==============================] - 0s 17ms/step - loss: 1.7143 - accuracy: 0.8625 - val_loss: 1.6549 - val_accuracy: 0.8587
Epoch 41/100
4/4 [==============================] - 0s 18ms/step - loss: 1.5913 - accuracy: 0.8662 - val_loss: 1.5200 - val_accuracy: 0.8587
Epoch 42/100
4/4 [==============================] - 0s 20ms/step - loss: 1.4305 - accuracy: 0.8589 - val_loss: 1.3938 - val_accuracy: 0.8587
Epoch 43/100
4/4 [==============================] - 0s 16ms/step - loss: 1.3148 - accuracy: 0.8637 - val_loss: 1.2759 - val_accuracy: 0.8587
Epoch 44/100
4/4 [==============================] - 0s 13ms/step - loss: 1.1801 - accuracy: 0.8637 - val_loss: 1.1726 - val_accuracy: 0.8587
Epoch 45/100
4/4 [==============================] - 0s 16ms/step - loss: 1.1026 - accuracy: 0.8686 - val_loss: 1.0792 - val_accuracy: 0.8587
Epoch 46/100
4/4 [==============================] - 0s 18ms/step - loss: 0.9931 - accuracy: 0.8613 - val_loss: 0.9887 - val_accuracy: 0.8587
Epoch 47/100
4/4 [==============================] - 0s 14ms/step - loss: 0.9031 - accuracy: 0.8674 - val_loss: 0.9094 - val_accuracy: 0.8587
Epoch 48/100
4/4 [==============================] - 0s 17ms/step - loss: 0.8174 - accuracy: 0.8625 - val_loss: 0.8386 - val_accuracy: 0.8587
Epoch 49/100
4/4 [==============================] - 0s 11ms/step - loss: 0.7394 - accuracy: 0.8637 - val_loss: 0.7777 - val_accuracy: 0.8587
Epoch 50/100
4/4 [==============================] - 0s 15ms/step - loss: 0.7061 - accuracy: 0.8613 - val_loss: 0.7298 - val_accuracy: 0.8587
Epoch 51/100
4/4 [==============================] - 0s 12ms/step - loss: 0.6553 - accuracy: 0.8552 - val_loss: 0.6974 - val_accuracy: 0.8587
Epoch 52/100
4/4 [==============================] - 0s 12ms/step - loss: 0.6125 - accuracy: 0.8723 - val_loss: 0.6713 - val_accuracy: 0.8587
Epoch 53/100
4/4 [==============================] - 0s 9ms/step - loss: 0.5878 - accuracy: 0.8662 - val_loss: 0.6461 - val_accuracy: 0.8587
Epoch 54/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5592 - accuracy: 0.8589 - val_loss: 0.6230 - val_accuracy: 0.8587
Epoch 55/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5391 - accuracy: 0.8589 - val_loss: 0.6061 - val_accuracy: 0.8587
Epoch 56/100
4/4 [==============================] - 0s 18ms/step - loss: 0.5257 - accuracy: 0.8650 - val_loss: 0.5996 - val_accuracy: 0.8587
Epoch 57/100
4/4 [==============================] - 0s 11ms/step - loss: 0.5105 - accuracy: 0.8686 - val_loss: 0.5870 - val_accuracy: 0.8587
Epoch 58/100
4/4 [==============================] - 0s 12ms/step - loss: 0.5158 - accuracy: 0.8504 - val_loss: 0.5816 - val_accuracy: 0.8587
Epoch 59/100
4/4 [==============================] - 0s 15ms/step - loss: 0.5146 - accuracy: 0.8577 - val_loss: 0.5694 - val_accuracy: 0.8587
Epoch 60/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4877 - accuracy: 0.8552 - val_loss: 0.5574 - val_accuracy: 0.8587
Epoch 61/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4715 - accuracy: 0.8625 - val_loss: 0.5491 - val_accuracy: 0.8587
Epoch 62/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4650 - accuracy: 0.8637 - val_loss: 0.5370 - val_accuracy: 0.8587
Epoch 63/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4614 - accuracy: 0.8613 - val_loss: 0.5279 - val_accuracy: 0.8587
Epoch 64/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4530 - accuracy: 0.8589 - val_loss: 0.5196 - val_accuracy: 0.8587
Epoch 65/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4461 - accuracy: 0.8662 - val_loss: 0.5185 - val_accuracy: 0.8587
Epoch 66/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4481 - accuracy: 0.8564 - val_loss: 0.5154 - val_accuracy: 0.8587
Epoch 67/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4317 - accuracy: 0.8650 - val_loss: 0.5061 - val_accuracy: 0.8587
Epoch 68/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4307 - accuracy: 0.8625 - val_loss: 0.4964 - val_accuracy: 0.8587
Epoch 69/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4232 - accuracy: 0.8589 - val_loss: 0.4962 - val_accuracy: 0.8587
Epoch 70/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4342 - accuracy: 0.8613 - val_loss: 0.4928 - val_accuracy: 0.8587
Epoch 71/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4170 - accuracy: 0.8552 - val_loss: 0.4891 - val_accuracy: 0.8587
Epoch 72/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4226 - accuracy: 0.8625 - val_loss: 0.4873 - val_accuracy: 0.8587
Epoch 73/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4236 - accuracy: 0.8577 - val_loss: 0.4854 - val_accuracy: 0.8587
Epoch 74/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4217 - accuracy: 0.8625 - val_loss: 0.4853 - val_accuracy: 0.8587
Epoch 75/100
4/4 [==============================] - 0s 19ms/step - loss: 0.4177 - accuracy: 0.8577 - val_loss: 0.4811 - val_accuracy: 0.8587
Epoch 76/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4203 - accuracy: 0.8528 - val_loss: 0.4715 - val_accuracy: 0.8587
Epoch 77/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4083 - accuracy: 0.8650 - val_loss: 0.4666 - val_accuracy: 0.8587
Epoch 78/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4213 - accuracy: 0.8552 - val_loss: 0.4709 - val_accuracy: 0.8587
Epoch 79/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4100 - accuracy: 0.8650 - val_loss: 0.4791 - val_accuracy: 0.8587
Epoch 80/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4167 - accuracy: 0.8564 - val_loss: 0.4694 - val_accuracy: 0.8587
Epoch 81/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4029 - accuracy: 0.8613 - val_loss: 0.4586 - val_accuracy: 0.8587
Epoch 82/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4133 - accuracy: 0.8577 - val_loss: 0.4582 - val_accuracy: 0.8587
Epoch 83/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4080 - accuracy: 0.8625 - val_loss: 0.4648 - val_accuracy: 0.8587
Epoch 84/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4063 - accuracy: 0.8650 - val_loss: 0.4678 - val_accuracy: 0.8587
Epoch 85/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4129 - accuracy: 0.8601 - val_loss: 0.4587 - val_accuracy: 0.8587
Epoch 86/100
4/4 [==============================] - 0s 19ms/step - loss: 0.4042 - accuracy: 0.8625 - val_loss: 0.4531 - val_accuracy: 0.8587
Epoch 87/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4130 - accuracy: 0.8589 - val_loss: 0.4512 - val_accuracy: 0.8587
Epoch 88/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4105 - accuracy: 0.8613 - val_loss: 0.4551 - val_accuracy: 0.8587
Epoch 89/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4147 - accuracy: 0.8540 - val_loss: 0.4590 - val_accuracy: 0.8587
Epoch 90/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4066 - accuracy: 0.8625 - val_loss: 0.4581 - val_accuracy: 0.8587
Epoch 91/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3986 - accuracy: 0.8625 - val_loss: 0.4485 - val_accuracy: 0.8587
Epoch 92/100
4/4 [==============================] - 0s 27ms/step - loss: 0.3971 - accuracy: 0.8625 - val_loss: 0.4418 - val_accuracy: 0.8587
Epoch 93/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4087 - accuracy: 0.8479 - val_loss: 0.4444 - val_accuracy: 0.8587
Epoch 94/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4013 - accuracy: 0.8613 - val_loss: 0.4462 - val_accuracy: 0.8587
Epoch 95/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3899 - accuracy: 0.8674 - val_loss: 0.4429 - val_accuracy: 0.8587
Epoch 96/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3975 - accuracy: 0.8686 - val_loss: 0.4396 - val_accuracy: 0.8587
Epoch 97/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4016 - accuracy: 0.8552 - val_loss: 0.4362 - val_accuracy: 0.8587
Epoch 98/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3931 - accuracy: 0.8589 - val_loss: 0.4332 - val_accuracy: 0.8587
Epoch 99/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4042 - accuracy: 0.8613 - val_loss: 0.4321 - val_accuracy: 0.8587
Epoch 100/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3998 - accuracy: 0.8540 - val_loss: 0.4406 - val_accuracy: 0.8587
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
4/4 [==============================] - 2s 83ms/step - loss: 16.7783 - accuracy: 0.4301 - val_loss: 16.1047 - val_accuracy: 0.1648
Epoch 2/100
4/4 [==============================] - 0s 15ms/step - loss: 16.0200 - accuracy: 0.4702 - val_loss: 15.4806 - val_accuracy: 0.1648
Epoch 3/100
4/4 [==============================] - 0s 17ms/step - loss: 15.4137 - accuracy: 0.4812 - val_loss: 14.8748 - val_accuracy: 0.1978
Epoch 4/100
4/4 [==============================] - 0s 17ms/step - loss: 14.7689 - accuracy: 0.5115 - val_loss: 14.2819 - val_accuracy: 0.2857
Epoch 5/100
4/4 [==============================] - 0s 14ms/step - loss: 14.2197 - accuracy: 0.5261 - val_loss: 13.7044 - val_accuracy: 0.4176
Epoch 6/100
4/4 [==============================] - 0s 16ms/step - loss: 13.6719 - accuracy: 0.5468 - val_loss: 13.1397 - val_accuracy: 0.5385
Epoch 7/100
4/4 [==============================] - 0s 15ms/step - loss: 13.0964 - accuracy: 0.5662 - val_loss: 12.5939 - val_accuracy: 0.6264
Epoch 8/100
4/4 [==============================] - 0s 17ms/step - loss: 12.5265 - accuracy: 0.5735 - val_loss: 12.0639 - val_accuracy: 0.7143
Epoch 9/100
4/4 [==============================] - 0s 17ms/step - loss: 12.0080 - accuracy: 0.5978 - val_loss: 11.5472 - val_accuracy: 0.7582
Epoch 10/100
4/4 [==============================] - 0s 15ms/step - loss: 11.4495 - accuracy: 0.6160 - val_loss: 11.0482 - val_accuracy: 0.8132
Epoch 11/100
4/4 [==============================] - 0s 15ms/step - loss: 11.0113 - accuracy: 0.6282 - val_loss: 10.5600 - val_accuracy: 0.8132
Epoch 12/100
4/4 [==============================] - 0s 18ms/step - loss: 10.5000 - accuracy: 0.6537 - val_loss: 10.0882 - val_accuracy: 0.8242
Epoch 13/100
4/4 [==============================] - 0s 11ms/step - loss: 10.0635 - accuracy: 0.6561 - val_loss: 9.6329 - val_accuracy: 0.8242
Epoch 14/100
4/4 [==============================] - 0s 12ms/step - loss: 9.5580 - accuracy: 0.6829 - val_loss: 9.1907 - val_accuracy: 0.8242
Epoch 15/100
4/4 [==============================] - 0s 16ms/step - loss: 9.1384 - accuracy: 0.6938 - val_loss: 8.7600 - val_accuracy: 0.8242
Epoch 16/100
4/4 [==============================] - 0s 17ms/step - loss: 8.7383 - accuracy: 0.6950 - val_loss: 8.3400 - val_accuracy: 0.8132
Epoch 17/100
4/4 [==============================] - 0s 13ms/step - loss: 8.3032 - accuracy: 0.7254 - val_loss: 7.9354 - val_accuracy: 0.8352
Epoch 18/100
4/4 [==============================] - 0s 16ms/step - loss: 7.8750 - accuracy: 0.7388 - val_loss: 7.5449 - val_accuracy: 0.8352
Epoch 19/100
4/4 [==============================] - 0s 17ms/step - loss: 7.5014 - accuracy: 0.7400 - val_loss: 7.1675 - val_accuracy: 0.8352
Epoch 20/100
4/4 [==============================] - 0s 16ms/step - loss: 7.1171 - accuracy: 0.7655 - val_loss: 6.7987 - val_accuracy: 0.8352
Epoch 21/100
4/4 [==============================] - 0s 15ms/step - loss: 6.7709 - accuracy: 0.7704 - val_loss: 6.4386 - val_accuracy: 0.8352
Epoch 22/100
4/4 [==============================] - 0s 18ms/step - loss: 6.3620 - accuracy: 0.7886 - val_loss: 6.0928 - val_accuracy: 0.8352
Epoch 23/100
4/4 [==============================] - 0s 14ms/step - loss: 6.0448 - accuracy: 0.7740 - val_loss: 5.7573 - val_accuracy: 0.8352
Epoch 24/100
4/4 [==============================] - 0s 16ms/step - loss: 5.7047 - accuracy: 0.7934 - val_loss: 5.4310 - val_accuracy: 0.8352
Epoch 25/100
4/4 [==============================] - 0s 16ms/step - loss: 5.3759 - accuracy: 0.8007 - val_loss: 5.1168 - val_accuracy: 0.8352
Epoch 26/100
4/4 [==============================] - 0s 12ms/step - loss: 5.0405 - accuracy: 0.8117 - val_loss: 4.8137 - val_accuracy: 0.8352
Epoch 27/100
4/4 [==============================] - 0s 14ms/step - loss: 4.7265 - accuracy: 0.8129 - val_loss: 4.5240 - val_accuracy: 0.8352
Epoch 28/100
4/4 [==============================] - 0s 20ms/step - loss: 4.4586 - accuracy: 0.8153 - val_loss: 4.2452 - val_accuracy: 0.8352
Epoch 29/100
4/4 [==============================] - 0s 15ms/step - loss: 4.1526 - accuracy: 0.8262 - val_loss: 3.9812 - val_accuracy: 0.8352
Epoch 30/100
4/4 [==============================] - 0s 15ms/step - loss: 3.9043 - accuracy: 0.8214 - val_loss: 3.7280 - val_accuracy: 0.8352
Epoch 31/100
4/4 [==============================] - 0s 18ms/step - loss: 3.6337 - accuracy: 0.8372 - val_loss: 3.4844 - val_accuracy: 0.8352
Epoch 32/100
4/4 [==============================] - 0s 14ms/step - loss: 3.4037 - accuracy: 0.8420 - val_loss: 3.2505 - val_accuracy: 0.8352
Epoch 33/100
4/4 [==============================] - 0s 16ms/step - loss: 3.1301 - accuracy: 0.8433 - val_loss: 3.0301 - val_accuracy: 0.8352
Epoch 34/100
4/4 [==============================] - 0s 17ms/step - loss: 2.9345 - accuracy: 0.8238 - val_loss: 2.8145 - val_accuracy: 0.8352
Epoch 35/100
4/4 [==============================] - 0s 13ms/step - loss: 2.7101 - accuracy: 0.8372 - val_loss: 2.6114 - val_accuracy: 0.8352
Epoch 36/100
4/4 [==============================] - 0s 15ms/step - loss: 2.5029 - accuracy: 0.8554 - val_loss: 2.4184 - val_accuracy: 0.8352
Epoch 37/100
4/4 [==============================] - 0s 16ms/step - loss: 2.2981 - accuracy: 0.8591 - val_loss: 2.2406 - val_accuracy: 0.8352
Epoch 38/100
4/4 [==============================] - 0s 16ms/step - loss: 2.1066 - accuracy: 0.8505 - val_loss: 2.0681 - val_accuracy: 0.8352
Epoch 39/100
4/4 [==============================] - 0s 11ms/step - loss: 1.9443 - accuracy: 0.8566 - val_loss: 1.9042 - val_accuracy: 0.8352
Epoch 40/100
4/4 [==============================] - 0s 17ms/step - loss: 1.7470 - accuracy: 0.8663 - val_loss: 1.7460 - val_accuracy: 0.8352
Epoch 41/100
4/4 [==============================] - 0s 14ms/step - loss: 1.6019 - accuracy: 0.8615 - val_loss: 1.5985 - val_accuracy: 0.8352
Epoch 42/100
4/4 [==============================] - 0s 17ms/step - loss: 1.4697 - accuracy: 0.8542 - val_loss: 1.4724 - val_accuracy: 0.8352
Epoch 43/100
4/4 [==============================] - 0s 17ms/step - loss: 1.3361 - accuracy: 0.8542 - val_loss: 1.3532 - val_accuracy: 0.8352
Epoch 44/100
4/4 [==============================] - 0s 16ms/step - loss: 1.2216 - accuracy: 0.8518 - val_loss: 1.2457 - val_accuracy: 0.8352
Epoch 45/100
4/4 [==============================] - 0s 14ms/step - loss: 1.0852 - accuracy: 0.8615 - val_loss: 1.1520 - val_accuracy: 0.8352
Epoch 46/100
4/4 [==============================] - 0s 19ms/step - loss: 0.9736 - accuracy: 0.8688 - val_loss: 1.0611 - val_accuracy: 0.8352
Epoch 47/100
4/4 [==============================] - 0s 12ms/step - loss: 0.8796 - accuracy: 0.8676 - val_loss: 0.9868 - val_accuracy: 0.8352
Epoch 48/100
4/4 [==============================] - 0s 16ms/step - loss: 0.8101 - accuracy: 0.8639 - val_loss: 0.9269 - val_accuracy: 0.8352
Epoch 49/100
4/4 [==============================] - 0s 18ms/step - loss: 0.7500 - accuracy: 0.8591 - val_loss: 0.8712 - val_accuracy: 0.8352
Epoch 50/100
4/4 [==============================] - 0s 17ms/step - loss: 0.6948 - accuracy: 0.8627 - val_loss: 0.8218 - val_accuracy: 0.8352
Epoch 51/100
4/4 [==============================] - 0s 16ms/step - loss: 0.6392 - accuracy: 0.8724 - val_loss: 0.7813 - val_accuracy: 0.8352
Epoch 52/100
4/4 [==============================] - 0s 12ms/step - loss: 0.6050 - accuracy: 0.8663 - val_loss: 0.7573 - val_accuracy: 0.8352
Epoch 53/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5840 - accuracy: 0.8736 - val_loss: 0.7401 - val_accuracy: 0.8352
Epoch 54/100
4/4 [==============================] - 0s 15ms/step - loss: 0.5733 - accuracy: 0.8591 - val_loss: 0.7265 - val_accuracy: 0.8352
Epoch 55/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5575 - accuracy: 0.8566 - val_loss: 0.7020 - val_accuracy: 0.8352
Epoch 56/100
4/4 [==============================] - 0s 15ms/step - loss: 0.5282 - accuracy: 0.8651 - val_loss: 0.6873 - val_accuracy: 0.8352
Epoch 57/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5257 - accuracy: 0.8651 - val_loss: 0.6751 - val_accuracy: 0.8352
Epoch 58/100
4/4 [==============================] - 0s 18ms/step - loss: 0.5081 - accuracy: 0.8651 - val_loss: 0.6645 - val_accuracy: 0.8352
Epoch 59/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4990 - accuracy: 0.8591 - val_loss: 0.6557 - val_accuracy: 0.8352
Epoch 60/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4833 - accuracy: 0.8651 - val_loss: 0.6435 - val_accuracy: 0.8352
Epoch 61/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4762 - accuracy: 0.8724 - val_loss: 0.6326 - val_accuracy: 0.8352
Epoch 62/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4615 - accuracy: 0.8663 - val_loss: 0.6242 - val_accuracy: 0.8352
Epoch 63/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4521 - accuracy: 0.8639 - val_loss: 0.6161 - val_accuracy: 0.8352
Epoch 64/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4450 - accuracy: 0.8627 - val_loss: 0.6018 - val_accuracy: 0.8352
Epoch 65/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4373 - accuracy: 0.8627 - val_loss: 0.5921 - val_accuracy: 0.8352
Epoch 66/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4319 - accuracy: 0.8700 - val_loss: 0.5881 - val_accuracy: 0.8352
Epoch 67/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4297 - accuracy: 0.8566 - val_loss: 0.5920 - val_accuracy: 0.8352
Epoch 68/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4374 - accuracy: 0.8615 - val_loss: 0.5841 - val_accuracy: 0.8352
Epoch 69/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4270 - accuracy: 0.8627 - val_loss: 0.5773 - val_accuracy: 0.8352
Epoch 70/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4338 - accuracy: 0.8639 - val_loss: 0.5770 - val_accuracy: 0.8352
Epoch 71/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4228 - accuracy: 0.8639 - val_loss: 0.5752 - val_accuracy: 0.8352
Epoch 72/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4217 - accuracy: 0.8530 - val_loss: 0.5709 - val_accuracy: 0.8352
Epoch 73/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4094 - accuracy: 0.8663 - val_loss: 0.5660 - val_accuracy: 0.8352
Epoch 74/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4169 - accuracy: 0.8651 - val_loss: 0.5644 - val_accuracy: 0.8352
Epoch 75/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4237 - accuracy: 0.8651 - val_loss: 0.5701 - val_accuracy: 0.8352
Epoch 76/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4107 - accuracy: 0.8676 - val_loss: 0.5677 - val_accuracy: 0.8352
Epoch 77/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4099 - accuracy: 0.8712 - val_loss: 0.5603 - val_accuracy: 0.8352
Epoch 78/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4088 - accuracy: 0.8688 - val_loss: 0.5579 - val_accuracy: 0.8352
Epoch 79/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4051 - accuracy: 0.8700 - val_loss: 0.5502 - val_accuracy: 0.8352
Epoch 80/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3990 - accuracy: 0.8761 - val_loss: 0.5441 - val_accuracy: 0.8352
Epoch 81/100
4/4 [==============================] - 0s 23ms/step - loss: 0.4031 - accuracy: 0.8639 - val_loss: 0.5423 - val_accuracy: 0.8352
Epoch 82/100
4/4 [==============================] - 0s 22ms/step - loss: 0.4041 - accuracy: 0.8736 - val_loss: 0.5410 - val_accuracy: 0.8352
Epoch 83/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3926 - accuracy: 0.8676 - val_loss: 0.5381 - val_accuracy: 0.8352
Epoch 84/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4004 - accuracy: 0.8554 - val_loss: 0.5355 - val_accuracy: 0.8352
Epoch 85/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3972 - accuracy: 0.8676 - val_loss: 0.5324 - val_accuracy: 0.8352
Epoch 86/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3955 - accuracy: 0.8724 - val_loss: 0.5301 - val_accuracy: 0.8352
Epoch 87/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3955 - accuracy: 0.8700 - val_loss: 0.5257 - val_accuracy: 0.8352
Epoch 88/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4005 - accuracy: 0.8615 - val_loss: 0.5237 - val_accuracy: 0.8352
Epoch 89/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3936 - accuracy: 0.8663 - val_loss: 0.5207 - val_accuracy: 0.8352
Epoch 90/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3950 - accuracy: 0.8639 - val_loss: 0.5152 - val_accuracy: 0.8352
Epoch 91/100
4/4 [==============================] - 0s 10ms/step - loss: 0.3902 - accuracy: 0.8712 - val_loss: 0.5124 - val_accuracy: 0.8352
Epoch 92/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3872 - accuracy: 0.8627 - val_loss: 0.5189 - val_accuracy: 0.8352
Epoch 93/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3995 - accuracy: 0.8663 - val_loss: 0.5232 - val_accuracy: 0.8352
Epoch 94/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3976 - accuracy: 0.8700 - val_loss: 0.5241 - val_accuracy: 0.8352
Epoch 95/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3965 - accuracy: 0.8627 - val_loss: 0.5103 - val_accuracy: 0.8352
Epoch 96/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4012 - accuracy: 0.8676 - val_loss: 0.5062 - val_accuracy: 0.8352
Epoch 97/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4019 - accuracy: 0.8651 - val_loss: 0.5121 - val_accuracy: 0.8352
Epoch 98/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3978 - accuracy: 0.8651 - val_loss: 0.5134 - val_accuracy: 0.8352
Epoch 99/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3982 - accuracy: 0.8676 - val_loss: 0.5069 - val_accuracy: 0.8352
Epoch 100/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3927 - accuracy: 0.8736 - val_loss: 0.5021 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
4/4 [==============================] - 1s 87ms/step - loss: 16.7213 - accuracy: 0.2296 - val_loss: 15.5715 - val_accuracy: 0.5824
Epoch 2/100
4/4 [==============================] - 0s 16ms/step - loss: 16.0002 - accuracy: 0.2928 - val_loss: 15.0156 - val_accuracy: 0.7253
Epoch 3/100
4/4 [==============================] - 0s 18ms/step - loss: 15.3321 - accuracy: 0.3293 - val_loss: 14.4758 - val_accuracy: 0.8022
Epoch 4/100
4/4 [==============================] - 0s 16ms/step - loss: 14.7505 - accuracy: 0.3779 - val_loss: 13.9450 - val_accuracy: 0.8132
Epoch 5/100
4/4 [==============================] - 0s 15ms/step - loss: 14.1454 - accuracy: 0.4289 - val_loss: 13.4238 - val_accuracy: 0.8242
Epoch 6/100
4/4 [==============================] - 0s 15ms/step - loss: 13.6482 - accuracy: 0.4666 - val_loss: 12.9060 - val_accuracy: 0.8352
Epoch 7/100
4/4 [==============================] - 0s 16ms/step - loss: 13.0662 - accuracy: 0.5115 - val_loss: 12.4037 - val_accuracy: 0.8462
Epoch 8/100
4/4 [==============================] - 0s 16ms/step - loss: 12.5412 - accuracy: 0.5553 - val_loss: 11.9094 - val_accuracy: 0.8571
Epoch 9/100
4/4 [==============================] - 0s 15ms/step - loss: 11.9971 - accuracy: 0.5869 - val_loss: 11.4241 - val_accuracy: 0.8571
Epoch 10/100
4/4 [==============================] - 0s 16ms/step - loss: 11.5048 - accuracy: 0.6173 - val_loss: 10.9503 - val_accuracy: 0.8462
Epoch 11/100
4/4 [==============================] - 0s 17ms/step - loss: 11.0689 - accuracy: 0.6209 - val_loss: 10.4874 - val_accuracy: 0.8462
Epoch 12/100
4/4 [==============================] - 0s 16ms/step - loss: 10.5867 - accuracy: 0.6367 - val_loss: 10.0301 - val_accuracy: 0.8571
Epoch 13/100
4/4 [==============================] - 0s 15ms/step - loss: 10.1117 - accuracy: 0.6501 - val_loss: 9.5905 - val_accuracy: 0.8681
Epoch 14/100
4/4 [==============================] - 0s 17ms/step - loss: 9.6158 - accuracy: 0.6841 - val_loss: 9.1625 - val_accuracy: 0.8681
Epoch 15/100
4/4 [==============================] - 0s 14ms/step - loss: 9.1639 - accuracy: 0.7023 - val_loss: 8.7479 - val_accuracy: 0.8681
Epoch 16/100
4/4 [==============================] - 0s 14ms/step - loss: 8.7730 - accuracy: 0.7047 - val_loss: 8.3412 - val_accuracy: 0.8681
Epoch 17/100
4/4 [==============================] - 0s 13ms/step - loss: 8.3635 - accuracy: 0.7011 - val_loss: 7.9415 - val_accuracy: 0.8681
Epoch 18/100
4/4 [==============================] - 0s 15ms/step - loss: 7.9662 - accuracy: 0.7217 - val_loss: 7.5512 - val_accuracy: 0.8681
Epoch 19/100
4/4 [==============================] - 0s 16ms/step - loss: 7.5541 - accuracy: 0.7278 - val_loss: 7.1717 - val_accuracy: 0.8681
Epoch 20/100
4/4 [==============================] - 0s 18ms/step - loss: 7.1723 - accuracy: 0.7497 - val_loss: 6.8076 - val_accuracy: 0.8681
Epoch 21/100
4/4 [==============================] - 0s 14ms/step - loss: 6.8169 - accuracy: 0.7424 - val_loss: 6.4533 - val_accuracy: 0.8681
Epoch 22/100
4/4 [==============================] - 0s 14ms/step - loss: 6.4519 - accuracy: 0.7776 - val_loss: 6.1057 - val_accuracy: 0.8681
Epoch 23/100
4/4 [==============================] - 0s 15ms/step - loss: 6.0876 - accuracy: 0.7776 - val_loss: 5.7687 - val_accuracy: 0.8681
Epoch 24/100
4/4 [==============================] - 0s 15ms/step - loss: 5.7491 - accuracy: 0.7874 - val_loss: 5.4408 - val_accuracy: 0.8681
Epoch 25/100
4/4 [==============================] - 0s 15ms/step - loss: 5.4587 - accuracy: 0.7740 - val_loss: 5.1280 - val_accuracy: 0.8681
Epoch 26/100
4/4 [==============================] - 0s 17ms/step - loss: 5.0986 - accuracy: 0.7934 - val_loss: 4.8273 - val_accuracy: 0.8681
Epoch 27/100
4/4 [==============================] - 0s 13ms/step - loss: 4.7975 - accuracy: 0.7886 - val_loss: 4.5399 - val_accuracy: 0.8681
Epoch 28/100
4/4 [==============================] - 0s 14ms/step - loss: 4.4811 - accuracy: 0.8226 - val_loss: 4.2620 - val_accuracy: 0.8681
Epoch 29/100
4/4 [==============================] - 0s 11ms/step - loss: 4.2191 - accuracy: 0.8262 - val_loss: 3.9911 - val_accuracy: 0.8681
Epoch 30/100
4/4 [==============================] - 0s 16ms/step - loss: 3.9395 - accuracy: 0.8384 - val_loss: 3.7282 - val_accuracy: 0.8681
Epoch 31/100
4/4 [==============================] - 0s 15ms/step - loss: 3.6635 - accuracy: 0.8396 - val_loss: 3.4770 - val_accuracy: 0.8681
Epoch 32/100
4/4 [==============================] - 0s 16ms/step - loss: 3.4068 - accuracy: 0.8457 - val_loss: 3.2347 - val_accuracy: 0.8681
Epoch 33/100
4/4 [==============================] - 0s 11ms/step - loss: 3.1672 - accuracy: 0.8396 - val_loss: 2.9987 - val_accuracy: 0.8681
Epoch 34/100
4/4 [==============================] - 0s 17ms/step - loss: 2.9110 - accuracy: 0.8445 - val_loss: 2.7770 - val_accuracy: 0.8681
Epoch 35/100
4/4 [==============================] - 0s 15ms/step - loss: 2.7089 - accuracy: 0.8408 - val_loss: 2.5653 - val_accuracy: 0.8681
Epoch 36/100
4/4 [==============================] - 0s 11ms/step - loss: 2.4802 - accuracy: 0.8591 - val_loss: 2.3600 - val_accuracy: 0.8681
Epoch 37/100
4/4 [==============================] - 0s 16ms/step - loss: 2.2336 - accuracy: 0.8688 - val_loss: 2.1790 - val_accuracy: 0.8681
Epoch 38/100
4/4 [==============================] - 0s 15ms/step - loss: 2.0750 - accuracy: 0.8530 - val_loss: 2.0100 - val_accuracy: 0.8681
Epoch 39/100
4/4 [==============================] - 0s 13ms/step - loss: 1.9138 - accuracy: 0.8663 - val_loss: 1.8484 - val_accuracy: 0.8681
Epoch 40/100
4/4 [==============================] - 0s 16ms/step - loss: 1.7521 - accuracy: 0.8530 - val_loss: 1.6931 - val_accuracy: 0.8681
Epoch 41/100
4/4 [==============================] - 0s 17ms/step - loss: 1.5925 - accuracy: 0.8615 - val_loss: 1.5447 - val_accuracy: 0.8681
Epoch 42/100
4/4 [==============================] - 0s 17ms/step - loss: 1.4537 - accuracy: 0.8603 - val_loss: 1.4165 - val_accuracy: 0.8681
Epoch 43/100
4/4 [==============================] - 0s 12ms/step - loss: 1.3107 - accuracy: 0.8688 - val_loss: 1.2985 - val_accuracy: 0.8681
Epoch 44/100
4/4 [==============================] - 0s 15ms/step - loss: 1.1847 - accuracy: 0.8663 - val_loss: 1.1890 - val_accuracy: 0.8681
Epoch 45/100
4/4 [==============================] - 0s 18ms/step - loss: 1.0777 - accuracy: 0.8700 - val_loss: 1.0867 - val_accuracy: 0.8681
Epoch 46/100
4/4 [==============================] - 0s 11ms/step - loss: 0.9775 - accuracy: 0.8627 - val_loss: 0.9953 - val_accuracy: 0.8681
Epoch 47/100
4/4 [==============================] - 0s 12ms/step - loss: 0.8682 - accuracy: 0.8676 - val_loss: 0.9169 - val_accuracy: 0.8681
Epoch 48/100
4/4 [==============================] - 0s 16ms/step - loss: 0.8061 - accuracy: 0.8603 - val_loss: 0.8520 - val_accuracy: 0.8681
Epoch 49/100
4/4 [==============================] - 0s 14ms/step - loss: 0.7334 - accuracy: 0.8712 - val_loss: 0.7953 - val_accuracy: 0.8681
Epoch 50/100
4/4 [==============================] - 0s 12ms/step - loss: 0.6804 - accuracy: 0.8748 - val_loss: 0.7478 - val_accuracy: 0.8681
Epoch 51/100
4/4 [==============================] - 0s 16ms/step - loss: 0.6316 - accuracy: 0.8785 - val_loss: 0.7079 - val_accuracy: 0.8681
Epoch 52/100
4/4 [==============================] - 0s 17ms/step - loss: 0.6001 - accuracy: 0.8700 - val_loss: 0.6753 - val_accuracy: 0.8681
Epoch 53/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5710 - accuracy: 0.8688 - val_loss: 0.6506 - val_accuracy: 0.8681
Epoch 54/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5451 - accuracy: 0.8651 - val_loss: 0.6308 - val_accuracy: 0.8681
Epoch 55/100
4/4 [==============================] - 0s 18ms/step - loss: 0.5313 - accuracy: 0.8748 - val_loss: 0.6152 - val_accuracy: 0.8681
Epoch 56/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5154 - accuracy: 0.8518 - val_loss: 0.6031 - val_accuracy: 0.8681
Epoch 57/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5022 - accuracy: 0.8542 - val_loss: 0.5941 - val_accuracy: 0.8681
Epoch 58/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4897 - accuracy: 0.8785 - val_loss: 0.5821 - val_accuracy: 0.8681
Epoch 59/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4852 - accuracy: 0.8615 - val_loss: 0.5735 - val_accuracy: 0.8681
Epoch 60/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4729 - accuracy: 0.8639 - val_loss: 0.5640 - val_accuracy: 0.8681
Epoch 61/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4648 - accuracy: 0.8688 - val_loss: 0.5565 - val_accuracy: 0.8681
Epoch 62/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4430 - accuracy: 0.8748 - val_loss: 0.5486 - val_accuracy: 0.8681
Epoch 63/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4474 - accuracy: 0.8676 - val_loss: 0.5381 - val_accuracy: 0.8681
Epoch 64/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4405 - accuracy: 0.8651 - val_loss: 0.5354 - val_accuracy: 0.8681
Epoch 65/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4419 - accuracy: 0.8627 - val_loss: 0.5278 - val_accuracy: 0.8681
Epoch 66/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4425 - accuracy: 0.8615 - val_loss: 0.5221 - val_accuracy: 0.8681
Epoch 67/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4289 - accuracy: 0.8651 - val_loss: 0.5174 - val_accuracy: 0.8681
Epoch 68/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4270 - accuracy: 0.8639 - val_loss: 0.5192 - val_accuracy: 0.8681
Epoch 69/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4337 - accuracy: 0.8542 - val_loss: 0.5160 - val_accuracy: 0.8681
Epoch 70/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4180 - accuracy: 0.8700 - val_loss: 0.5120 - val_accuracy: 0.8681
Epoch 71/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4119 - accuracy: 0.8700 - val_loss: 0.5058 - val_accuracy: 0.8681
Epoch 72/100
4/4 [==============================] - 0s 19ms/step - loss: 0.4139 - accuracy: 0.8688 - val_loss: 0.5034 - val_accuracy: 0.8681
Epoch 73/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4104 - accuracy: 0.8627 - val_loss: 0.5046 - val_accuracy: 0.8681
Epoch 74/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4197 - accuracy: 0.8639 - val_loss: 0.5021 - val_accuracy: 0.8681
Epoch 75/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4156 - accuracy: 0.8724 - val_loss: 0.4969 - val_accuracy: 0.8681
Epoch 76/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4006 - accuracy: 0.8712 - val_loss: 0.5000 - val_accuracy: 0.8681
Epoch 77/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4257 - accuracy: 0.8603 - val_loss: 0.4986 - val_accuracy: 0.8681
Epoch 78/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4026 - accuracy: 0.8676 - val_loss: 0.4950 - val_accuracy: 0.8681
Epoch 79/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3995 - accuracy: 0.8663 - val_loss: 0.4941 - val_accuracy: 0.8681
Epoch 80/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3992 - accuracy: 0.8627 - val_loss: 0.4892 - val_accuracy: 0.8681
Epoch 81/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3929 - accuracy: 0.8736 - val_loss: 0.4863 - val_accuracy: 0.8681
Epoch 82/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3916 - accuracy: 0.8688 - val_loss: 0.4848 - val_accuracy: 0.8681
Epoch 83/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3899 - accuracy: 0.8724 - val_loss: 0.4834 - val_accuracy: 0.8681
Epoch 84/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3960 - accuracy: 0.8651 - val_loss: 0.4837 - val_accuracy: 0.8681
Epoch 85/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3998 - accuracy: 0.8688 - val_loss: 0.4838 - val_accuracy: 0.8681
Epoch 86/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3891 - accuracy: 0.8688 - val_loss: 0.4860 - val_accuracy: 0.8681
Epoch 87/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3996 - accuracy: 0.8639 - val_loss: 0.4831 - val_accuracy: 0.8681
Epoch 88/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3906 - accuracy: 0.8676 - val_loss: 0.4806 - val_accuracy: 0.8681
Epoch 89/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3917 - accuracy: 0.8688 - val_loss: 0.4776 - val_accuracy: 0.8681
Epoch 90/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3938 - accuracy: 0.8736 - val_loss: 0.4762 - val_accuracy: 0.8681
Epoch 91/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3912 - accuracy: 0.8676 - val_loss: 0.4771 - val_accuracy: 0.8681
Epoch 92/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3854 - accuracy: 0.8615 - val_loss: 0.4767 - val_accuracy: 0.8681
Epoch 93/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3894 - accuracy: 0.8724 - val_loss: 0.4744 - val_accuracy: 0.8681
Epoch 94/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3878 - accuracy: 0.8700 - val_loss: 0.4720 - val_accuracy: 0.8681
Epoch 95/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3809 - accuracy: 0.8663 - val_loss: 0.4721 - val_accuracy: 0.8681
Epoch 96/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3840 - accuracy: 0.8712 - val_loss: 0.4704 - val_accuracy: 0.8681
Epoch 97/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3868 - accuracy: 0.8736 - val_loss: 0.4701 - val_accuracy: 0.8681
Epoch 98/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3813 - accuracy: 0.8797 - val_loss: 0.4703 - val_accuracy: 0.8681
Epoch 99/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3880 - accuracy: 0.8676 - val_loss: 0.4705 - val_accuracy: 0.8681
Epoch 100/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3821 - accuracy: 0.8724 - val_loss: 0.4690 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 7ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
4/4 [==============================] - 1s 84ms/step - loss: 16.1646 - accuracy: 0.3791 - val_loss: 15.4499 - val_accuracy: 0.2418
Epoch 2/100
4/4 [==============================] - 0s 13ms/step - loss: 15.4917 - accuracy: 0.4034 - val_loss: 14.8695 - val_accuracy: 0.4176
Epoch 3/100
4/4 [==============================] - 0s 16ms/step - loss: 14.8912 - accuracy: 0.4374 - val_loss: 14.3073 - val_accuracy: 0.6264
Epoch 4/100
4/4 [==============================] - 0s 17ms/step - loss: 14.3105 - accuracy: 0.4836 - val_loss: 13.7550 - val_accuracy: 0.7363
Epoch 5/100
4/4 [==============================] - 0s 16ms/step - loss: 13.7987 - accuracy: 0.5055 - val_loss: 13.2151 - val_accuracy: 0.7802
Epoch 6/100
4/4 [==============================] - 0s 16ms/step - loss: 13.2763 - accuracy: 0.5103 - val_loss: 12.6882 - val_accuracy: 0.8132
Epoch 7/100
4/4 [==============================] - 0s 15ms/step - loss: 12.7051 - accuracy: 0.5456 - val_loss: 12.1787 - val_accuracy: 0.8352
Epoch 8/100
4/4 [==============================] - 0s 16ms/step - loss: 12.1790 - accuracy: 0.5869 - val_loss: 11.6806 - val_accuracy: 0.8352
Epoch 9/100
4/4 [==============================] - 0s 17ms/step - loss: 11.6999 - accuracy: 0.6015 - val_loss: 11.1912 - val_accuracy: 0.8681
Epoch 10/100
4/4 [==============================] - 0s 14ms/step - loss: 11.1882 - accuracy: 0.6221 - val_loss: 10.7114 - val_accuracy: 0.9011
Epoch 11/100
4/4 [==============================] - 0s 15ms/step - loss: 10.7482 - accuracy: 0.6318 - val_loss: 10.2456 - val_accuracy: 0.9121
Epoch 12/100
4/4 [==============================] - 0s 16ms/step - loss: 10.2402 - accuracy: 0.6586 - val_loss: 9.7954 - val_accuracy: 0.8901
Epoch 13/100
4/4 [==============================] - 0s 16ms/step - loss: 9.7685 - accuracy: 0.6768 - val_loss: 9.3538 - val_accuracy: 0.8791
Epoch 14/100
4/4 [==============================] - 0s 14ms/step - loss: 9.3607 - accuracy: 0.6634 - val_loss: 8.9269 - val_accuracy: 0.8901
Epoch 15/100
4/4 [==============================] - 0s 16ms/step - loss: 8.9113 - accuracy: 0.7120 - val_loss: 8.5080 - val_accuracy: 0.9011
Epoch 16/100
4/4 [==============================] - 0s 16ms/step - loss: 8.5221 - accuracy: 0.6902 - val_loss: 8.0962 - val_accuracy: 0.9011
Epoch 17/100
4/4 [==============================] - 0s 18ms/step - loss: 8.1260 - accuracy: 0.7157 - val_loss: 7.6911 - val_accuracy: 0.9011
Epoch 18/100
4/4 [==============================] - 0s 16ms/step - loss: 7.6998 - accuracy: 0.7217 - val_loss: 7.2945 - val_accuracy: 0.9011
Epoch 19/100
4/4 [==============================] - 0s 16ms/step - loss: 7.2851 - accuracy: 0.7606 - val_loss: 6.9106 - val_accuracy: 0.9011
Epoch 20/100
4/4 [==============================] - 0s 17ms/step - loss: 6.9436 - accuracy: 0.7363 - val_loss: 6.5341 - val_accuracy: 0.9011
Epoch 21/100
4/4 [==============================] - 0s 13ms/step - loss: 6.5326 - accuracy: 0.7776 - val_loss: 6.1705 - val_accuracy: 0.9011
Epoch 22/100
4/4 [==============================] - 0s 17ms/step - loss: 6.1890 - accuracy: 0.7704 - val_loss: 5.8233 - val_accuracy: 0.9011
Epoch 23/100
4/4 [==============================] - 0s 13ms/step - loss: 5.8782 - accuracy: 0.7679 - val_loss: 5.4852 - val_accuracy: 0.9011
Epoch 24/100
4/4 [==============================] - 0s 16ms/step - loss: 5.5235 - accuracy: 0.7716 - val_loss: 5.1561 - val_accuracy: 0.9011
Epoch 25/100
4/4 [==============================] - 0s 13ms/step - loss: 5.1865 - accuracy: 0.7971 - val_loss: 4.8420 - val_accuracy: 0.9011
Epoch 26/100
4/4 [==============================] - 0s 13ms/step - loss: 4.8690 - accuracy: 0.7995 - val_loss: 4.5423 - val_accuracy: 0.9011
Epoch 27/100
4/4 [==============================] - 0s 16ms/step - loss: 4.5721 - accuracy: 0.8019 - val_loss: 4.2566 - val_accuracy: 0.9011
Epoch 28/100
4/4 [==============================] - 0s 17ms/step - loss: 4.2681 - accuracy: 0.8287 - val_loss: 3.9776 - val_accuracy: 0.9011
Epoch 29/100
4/4 [==============================] - 0s 13ms/step - loss: 3.9907 - accuracy: 0.8287 - val_loss: 3.7083 - val_accuracy: 0.9011
Epoch 30/100
4/4 [==============================] - 0s 16ms/step - loss: 3.7292 - accuracy: 0.8238 - val_loss: 3.4505 - val_accuracy: 0.9011
Epoch 31/100
4/4 [==============================] - 0s 17ms/step - loss: 3.4643 - accuracy: 0.8445 - val_loss: 3.2065 - val_accuracy: 0.9011
Epoch 32/100
4/4 [==============================] - 0s 17ms/step - loss: 3.2090 - accuracy: 0.8323 - val_loss: 2.9738 - val_accuracy: 0.9011
Epoch 33/100
4/4 [==============================] - 0s 17ms/step - loss: 2.9730 - accuracy: 0.8323 - val_loss: 2.7514 - val_accuracy: 0.9011
Epoch 34/100
4/4 [==============================] - 0s 17ms/step - loss: 2.7412 - accuracy: 0.8578 - val_loss: 2.5386 - val_accuracy: 0.9011
Epoch 35/100
4/4 [==============================] - 0s 16ms/step - loss: 2.5396 - accuracy: 0.8481 - val_loss: 2.3371 - val_accuracy: 0.9011
Epoch 36/100
4/4 [==============================] - 0s 14ms/step - loss: 2.3259 - accuracy: 0.8505 - val_loss: 2.1513 - val_accuracy: 0.9011
Epoch 37/100
4/4 [==============================] - 0s 13ms/step - loss: 2.1299 - accuracy: 0.8493 - val_loss: 1.9757 - val_accuracy: 0.9011
Epoch 38/100
4/4 [==============================] - 0s 14ms/step - loss: 1.9387 - accuracy: 0.8700 - val_loss: 1.8118 - val_accuracy: 0.9011
Epoch 39/100
4/4 [==============================] - 0s 16ms/step - loss: 1.7837 - accuracy: 0.8651 - val_loss: 1.6593 - val_accuracy: 0.9011
Epoch 40/100
4/4 [==============================] - 0s 16ms/step - loss: 1.6307 - accuracy: 0.8627 - val_loss: 1.5094 - val_accuracy: 0.9011
Epoch 41/100
4/4 [==============================] - 0s 16ms/step - loss: 1.4842 - accuracy: 0.8639 - val_loss: 1.3748 - val_accuracy: 0.9011
Epoch 42/100
4/4 [==============================] - 0s 15ms/step - loss: 1.3505 - accuracy: 0.8554 - val_loss: 1.2503 - val_accuracy: 0.9011
Epoch 43/100
4/4 [==============================] - 0s 12ms/step - loss: 1.2217 - accuracy: 0.8676 - val_loss: 1.1342 - val_accuracy: 0.9011
Epoch 44/100
4/4 [==============================] - 0s 15ms/step - loss: 1.1009 - accuracy: 0.8566 - val_loss: 1.0320 - val_accuracy: 0.9011
Epoch 45/100
4/4 [==============================] - 0s 14ms/step - loss: 1.0194 - accuracy: 0.8566 - val_loss: 0.9444 - val_accuracy: 0.9011
Epoch 46/100
4/4 [==============================] - 0s 15ms/step - loss: 0.9137 - accuracy: 0.8639 - val_loss: 0.8612 - val_accuracy: 0.9011
Epoch 47/100
4/4 [==============================] - 0s 14ms/step - loss: 0.8239 - accuracy: 0.8700 - val_loss: 0.7862 - val_accuracy: 0.9011
Epoch 48/100
4/4 [==============================] - 0s 17ms/step - loss: 0.7673 - accuracy: 0.8481 - val_loss: 0.7199 - val_accuracy: 0.9011
Epoch 49/100
4/4 [==============================] - 0s 14ms/step - loss: 0.6800 - accuracy: 0.8639 - val_loss: 0.6662 - val_accuracy: 0.9011
Epoch 50/100
4/4 [==============================] - 0s 16ms/step - loss: 0.6412 - accuracy: 0.8712 - val_loss: 0.6230 - val_accuracy: 0.9011
Epoch 51/100
4/4 [==============================] - 0s 16ms/step - loss: 0.6029 - accuracy: 0.8663 - val_loss: 0.5923 - val_accuracy: 0.9011
Epoch 52/100
4/4 [==============================] - 0s 13ms/step - loss: 0.5773 - accuracy: 0.8591 - val_loss: 0.5724 - val_accuracy: 0.9011
Epoch 53/100
4/4 [==============================] - 0s 18ms/step - loss: 0.5565 - accuracy: 0.8663 - val_loss: 0.5601 - val_accuracy: 0.9011
Epoch 54/100
4/4 [==============================] - 0s 12ms/step - loss: 0.5439 - accuracy: 0.8663 - val_loss: 0.5490 - val_accuracy: 0.9011
Epoch 55/100
4/4 [==============================] - 0s 15ms/step - loss: 0.5296 - accuracy: 0.8615 - val_loss: 0.5387 - val_accuracy: 0.9011
Epoch 56/100
4/4 [==============================] - 0s 18ms/step - loss: 0.5148 - accuracy: 0.8700 - val_loss: 0.5271 - val_accuracy: 0.9011
Epoch 57/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5121 - accuracy: 0.8591 - val_loss: 0.5110 - val_accuracy: 0.9011
Epoch 58/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4874 - accuracy: 0.8724 - val_loss: 0.4990 - val_accuracy: 0.9011
Epoch 59/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4802 - accuracy: 0.8700 - val_loss: 0.4911 - val_accuracy: 0.9011
Epoch 60/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4723 - accuracy: 0.8676 - val_loss: 0.4805 - val_accuracy: 0.9011
Epoch 61/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4620 - accuracy: 0.8748 - val_loss: 0.4710 - val_accuracy: 0.9011
Epoch 62/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4547 - accuracy: 0.8663 - val_loss: 0.4669 - val_accuracy: 0.9011
Epoch 63/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4454 - accuracy: 0.8676 - val_loss: 0.4611 - val_accuracy: 0.9011
Epoch 64/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4426 - accuracy: 0.8651 - val_loss: 0.4544 - val_accuracy: 0.9011
Epoch 65/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4393 - accuracy: 0.8663 - val_loss: 0.4458 - val_accuracy: 0.9011
Epoch 66/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4303 - accuracy: 0.8554 - val_loss: 0.4442 - val_accuracy: 0.9011
Epoch 67/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4426 - accuracy: 0.8578 - val_loss: 0.4369 - val_accuracy: 0.9011
Epoch 68/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4185 - accuracy: 0.8676 - val_loss: 0.4322 - val_accuracy: 0.9011
Epoch 69/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4271 - accuracy: 0.8663 - val_loss: 0.4258 - val_accuracy: 0.9011
Epoch 70/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4262 - accuracy: 0.8651 - val_loss: 0.4268 - val_accuracy: 0.9011
Epoch 71/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4232 - accuracy: 0.8651 - val_loss: 0.4252 - val_accuracy: 0.9011
Epoch 72/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4116 - accuracy: 0.8639 - val_loss: 0.4224 - val_accuracy: 0.9011
Epoch 73/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4129 - accuracy: 0.8603 - val_loss: 0.4177 - val_accuracy: 0.9011
Epoch 74/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4113 - accuracy: 0.8651 - val_loss: 0.4168 - val_accuracy: 0.9011
Epoch 75/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4139 - accuracy: 0.8566 - val_loss: 0.4154 - val_accuracy: 0.9011
Epoch 76/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4103 - accuracy: 0.8688 - val_loss: 0.4132 - val_accuracy: 0.9011
Epoch 77/100
4/4 [==============================] - 0s 19ms/step - loss: 0.4082 - accuracy: 0.8712 - val_loss: 0.4138 - val_accuracy: 0.9011
Epoch 78/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4036 - accuracy: 0.8663 - val_loss: 0.4124 - val_accuracy: 0.9011
Epoch 79/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4005 - accuracy: 0.8676 - val_loss: 0.4098 - val_accuracy: 0.9011
Epoch 80/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4082 - accuracy: 0.8578 - val_loss: 0.4102 - val_accuracy: 0.9011
Epoch 81/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4063 - accuracy: 0.8700 - val_loss: 0.4117 - val_accuracy: 0.9011
Epoch 82/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4010 - accuracy: 0.8700 - val_loss: 0.4078 - val_accuracy: 0.9011
Epoch 83/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4068 - accuracy: 0.8627 - val_loss: 0.4039 - val_accuracy: 0.9011
Epoch 84/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4028 - accuracy: 0.8724 - val_loss: 0.4072 - val_accuracy: 0.9011
Epoch 85/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4026 - accuracy: 0.8712 - val_loss: 0.4103 - val_accuracy: 0.9011
Epoch 86/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4039 - accuracy: 0.8578 - val_loss: 0.4075 - val_accuracy: 0.9011
Epoch 87/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4034 - accuracy: 0.8676 - val_loss: 0.4037 - val_accuracy: 0.9011
Epoch 88/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3936 - accuracy: 0.8736 - val_loss: 0.4038 - val_accuracy: 0.9011
Epoch 89/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3955 - accuracy: 0.8542 - val_loss: 0.4031 - val_accuracy: 0.9011
Epoch 90/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3963 - accuracy: 0.8651 - val_loss: 0.3999 - val_accuracy: 0.9011
Epoch 91/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3893 - accuracy: 0.8773 - val_loss: 0.3965 - val_accuracy: 0.9011
Epoch 92/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3928 - accuracy: 0.8639 - val_loss: 0.3947 - val_accuracy: 0.9011
Epoch 93/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3985 - accuracy: 0.8651 - val_loss: 0.3989 - val_accuracy: 0.9011
Epoch 94/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3924 - accuracy: 0.8676 - val_loss: 0.3949 - val_accuracy: 0.9011
Epoch 95/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3863 - accuracy: 0.8736 - val_loss: 0.3923 - val_accuracy: 0.9011
Epoch 96/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3943 - accuracy: 0.8639 - val_loss: 0.3936 - val_accuracy: 0.9011
Epoch 97/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3955 - accuracy: 0.8724 - val_loss: 0.3901 - val_accuracy: 0.9011
Epoch 98/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3840 - accuracy: 0.8724 - val_loss: 0.3886 - val_accuracy: 0.9011
Epoch 99/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3936 - accuracy: 0.8639 - val_loss: 0.3923 - val_accuracy: 0.9011
Epoch 100/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3958 - accuracy: 0.8639 - val_loss: 0.3940 - val_accuracy: 0.9011
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
4/4 [==============================] - 1s 85ms/step - loss: 16.3386 - accuracy: 0.3013 - val_loss: 15.2465 - val_accuracy: 0.6044
Epoch 2/100
4/4 [==============================] - 0s 14ms/step - loss: 15.7139 - accuracy: 0.3196 - val_loss: 14.7171 - val_accuracy: 0.6593
Epoch 3/100
4/4 [==============================] - 0s 11ms/step - loss: 15.0189 - accuracy: 0.3900 - val_loss: 14.1966 - val_accuracy: 0.7473
Epoch 4/100
4/4 [==============================] - 0s 14ms/step - loss: 14.4518 - accuracy: 0.4423 - val_loss: 13.6789 - val_accuracy: 0.7912
Epoch 5/100
4/4 [==============================] - 0s 16ms/step - loss: 13.7799 - accuracy: 0.4885 - val_loss: 13.1668 - val_accuracy: 0.8022
Epoch 6/100
4/4 [==============================] - 0s 18ms/step - loss: 13.2255 - accuracy: 0.5249 - val_loss: 12.6623 - val_accuracy: 0.8022
Epoch 7/100
4/4 [==============================] - 0s 13ms/step - loss: 12.7281 - accuracy: 0.5565 - val_loss: 12.1699 - val_accuracy: 0.8022
Epoch 8/100
4/4 [==============================] - 0s 15ms/step - loss: 12.1604 - accuracy: 0.6185 - val_loss: 11.6875 - val_accuracy: 0.8022
Epoch 9/100
4/4 [==============================] - 0s 16ms/step - loss: 11.6849 - accuracy: 0.6209 - val_loss: 11.2088 - val_accuracy: 0.8242
Epoch 10/100
4/4 [==============================] - 0s 15ms/step - loss: 11.2251 - accuracy: 0.6258 - val_loss: 10.7389 - val_accuracy: 0.8242
Epoch 11/100
4/4 [==============================] - 0s 17ms/step - loss: 10.7721 - accuracy: 0.6294 - val_loss: 10.2750 - val_accuracy: 0.8242
Epoch 12/100
4/4 [==============================] - 0s 20ms/step - loss: 10.2983 - accuracy: 0.6488 - val_loss: 9.8223 - val_accuracy: 0.8352
Epoch 13/100
4/4 [==============================] - 0s 16ms/step - loss: 9.7802 - accuracy: 0.6889 - val_loss: 9.3780 - val_accuracy: 0.8571
Epoch 14/100
4/4 [==============================] - 0s 13ms/step - loss: 9.3677 - accuracy: 0.6914 - val_loss: 8.9442 - val_accuracy: 0.8571
Epoch 15/100
4/4 [==============================] - 0s 16ms/step - loss: 8.9664 - accuracy: 0.6926 - val_loss: 8.5263 - val_accuracy: 0.8681
Epoch 16/100
4/4 [==============================] - 0s 13ms/step - loss: 8.5153 - accuracy: 0.7132 - val_loss: 8.1259 - val_accuracy: 0.8681
Epoch 17/100
4/4 [==============================] - 0s 17ms/step - loss: 8.0919 - accuracy: 0.7375 - val_loss: 7.7386 - val_accuracy: 0.8681
Epoch 18/100
4/4 [==============================] - 0s 17ms/step - loss: 7.7137 - accuracy: 0.7558 - val_loss: 7.3600 - val_accuracy: 0.8681
Epoch 19/100
4/4 [==============================] - 0s 17ms/step - loss: 7.3362 - accuracy: 0.7570 - val_loss: 6.9966 - val_accuracy: 0.8681
Epoch 20/100
4/4 [==============================] - 0s 16ms/step - loss: 6.9590 - accuracy: 0.7691 - val_loss: 6.6426 - val_accuracy: 0.8681
Epoch 21/100
4/4 [==============================] - 0s 17ms/step - loss: 6.6261 - accuracy: 0.7533 - val_loss: 6.2963 - val_accuracy: 0.8681
Epoch 22/100
4/4 [==============================] - 0s 16ms/step - loss: 6.2691 - accuracy: 0.7716 - val_loss: 5.9591 - val_accuracy: 0.8681
Epoch 23/100
4/4 [==============================] - 0s 14ms/step - loss: 5.9074 - accuracy: 0.7922 - val_loss: 5.6330 - val_accuracy: 0.8681
Epoch 24/100
4/4 [==============================] - 0s 15ms/step - loss: 5.5936 - accuracy: 0.7898 - val_loss: 5.3200 - val_accuracy: 0.8681
Epoch 25/100
4/4 [==============================] - 0s 18ms/step - loss: 5.2681 - accuracy: 0.8141 - val_loss: 5.0182 - val_accuracy: 0.8681
Epoch 26/100
4/4 [==============================] - 0s 16ms/step - loss: 5.0044 - accuracy: 0.7910 - val_loss: 4.7271 - val_accuracy: 0.8681
Epoch 27/100
4/4 [==============================] - 0s 12ms/step - loss: 4.7067 - accuracy: 0.8129 - val_loss: 4.4454 - val_accuracy: 0.8681
Epoch 28/100
4/4 [==============================] - 0s 16ms/step - loss: 4.4135 - accuracy: 0.8177 - val_loss: 4.1689 - val_accuracy: 0.8681
Epoch 29/100
4/4 [==============================] - 0s 17ms/step - loss: 4.0967 - accuracy: 0.8287 - val_loss: 3.9047 - val_accuracy: 0.8681
Epoch 30/100
4/4 [==============================] - 0s 14ms/step - loss: 3.8324 - accuracy: 0.8384 - val_loss: 3.6512 - val_accuracy: 0.8681
Epoch 31/100
4/4 [==============================] - 0s 16ms/step - loss: 3.5861 - accuracy: 0.8348 - val_loss: 3.4058 - val_accuracy: 0.8681
Epoch 32/100
4/4 [==============================] - 0s 16ms/step - loss: 3.3371 - accuracy: 0.8372 - val_loss: 3.1757 - val_accuracy: 0.8681
Epoch 33/100
4/4 [==============================] - 0s 17ms/step - loss: 3.0993 - accuracy: 0.8481 - val_loss: 2.9546 - val_accuracy: 0.8681
Epoch 34/100
4/4 [==============================] - 0s 18ms/step - loss: 2.8918 - accuracy: 0.8420 - val_loss: 2.7461 - val_accuracy: 0.8681
Epoch 35/100
4/4 [==============================] - 0s 19ms/step - loss: 2.6455 - accuracy: 0.8481 - val_loss: 2.5448 - val_accuracy: 0.8681
Epoch 36/100
4/4 [==============================] - 0s 15ms/step - loss: 2.4633 - accuracy: 0.8566 - val_loss: 2.3532 - val_accuracy: 0.8681
Epoch 37/100
4/4 [==============================] - 0s 14ms/step - loss: 2.2672 - accuracy: 0.8578 - val_loss: 2.1715 - val_accuracy: 0.8681
Epoch 38/100
4/4 [==============================] - 0s 13ms/step - loss: 2.0802 - accuracy: 0.8663 - val_loss: 2.0047 - val_accuracy: 0.8681
Epoch 39/100
4/4 [==============================] - 0s 15ms/step - loss: 1.8759 - accuracy: 0.8809 - val_loss: 1.8491 - val_accuracy: 0.8681
Epoch 40/100
4/4 [==============================] - 0s 15ms/step - loss: 1.7373 - accuracy: 0.8785 - val_loss: 1.7040 - val_accuracy: 0.8681
Epoch 41/100
4/4 [==============================] - 0s 16ms/step - loss: 1.5695 - accuracy: 0.8785 - val_loss: 1.5653 - val_accuracy: 0.8681
Epoch 42/100
4/4 [==============================] - 0s 12ms/step - loss: 1.4402 - accuracy: 0.8724 - val_loss: 1.4332 - val_accuracy: 0.8681
Epoch 43/100
4/4 [==============================] - 0s 15ms/step - loss: 1.3186 - accuracy: 0.8603 - val_loss: 1.3096 - val_accuracy: 0.8681
Epoch 44/100
4/4 [==============================] - 0s 21ms/step - loss: 1.1942 - accuracy: 0.8700 - val_loss: 1.1971 - val_accuracy: 0.8681
Epoch 45/100
4/4 [==============================] - 0s 17ms/step - loss: 1.0664 - accuracy: 0.8688 - val_loss: 1.0948 - val_accuracy: 0.8681
Epoch 46/100
4/4 [==============================] - 0s 13ms/step - loss: 0.9554 - accuracy: 0.8773 - val_loss: 1.0025 - val_accuracy: 0.8681
Epoch 47/100
4/4 [==============================] - 0s 12ms/step - loss: 0.8780 - accuracy: 0.8663 - val_loss: 0.9266 - val_accuracy: 0.8681
Epoch 48/100
4/4 [==============================] - 0s 15ms/step - loss: 0.7905 - accuracy: 0.8761 - val_loss: 0.8594 - val_accuracy: 0.8681
Epoch 49/100
4/4 [==============================] - 0s 15ms/step - loss: 0.7174 - accuracy: 0.8748 - val_loss: 0.8031 - val_accuracy: 0.8681
Epoch 50/100
4/4 [==============================] - 0s 11ms/step - loss: 0.6727 - accuracy: 0.8615 - val_loss: 0.7543 - val_accuracy: 0.8681
Epoch 51/100
4/4 [==============================] - 0s 15ms/step - loss: 0.6269 - accuracy: 0.8651 - val_loss: 0.7213 - val_accuracy: 0.8681
Epoch 52/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5960 - accuracy: 0.8663 - val_loss: 0.7001 - val_accuracy: 0.8681
Epoch 53/100
4/4 [==============================] - 0s 12ms/step - loss: 0.5759 - accuracy: 0.8724 - val_loss: 0.6810 - val_accuracy: 0.8681
Epoch 54/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5608 - accuracy: 0.8688 - val_loss: 0.6609 - val_accuracy: 0.8681
Epoch 55/100
4/4 [==============================] - 0s 13ms/step - loss: 0.5345 - accuracy: 0.8712 - val_loss: 0.6391 - val_accuracy: 0.8681
Epoch 56/100
4/4 [==============================] - 0s 12ms/step - loss: 0.5108 - accuracy: 0.8700 - val_loss: 0.6225 - val_accuracy: 0.8681
Epoch 57/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4986 - accuracy: 0.8773 - val_loss: 0.6063 - val_accuracy: 0.8681
Epoch 58/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4766 - accuracy: 0.8724 - val_loss: 0.5949 - val_accuracy: 0.8681
Epoch 59/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4706 - accuracy: 0.8651 - val_loss: 0.5853 - val_accuracy: 0.8681
Epoch 60/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4604 - accuracy: 0.8724 - val_loss: 0.5768 - val_accuracy: 0.8681
Epoch 61/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4502 - accuracy: 0.8773 - val_loss: 0.5662 - val_accuracy: 0.8681
Epoch 62/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4445 - accuracy: 0.8785 - val_loss: 0.5566 - val_accuracy: 0.8681
Epoch 63/100
4/4 [==============================] - 0s 11ms/step - loss: 0.4360 - accuracy: 0.8773 - val_loss: 0.5501 - val_accuracy: 0.8681
Epoch 64/100
4/4 [==============================] - 0s 21ms/step - loss: 0.4364 - accuracy: 0.8627 - val_loss: 0.5468 - val_accuracy: 0.8681
Epoch 65/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4291 - accuracy: 0.8639 - val_loss: 0.5423 - val_accuracy: 0.8681
Epoch 66/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4226 - accuracy: 0.8688 - val_loss: 0.5360 - val_accuracy: 0.8681
Epoch 67/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4116 - accuracy: 0.8724 - val_loss: 0.5297 - val_accuracy: 0.8681
Epoch 68/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4091 - accuracy: 0.8663 - val_loss: 0.5256 - val_accuracy: 0.8681
Epoch 69/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4129 - accuracy: 0.8761 - val_loss: 0.5228 - val_accuracy: 0.8681
Epoch 70/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4094 - accuracy: 0.8676 - val_loss: 0.5187 - val_accuracy: 0.8681
Epoch 71/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3999 - accuracy: 0.8663 - val_loss: 0.5147 - val_accuracy: 0.8681
Epoch 72/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4033 - accuracy: 0.8773 - val_loss: 0.5144 - val_accuracy: 0.8681
Epoch 73/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3967 - accuracy: 0.8736 - val_loss: 0.5131 - val_accuracy: 0.8681
Epoch 74/100
4/4 [==============================] - 0s 10ms/step - loss: 0.3921 - accuracy: 0.8712 - val_loss: 0.5091 - val_accuracy: 0.8681
Epoch 75/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3997 - accuracy: 0.8821 - val_loss: 0.5057 - val_accuracy: 0.8681
Epoch 76/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3904 - accuracy: 0.8712 - val_loss: 0.5027 - val_accuracy: 0.8681
Epoch 77/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3982 - accuracy: 0.8663 - val_loss: 0.5025 - val_accuracy: 0.8681
Epoch 78/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3949 - accuracy: 0.8663 - val_loss: 0.5015 - val_accuracy: 0.8681
Epoch 79/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3958 - accuracy: 0.8700 - val_loss: 0.5009 - val_accuracy: 0.8681
Epoch 80/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3944 - accuracy: 0.8736 - val_loss: 0.5020 - val_accuracy: 0.8681
Epoch 81/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3969 - accuracy: 0.8797 - val_loss: 0.4984 - val_accuracy: 0.8681
Epoch 82/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3881 - accuracy: 0.8785 - val_loss: 0.4973 - val_accuracy: 0.8681
Epoch 83/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3886 - accuracy: 0.8761 - val_loss: 0.4928 - val_accuracy: 0.8681
Epoch 84/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3857 - accuracy: 0.8821 - val_loss: 0.4896 - val_accuracy: 0.8681
Epoch 85/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3909 - accuracy: 0.8663 - val_loss: 0.4879 - val_accuracy: 0.8681
Epoch 86/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3799 - accuracy: 0.8821 - val_loss: 0.4864 - val_accuracy: 0.8681
Epoch 87/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3890 - accuracy: 0.8736 - val_loss: 0.4834 - val_accuracy: 0.8681
Epoch 88/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3879 - accuracy: 0.8688 - val_loss: 0.4816 - val_accuracy: 0.8681
Epoch 89/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3897 - accuracy: 0.8748 - val_loss: 0.4798 - val_accuracy: 0.8681
Epoch 90/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3888 - accuracy: 0.8724 - val_loss: 0.4816 - val_accuracy: 0.8681
Epoch 91/100
4/4 [==============================] - 0s 18ms/step - loss: 0.3833 - accuracy: 0.8688 - val_loss: 0.4828 - val_accuracy: 0.8681
Epoch 92/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3905 - accuracy: 0.8785 - val_loss: 0.4813 - val_accuracy: 0.8681
Epoch 93/100
4/4 [==============================] - 0s 23ms/step - loss: 0.3817 - accuracy: 0.8700 - val_loss: 0.4804 - val_accuracy: 0.8681
Epoch 94/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3911 - accuracy: 0.8736 - val_loss: 0.4765 - val_accuracy: 0.8681
Epoch 95/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3864 - accuracy: 0.8663 - val_loss: 0.4766 - val_accuracy: 0.8681
Epoch 96/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3817 - accuracy: 0.8688 - val_loss: 0.4749 - val_accuracy: 0.8681
Epoch 97/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3788 - accuracy: 0.8712 - val_loss: 0.4736 - val_accuracy: 0.8681
Epoch 98/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3819 - accuracy: 0.8700 - val_loss: 0.4712 - val_accuracy: 0.8681
Epoch 99/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3773 - accuracy: 0.8736 - val_loss: 0.4775 - val_accuracy: 0.8681
Epoch 100/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3891 - accuracy: 0.8663 - val_loss: 0.4792 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
4/4 [==============================] - 1s 92ms/step - loss: 16.9323 - accuracy: 0.4204 - val_loss: 16.0978 - val_accuracy: 0.2308
Epoch 2/100
4/4 [==============================] - 0s 15ms/step - loss: 16.2714 - accuracy: 0.4386 - val_loss: 15.5058 - val_accuracy: 0.2747
Epoch 3/100
4/4 [==============================] - 0s 15ms/step - loss: 15.5412 - accuracy: 0.5103 - val_loss: 14.9286 - val_accuracy: 0.3956
Epoch 4/100
4/4 [==============================] - 0s 16ms/step - loss: 14.9729 - accuracy: 0.5188 - val_loss: 14.3632 - val_accuracy: 0.5385
Epoch 5/100
4/4 [==============================] - 0s 11ms/step - loss: 14.3886 - accuracy: 0.5480 - val_loss: 13.8083 - val_accuracy: 0.6154
Epoch 6/100
4/4 [==============================] - 0s 16ms/step - loss: 13.8839 - accuracy: 0.5626 - val_loss: 13.2668 - val_accuracy: 0.6923
Epoch 7/100
4/4 [==============================] - 0s 13ms/step - loss: 13.3226 - accuracy: 0.5942 - val_loss: 12.7360 - val_accuracy: 0.7473
Epoch 8/100
4/4 [==============================] - 0s 13ms/step - loss: 12.8055 - accuracy: 0.6087 - val_loss: 12.2196 - val_accuracy: 0.8022
Epoch 9/100
4/4 [==============================] - 0s 12ms/step - loss: 12.2376 - accuracy: 0.6233 - val_loss: 11.7199 - val_accuracy: 0.8462
Epoch 10/100
4/4 [==============================] - 0s 15ms/step - loss: 11.8270 - accuracy: 0.6574 - val_loss: 11.2360 - val_accuracy: 0.8791
Epoch 11/100
4/4 [==============================] - 0s 14ms/step - loss: 11.3294 - accuracy: 0.6355 - val_loss: 10.7610 - val_accuracy: 0.9011
Epoch 12/100
4/4 [==============================] - 0s 12ms/step - loss: 10.8282 - accuracy: 0.6549 - val_loss: 10.3001 - val_accuracy: 0.9121
Epoch 13/100
4/4 [==============================] - 0s 16ms/step - loss: 10.3572 - accuracy: 0.6646 - val_loss: 9.8467 - val_accuracy: 0.9121
Epoch 14/100
4/4 [==============================] - 0s 17ms/step - loss: 9.8778 - accuracy: 0.6744 - val_loss: 9.4078 - val_accuracy: 0.9121
Epoch 15/100
4/4 [==============================] - 0s 16ms/step - loss: 9.4745 - accuracy: 0.7047 - val_loss: 8.9822 - val_accuracy: 0.8901
Epoch 16/100
4/4 [==============================] - 0s 16ms/step - loss: 9.0127 - accuracy: 0.7193 - val_loss: 8.5692 - val_accuracy: 0.8791
Epoch 17/100
4/4 [==============================] - 0s 14ms/step - loss: 8.5819 - accuracy: 0.7448 - val_loss: 8.1635 - val_accuracy: 0.8791
Epoch 18/100
4/4 [==============================] - 0s 16ms/step - loss: 8.1866 - accuracy: 0.7375 - val_loss: 7.7699 - val_accuracy: 0.8791
Epoch 19/100
4/4 [==============================] - 0s 17ms/step - loss: 7.7731 - accuracy: 0.7764 - val_loss: 7.3890 - val_accuracy: 0.8901
Epoch 20/100
4/4 [==============================] - 0s 22ms/step - loss: 7.4437 - accuracy: 0.7570 - val_loss: 7.0204 - val_accuracy: 0.8901
Epoch 21/100
4/4 [==============================] - 0s 19ms/step - loss: 7.0570 - accuracy: 0.7618 - val_loss: 6.6562 - val_accuracy: 0.8901
Epoch 22/100
4/4 [==============================] - 0s 15ms/step - loss: 6.7148 - accuracy: 0.7618 - val_loss: 6.2970 - val_accuracy: 0.8901
Epoch 23/100
4/4 [==============================] - 0s 15ms/step - loss: 6.3230 - accuracy: 0.7898 - val_loss: 5.9459 - val_accuracy: 0.8901
Epoch 24/100
4/4 [==============================] - 0s 13ms/step - loss: 6.0017 - accuracy: 0.7849 - val_loss: 5.6158 - val_accuracy: 0.8901
Epoch 25/100
4/4 [==============================] - 0s 17ms/step - loss: 5.6363 - accuracy: 0.8092 - val_loss: 5.3001 - val_accuracy: 0.8901
Epoch 26/100
4/4 [==============================] - 0s 13ms/step - loss: 5.3114 - accuracy: 0.8032 - val_loss: 4.9923 - val_accuracy: 0.8901
Epoch 27/100
4/4 [==============================] - 0s 10ms/step - loss: 5.0362 - accuracy: 0.8104 - val_loss: 4.6996 - val_accuracy: 0.8901
Epoch 28/100
4/4 [==============================] - 0s 17ms/step - loss: 4.7348 - accuracy: 0.7959 - val_loss: 4.4152 - val_accuracy: 0.8901
Epoch 29/100
4/4 [==============================] - 0s 17ms/step - loss: 4.4400 - accuracy: 0.8202 - val_loss: 4.1412 - val_accuracy: 0.8901
Epoch 30/100
4/4 [==============================] - 0s 15ms/step - loss: 4.1607 - accuracy: 0.8165 - val_loss: 3.8737 - val_accuracy: 0.8901
Epoch 31/100
4/4 [==============================] - 0s 12ms/step - loss: 3.8845 - accuracy: 0.8396 - val_loss: 3.6151 - val_accuracy: 0.8901
Epoch 32/100
4/4 [==============================] - 0s 16ms/step - loss: 3.6194 - accuracy: 0.8433 - val_loss: 3.3661 - val_accuracy: 0.8901
Epoch 33/100
4/4 [==============================] - 0s 17ms/step - loss: 3.3526 - accuracy: 0.8518 - val_loss: 3.1307 - val_accuracy: 0.8901
Epoch 34/100
4/4 [==============================] - 0s 12ms/step - loss: 3.1318 - accuracy: 0.8408 - val_loss: 2.9029 - val_accuracy: 0.8901
Epoch 35/100
4/4 [==============================] - 0s 11ms/step - loss: 2.9021 - accuracy: 0.8481 - val_loss: 2.6834 - val_accuracy: 0.8901
Epoch 36/100
4/4 [==============================] - 0s 16ms/step - loss: 2.6512 - accuracy: 0.8663 - val_loss: 2.4747 - val_accuracy: 0.8901
Epoch 37/100
4/4 [==============================] - 0s 15ms/step - loss: 2.4448 - accuracy: 0.8603 - val_loss: 2.2736 - val_accuracy: 0.8901
Epoch 38/100
4/4 [==============================] - 0s 16ms/step - loss: 2.2388 - accuracy: 0.8663 - val_loss: 2.0830 - val_accuracy: 0.8901
Epoch 39/100
4/4 [==============================] - 0s 16ms/step - loss: 2.0482 - accuracy: 0.8578 - val_loss: 1.9102 - val_accuracy: 0.8901
Epoch 40/100
4/4 [==============================] - 0s 17ms/step - loss: 1.8704 - accuracy: 0.8663 - val_loss: 1.7503 - val_accuracy: 0.8901
Epoch 41/100
4/4 [==============================] - 0s 17ms/step - loss: 1.7190 - accuracy: 0.8518 - val_loss: 1.6018 - val_accuracy: 0.8901
Epoch 42/100
4/4 [==============================] - 0s 16ms/step - loss: 1.5524 - accuracy: 0.8676 - val_loss: 1.4678 - val_accuracy: 0.8901
Epoch 43/100
4/4 [==============================] - 0s 15ms/step - loss: 1.4401 - accuracy: 0.8615 - val_loss: 1.3425 - val_accuracy: 0.8901
Epoch 44/100
4/4 [==============================] - 0s 13ms/step - loss: 1.3105 - accuracy: 0.8530 - val_loss: 1.2259 - val_accuracy: 0.8901
Epoch 45/100
4/4 [==============================] - 0s 12ms/step - loss: 1.1785 - accuracy: 0.8591 - val_loss: 1.1192 - val_accuracy: 0.8901
Epoch 46/100
4/4 [==============================] - 0s 15ms/step - loss: 1.0596 - accuracy: 0.8663 - val_loss: 1.0167 - val_accuracy: 0.8901
Epoch 47/100
4/4 [==============================] - 0s 16ms/step - loss: 0.9605 - accuracy: 0.8748 - val_loss: 0.9312 - val_accuracy: 0.8901
Epoch 48/100
4/4 [==============================] - 0s 12ms/step - loss: 0.8734 - accuracy: 0.8615 - val_loss: 0.8605 - val_accuracy: 0.8901
Epoch 49/100
4/4 [==============================] - 0s 15ms/step - loss: 0.8046 - accuracy: 0.8724 - val_loss: 0.7934 - val_accuracy: 0.8901
Epoch 50/100
4/4 [==============================] - 0s 15ms/step - loss: 0.7399 - accuracy: 0.8591 - val_loss: 0.7315 - val_accuracy: 0.8901
Epoch 51/100
4/4 [==============================] - 0s 17ms/step - loss: 0.6916 - accuracy: 0.8663 - val_loss: 0.6862 - val_accuracy: 0.8901
Epoch 52/100
4/4 [==============================] - 0s 16ms/step - loss: 0.6434 - accuracy: 0.8651 - val_loss: 0.6534 - val_accuracy: 0.8901
Epoch 53/100
4/4 [==============================] - 0s 12ms/step - loss: 0.6129 - accuracy: 0.8748 - val_loss: 0.6281 - val_accuracy: 0.8901
Epoch 54/100
4/4 [==============================] - 0s 17ms/step - loss: 0.5921 - accuracy: 0.8627 - val_loss: 0.6046 - val_accuracy: 0.8901
Epoch 55/100
4/4 [==============================] - 0s 13ms/step - loss: 0.5668 - accuracy: 0.8578 - val_loss: 0.5814 - val_accuracy: 0.8901
Epoch 56/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5381 - accuracy: 0.8761 - val_loss: 0.5621 - val_accuracy: 0.8901
Epoch 57/100
4/4 [==============================] - 0s 14ms/step - loss: 0.5260 - accuracy: 0.8603 - val_loss: 0.5500 - val_accuracy: 0.8901
Epoch 58/100
4/4 [==============================] - 0s 12ms/step - loss: 0.5217 - accuracy: 0.8615 - val_loss: 0.5327 - val_accuracy: 0.8901
Epoch 59/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4937 - accuracy: 0.8700 - val_loss: 0.5230 - val_accuracy: 0.8901
Epoch 60/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4932 - accuracy: 0.8724 - val_loss: 0.5129 - val_accuracy: 0.8901
Epoch 61/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4849 - accuracy: 0.8663 - val_loss: 0.5107 - val_accuracy: 0.8901
Epoch 62/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4933 - accuracy: 0.8566 - val_loss: 0.4995 - val_accuracy: 0.8901
Epoch 63/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4748 - accuracy: 0.8591 - val_loss: 0.4922 - val_accuracy: 0.8901
Epoch 64/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4658 - accuracy: 0.8676 - val_loss: 0.4839 - val_accuracy: 0.8901
Epoch 65/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4565 - accuracy: 0.8518 - val_loss: 0.4775 - val_accuracy: 0.8901
Epoch 66/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4342 - accuracy: 0.8773 - val_loss: 0.4715 - val_accuracy: 0.8901
Epoch 67/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4418 - accuracy: 0.8603 - val_loss: 0.4657 - val_accuracy: 0.8901
Epoch 68/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4434 - accuracy: 0.8591 - val_loss: 0.4604 - val_accuracy: 0.8901
Epoch 69/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4276 - accuracy: 0.8639 - val_loss: 0.4585 - val_accuracy: 0.8901
Epoch 70/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4318 - accuracy: 0.8615 - val_loss: 0.4546 - val_accuracy: 0.8901
Epoch 71/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4258 - accuracy: 0.8603 - val_loss: 0.4502 - val_accuracy: 0.8901
Epoch 72/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4289 - accuracy: 0.8578 - val_loss: 0.4455 - val_accuracy: 0.8901
Epoch 73/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4098 - accuracy: 0.8627 - val_loss: 0.4410 - val_accuracy: 0.8901
Epoch 74/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4099 - accuracy: 0.8663 - val_loss: 0.4393 - val_accuracy: 0.8901
Epoch 75/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4064 - accuracy: 0.8724 - val_loss: 0.4361 - val_accuracy: 0.8901
Epoch 76/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4083 - accuracy: 0.8688 - val_loss: 0.4329 - val_accuracy: 0.8901
Epoch 77/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4067 - accuracy: 0.8663 - val_loss: 0.4278 - val_accuracy: 0.8901
Epoch 78/100
4/4 [==============================] - 0s 21ms/step - loss: 0.4051 - accuracy: 0.8700 - val_loss: 0.4227 - val_accuracy: 0.8901
Epoch 79/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4046 - accuracy: 0.8651 - val_loss: 0.4207 - val_accuracy: 0.8901
Epoch 80/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3999 - accuracy: 0.8688 - val_loss: 0.4225 - val_accuracy: 0.8901
Epoch 81/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4024 - accuracy: 0.8566 - val_loss: 0.4234 - val_accuracy: 0.8901
Epoch 82/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4053 - accuracy: 0.8639 - val_loss: 0.4201 - val_accuracy: 0.8901
Epoch 83/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4011 - accuracy: 0.8615 - val_loss: 0.4191 - val_accuracy: 0.8901
Epoch 84/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4059 - accuracy: 0.8566 - val_loss: 0.4176 - val_accuracy: 0.8901
Epoch 85/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4020 - accuracy: 0.8651 - val_loss: 0.4206 - val_accuracy: 0.8901
Epoch 86/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4140 - accuracy: 0.8639 - val_loss: 0.4223 - val_accuracy: 0.8901
Epoch 87/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4031 - accuracy: 0.8542 - val_loss: 0.4171 - val_accuracy: 0.8901
Epoch 88/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3907 - accuracy: 0.8761 - val_loss: 0.4124 - val_accuracy: 0.8901
Epoch 89/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4048 - accuracy: 0.8554 - val_loss: 0.4147 - val_accuracy: 0.8901
Epoch 90/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4075 - accuracy: 0.8615 - val_loss: 0.4134 - val_accuracy: 0.8901
Epoch 91/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3931 - accuracy: 0.8663 - val_loss: 0.4114 - val_accuracy: 0.8901
Epoch 92/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4023 - accuracy: 0.8627 - val_loss: 0.4095 - val_accuracy: 0.8901
Epoch 93/100
4/4 [==============================] - 0s 21ms/step - loss: 0.4002 - accuracy: 0.8627 - val_loss: 0.4095 - val_accuracy: 0.8901
Epoch 94/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3947 - accuracy: 0.8736 - val_loss: 0.4090 - val_accuracy: 0.8901
Epoch 95/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3897 - accuracy: 0.8700 - val_loss: 0.4073 - val_accuracy: 0.8901
Epoch 96/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3954 - accuracy: 0.8603 - val_loss: 0.4038 - val_accuracy: 0.8901
Epoch 97/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3962 - accuracy: 0.8700 - val_loss: 0.4029 - val_accuracy: 0.8901
Epoch 98/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3853 - accuracy: 0.8676 - val_loss: 0.4059 - val_accuracy: 0.8901
Epoch 99/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3902 - accuracy: 0.8627 - val_loss: 0.4064 - val_accuracy: 0.8901
Epoch 100/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4006 - accuracy: 0.8615 - val_loss: 0.4074 - val_accuracy: 0.8901
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 9ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': True}
Batch size: 256
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
4/4 [==============================] - 1s 84ms/step - loss: 16.7603 - accuracy: 0.3293 - val_loss: 15.7399 - val_accuracy: 0.7143
Epoch 2/100
4/4 [==============================] - 0s 16ms/step - loss: 16.1410 - accuracy: 0.3232 - val_loss: 15.1884 - val_accuracy: 0.7802
Epoch 3/100
4/4 [==============================] - 0s 17ms/step - loss: 15.4704 - accuracy: 0.3913 - val_loss: 14.6489 - val_accuracy: 0.7802
Epoch 4/100
4/4 [==============================] - 0s 15ms/step - loss: 14.8683 - accuracy: 0.4131 - val_loss: 14.1202 - val_accuracy: 0.8242
Epoch 5/100
4/4 [==============================] - 0s 15ms/step - loss: 14.3022 - accuracy: 0.4739 - val_loss: 13.6001 - val_accuracy: 0.8242
Epoch 6/100
4/4 [==============================] - 0s 15ms/step - loss: 13.7757 - accuracy: 0.4945 - val_loss: 13.0868 - val_accuracy: 0.8242
Epoch 7/100
4/4 [==============================] - 0s 15ms/step - loss: 13.1859 - accuracy: 0.5334 - val_loss: 12.5798 - val_accuracy: 0.8132
Epoch 8/100
4/4 [==============================] - 0s 16ms/step - loss: 12.7161 - accuracy: 0.5419 - val_loss: 12.0842 - val_accuracy: 0.8242
Epoch 9/100
4/4 [==============================] - 0s 17ms/step - loss: 12.1880 - accuracy: 0.5626 - val_loss: 11.6016 - val_accuracy: 0.8352
Epoch 10/100
4/4 [==============================] - 0s 17ms/step - loss: 11.6925 - accuracy: 0.6112 - val_loss: 11.1290 - val_accuracy: 0.8352
Epoch 11/100
4/4 [==============================] - 0s 17ms/step - loss: 11.1993 - accuracy: 0.6185 - val_loss: 10.6623 - val_accuracy: 0.8352
Epoch 12/100
4/4 [==============================] - 0s 15ms/step - loss: 10.7359 - accuracy: 0.6440 - val_loss: 10.2027 - val_accuracy: 0.8352
Epoch 13/100
4/4 [==============================] - 0s 12ms/step - loss: 10.2589 - accuracy: 0.6488 - val_loss: 9.7514 - val_accuracy: 0.8352
Epoch 14/100
4/4 [==============================] - 0s 17ms/step - loss: 9.7422 - accuracy: 0.6841 - val_loss: 9.3177 - val_accuracy: 0.8462
Epoch 15/100
4/4 [==============================] - 0s 13ms/step - loss: 9.3414 - accuracy: 0.6646 - val_loss: 8.8968 - val_accuracy: 0.8352
Epoch 16/100
4/4 [==============================] - 0s 17ms/step - loss: 8.9122 - accuracy: 0.6926 - val_loss: 8.4829 - val_accuracy: 0.8352
Epoch 17/100
4/4 [==============================] - 0s 12ms/step - loss: 8.4887 - accuracy: 0.7108 - val_loss: 8.0842 - val_accuracy: 0.8352
Epoch 18/100
4/4 [==============================] - 0s 16ms/step - loss: 8.0407 - accuracy: 0.7351 - val_loss: 7.6963 - val_accuracy: 0.8352
Epoch 19/100
4/4 [==============================] - 0s 15ms/step - loss: 7.7249 - accuracy: 0.7096 - val_loss: 7.3134 - val_accuracy: 0.8352
Epoch 20/100
4/4 [==============================] - 0s 15ms/step - loss: 7.2751 - accuracy: 0.7363 - val_loss: 6.9370 - val_accuracy: 0.8352
Epoch 21/100
4/4 [==============================] - 0s 16ms/step - loss: 6.8605 - accuracy: 0.7655 - val_loss: 6.5700 - val_accuracy: 0.8352
Epoch 22/100
4/4 [==============================] - 0s 17ms/step - loss: 6.5679 - accuracy: 0.7497 - val_loss: 6.2175 - val_accuracy: 0.8352
Epoch 23/100
4/4 [==============================] - 0s 12ms/step - loss: 6.1711 - accuracy: 0.7716 - val_loss: 5.8805 - val_accuracy: 0.8352
Epoch 24/100
4/4 [==============================] - 0s 16ms/step - loss: 5.8186 - accuracy: 0.7716 - val_loss: 5.5594 - val_accuracy: 0.8352
Epoch 25/100
4/4 [==============================] - 0s 17ms/step - loss: 5.5047 - accuracy: 0.7886 - val_loss: 5.2442 - val_accuracy: 0.8352
Epoch 26/100
4/4 [==============================] - 0s 16ms/step - loss: 5.1850 - accuracy: 0.8044 - val_loss: 4.9320 - val_accuracy: 0.8352
Epoch 27/100
4/4 [==============================] - 0s 17ms/step - loss: 4.8527 - accuracy: 0.8153 - val_loss: 4.6319 - val_accuracy: 0.8352
Epoch 28/100
4/4 [==============================] - 0s 21ms/step - loss: 4.5688 - accuracy: 0.8056 - val_loss: 4.3478 - val_accuracy: 0.8352
Epoch 29/100
4/4 [==============================] - 0s 17ms/step - loss: 4.2411 - accuracy: 0.8311 - val_loss: 4.0751 - val_accuracy: 0.8352
Epoch 30/100
4/4 [==============================] - 0s 15ms/step - loss: 3.9688 - accuracy: 0.8433 - val_loss: 3.8143 - val_accuracy: 0.8352
Epoch 31/100
4/4 [==============================] - 0s 16ms/step - loss: 3.7123 - accuracy: 0.8311 - val_loss: 3.5614 - val_accuracy: 0.8352
Epoch 32/100
4/4 [==============================] - 0s 14ms/step - loss: 3.4697 - accuracy: 0.8275 - val_loss: 3.3176 - val_accuracy: 0.8352
Epoch 33/100
4/4 [==============================] - 0s 16ms/step - loss: 3.2112 - accuracy: 0.8457 - val_loss: 3.0868 - val_accuracy: 0.8352
Epoch 34/100
4/4 [==============================] - 0s 17ms/step - loss: 2.9772 - accuracy: 0.8275 - val_loss: 2.8707 - val_accuracy: 0.8352
Epoch 35/100
4/4 [==============================] - 0s 19ms/step - loss: 2.7555 - accuracy: 0.8396 - val_loss: 2.6693 - val_accuracy: 0.8352
Epoch 36/100
4/4 [==============================] - 0s 15ms/step - loss: 2.5493 - accuracy: 0.8481 - val_loss: 2.4800 - val_accuracy: 0.8352
Epoch 37/100
4/4 [==============================] - 0s 15ms/step - loss: 2.3151 - accuracy: 0.8676 - val_loss: 2.2975 - val_accuracy: 0.8352
Epoch 38/100
4/4 [==============================] - 0s 13ms/step - loss: 2.1173 - accuracy: 0.8615 - val_loss: 2.1228 - val_accuracy: 0.8352
Epoch 39/100
4/4 [==============================] - 0s 12ms/step - loss: 1.9595 - accuracy: 0.8603 - val_loss: 1.9577 - val_accuracy: 0.8352
Epoch 40/100
4/4 [==============================] - 0s 11ms/step - loss: 1.8002 - accuracy: 0.8505 - val_loss: 1.8012 - val_accuracy: 0.8352
Epoch 41/100
4/4 [==============================] - 0s 15ms/step - loss: 1.6282 - accuracy: 0.8615 - val_loss: 1.6581 - val_accuracy: 0.8352
Epoch 42/100
4/4 [==============================] - 0s 17ms/step - loss: 1.4798 - accuracy: 0.8688 - val_loss: 1.5264 - val_accuracy: 0.8352
Epoch 43/100
4/4 [==============================] - 0s 16ms/step - loss: 1.3377 - accuracy: 0.8615 - val_loss: 1.4076 - val_accuracy: 0.8352
Epoch 44/100
4/4 [==============================] - 0s 14ms/step - loss: 1.2191 - accuracy: 0.8724 - val_loss: 1.3010 - val_accuracy: 0.8352
Epoch 45/100
4/4 [==============================] - 0s 15ms/step - loss: 1.1065 - accuracy: 0.8724 - val_loss: 1.1974 - val_accuracy: 0.8352
Epoch 46/100
4/4 [==============================] - 0s 13ms/step - loss: 0.9988 - accuracy: 0.8700 - val_loss: 1.1052 - val_accuracy: 0.8352
Epoch 47/100
4/4 [==============================] - 0s 14ms/step - loss: 0.9021 - accuracy: 0.8688 - val_loss: 1.0244 - val_accuracy: 0.8352
Epoch 48/100
4/4 [==============================] - 0s 18ms/step - loss: 0.8186 - accuracy: 0.8736 - val_loss: 0.9583 - val_accuracy: 0.8352
Epoch 49/100
4/4 [==============================] - 0s 11ms/step - loss: 0.7482 - accuracy: 0.8870 - val_loss: 0.8938 - val_accuracy: 0.8352
Epoch 50/100
4/4 [==============================] - 0s 15ms/step - loss: 0.6849 - accuracy: 0.8821 - val_loss: 0.8453 - val_accuracy: 0.8352
Epoch 51/100
4/4 [==============================] - 0s 18ms/step - loss: 0.6386 - accuracy: 0.8797 - val_loss: 0.8115 - val_accuracy: 0.8352
Epoch 52/100
4/4 [==============================] - 0s 16ms/step - loss: 0.6056 - accuracy: 0.8663 - val_loss: 0.7796 - val_accuracy: 0.8352
Epoch 53/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5734 - accuracy: 0.8736 - val_loss: 0.7561 - val_accuracy: 0.8352
Epoch 54/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5504 - accuracy: 0.8700 - val_loss: 0.7453 - val_accuracy: 0.8352
Epoch 55/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5343 - accuracy: 0.8846 - val_loss: 0.7333 - val_accuracy: 0.8352
Epoch 56/100
4/4 [==============================] - 0s 16ms/step - loss: 0.5152 - accuracy: 0.8785 - val_loss: 0.7153 - val_accuracy: 0.8352
Epoch 57/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4967 - accuracy: 0.8773 - val_loss: 0.6994 - val_accuracy: 0.8352
Epoch 58/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4858 - accuracy: 0.8724 - val_loss: 0.6818 - val_accuracy: 0.8352
Epoch 59/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4656 - accuracy: 0.8821 - val_loss: 0.6688 - val_accuracy: 0.8352
Epoch 60/100
4/4 [==============================] - 0s 18ms/step - loss: 0.4629 - accuracy: 0.8663 - val_loss: 0.6613 - val_accuracy: 0.8352
Epoch 61/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4583 - accuracy: 0.8676 - val_loss: 0.6572 - val_accuracy: 0.8352
Epoch 62/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4539 - accuracy: 0.8748 - val_loss: 0.6493 - val_accuracy: 0.8352
Epoch 63/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4297 - accuracy: 0.8821 - val_loss: 0.6441 - val_accuracy: 0.8352
Epoch 64/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4331 - accuracy: 0.8651 - val_loss: 0.6353 - val_accuracy: 0.8352
Epoch 65/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4192 - accuracy: 0.8761 - val_loss: 0.6302 - val_accuracy: 0.8352
Epoch 66/100
4/4 [==============================] - 0s 14ms/step - loss: 0.4217 - accuracy: 0.8748 - val_loss: 0.6250 - val_accuracy: 0.8352
Epoch 67/100
4/4 [==============================] - 0s 12ms/step - loss: 0.4107 - accuracy: 0.8809 - val_loss: 0.6237 - val_accuracy: 0.8352
Epoch 68/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4094 - accuracy: 0.8712 - val_loss: 0.6154 - val_accuracy: 0.8352
Epoch 69/100
4/4 [==============================] - 0s 16ms/step - loss: 0.4024 - accuracy: 0.8748 - val_loss: 0.6091 - val_accuracy: 0.8352
Epoch 70/100
4/4 [==============================] - 0s 16ms/step - loss: 0.3990 - accuracy: 0.8724 - val_loss: 0.6074 - val_accuracy: 0.8352
Epoch 71/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4101 - accuracy: 0.8651 - val_loss: 0.6055 - val_accuracy: 0.8352
Epoch 72/100
4/4 [==============================] - 0s 13ms/step - loss: 0.4060 - accuracy: 0.8712 - val_loss: 0.6008 - val_accuracy: 0.8352
Epoch 73/100
4/4 [==============================] - 0s 17ms/step - loss: 0.4023 - accuracy: 0.8712 - val_loss: 0.5972 - val_accuracy: 0.8352
Epoch 74/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3964 - accuracy: 0.8700 - val_loss: 0.5937 - val_accuracy: 0.8352
Epoch 75/100
4/4 [==============================] - 0s 15ms/step - loss: 0.4006 - accuracy: 0.8712 - val_loss: 0.5896 - val_accuracy: 0.8352
Epoch 76/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3900 - accuracy: 0.8748 - val_loss: 0.5861 - val_accuracy: 0.8352
Epoch 77/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3844 - accuracy: 0.8834 - val_loss: 0.5822 - val_accuracy: 0.8352
Epoch 78/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3871 - accuracy: 0.8773 - val_loss: 0.5789 - val_accuracy: 0.8352
Epoch 79/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3776 - accuracy: 0.8748 - val_loss: 0.5819 - val_accuracy: 0.8352
Epoch 80/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3804 - accuracy: 0.8724 - val_loss: 0.5801 - val_accuracy: 0.8352
Epoch 81/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3821 - accuracy: 0.8846 - val_loss: 0.5774 - val_accuracy: 0.8352
Epoch 82/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3854 - accuracy: 0.8700 - val_loss: 0.5707 - val_accuracy: 0.8352
Epoch 83/100
4/4 [==============================] - 0s 17ms/step - loss: 0.3757 - accuracy: 0.8712 - val_loss: 0.5676 - val_accuracy: 0.8352
Epoch 84/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3839 - accuracy: 0.8676 - val_loss: 0.5662 - val_accuracy: 0.8352
Epoch 85/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3752 - accuracy: 0.8761 - val_loss: 0.5674 - val_accuracy: 0.8352
Epoch 86/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3960 - accuracy: 0.8785 - val_loss: 0.5677 - val_accuracy: 0.8352
Epoch 87/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3806 - accuracy: 0.8736 - val_loss: 0.5654 - val_accuracy: 0.8352
Epoch 88/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3913 - accuracy: 0.8700 - val_loss: 0.5628 - val_accuracy: 0.8352
Epoch 89/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3820 - accuracy: 0.8736 - val_loss: 0.5639 - val_accuracy: 0.8352
Epoch 90/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3848 - accuracy: 0.8700 - val_loss: 0.5633 - val_accuracy: 0.8352
Epoch 91/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3864 - accuracy: 0.8676 - val_loss: 0.5607 - val_accuracy: 0.8352
Epoch 92/100
4/4 [==============================] - 0s 12ms/step - loss: 0.3802 - accuracy: 0.8712 - val_loss: 0.5583 - val_accuracy: 0.8352
Epoch 93/100
4/4 [==============================] - 0s 13ms/step - loss: 0.3723 - accuracy: 0.8761 - val_loss: 0.5590 - val_accuracy: 0.8352
Epoch 94/100
4/4 [==============================] - 0s 11ms/step - loss: 0.3780 - accuracy: 0.8797 - val_loss: 0.5551 - val_accuracy: 0.8352
Epoch 95/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3679 - accuracy: 0.8858 - val_loss: 0.5538 - val_accuracy: 0.8352
Epoch 96/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3780 - accuracy: 0.8724 - val_loss: 0.5532 - val_accuracy: 0.8352
Epoch 97/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3816 - accuracy: 0.8663 - val_loss: 0.5588 - val_accuracy: 0.8352
Epoch 98/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3831 - accuracy: 0.8809 - val_loss: 0.5593 - val_accuracy: 0.8352
Epoch 99/100
4/4 [==============================] - 0s 15ms/step - loss: 0.3772 - accuracy: 0.8736 - val_loss: 0.5571 - val_accuracy: 0.8352
Epoch 100/100
4/4 [==============================] - 0s 14ms/step - loss: 0.3722 - accuracy: 0.8748 - val_loss: 0.5518 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 2ms/step
Experiment number: 4
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 215ms/step - loss: 6.6902 - accuracy: 0.5353 - val_loss: 2.9931 - val_accuracy: 0.8370
Epoch 2/100
2/2 [==============================] - 0s 34ms/step - loss: 2.7100 - accuracy: 0.8516 - val_loss: 2.7163 - val_accuracy: 0.8370
Epoch 3/100
2/2 [==============================] - 0s 32ms/step - loss: 2.7639 - accuracy: 0.8516 - val_loss: 2.9681 - val_accuracy: 0.8370
Epoch 4/100
2/2 [==============================] - 0s 54ms/step - loss: 2.7977 - accuracy: 0.8516 - val_loss: 2.3445 - val_accuracy: 0.8370
Epoch 5/100
2/2 [==============================] - 0s 30ms/step - loss: 2.1189 - accuracy: 0.8516 - val_loss: 1.7606 - val_accuracy: 0.8370
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6555 - accuracy: 0.8516 - val_loss: 1.6855 - val_accuracy: 0.8370
Epoch 7/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7099 - accuracy: 0.8516 - val_loss: 1.7528 - val_accuracy: 0.8370
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6760 - accuracy: 0.8516 - val_loss: 1.4854 - val_accuracy: 0.8370
Epoch 9/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3997 - accuracy: 0.8516 - val_loss: 1.4160 - val_accuracy: 0.8370
Epoch 10/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3274 - accuracy: 0.8516 - val_loss: 1.4112 - val_accuracy: 0.8370
Epoch 11/100
2/2 [==============================] - 0s 26ms/step - loss: 1.2825 - accuracy: 0.8516 - val_loss: 1.3056 - val_accuracy: 0.8370
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2032 - accuracy: 0.8504 - val_loss: 1.2199 - val_accuracy: 0.8370
Epoch 13/100
2/2 [==============================] - 0s 34ms/step - loss: 1.1178 - accuracy: 0.8516 - val_loss: 1.1551 - val_accuracy: 0.8370
Epoch 14/100
2/2 [==============================] - 0s 52ms/step - loss: 1.0885 - accuracy: 0.8516 - val_loss: 1.1762 - val_accuracy: 0.8370
Epoch 15/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0957 - accuracy: 0.8540 - val_loss: 1.1198 - val_accuracy: 0.8370
Epoch 16/100
2/2 [==============================] - 0s 34ms/step - loss: 1.0143 - accuracy: 0.8504 - val_loss: 1.0546 - val_accuracy: 0.8370
Epoch 17/100
2/2 [==============================] - 0s 44ms/step - loss: 0.9945 - accuracy: 0.8504 - val_loss: 1.1050 - val_accuracy: 0.8370
Epoch 18/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0246 - accuracy: 0.8516 - val_loss: 1.0033 - val_accuracy: 0.8370
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9511 - accuracy: 0.8504 - val_loss: 0.9919 - val_accuracy: 0.8370
Epoch 20/100
2/2 [==============================] - 0s 30ms/step - loss: 0.9399 - accuracy: 0.8516 - val_loss: 1.0327 - val_accuracy: 0.8370
Epoch 21/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9583 - accuracy: 0.8504 - val_loss: 0.9842 - val_accuracy: 0.8370
Epoch 22/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9370 - accuracy: 0.8516 - val_loss: 0.9911 - val_accuracy: 0.8370
Epoch 23/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9216 - accuracy: 0.8516 - val_loss: 0.9478 - val_accuracy: 0.8370
Epoch 24/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8906 - accuracy: 0.8516 - val_loss: 0.9780 - val_accuracy: 0.8370
Epoch 25/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9421 - accuracy: 0.8443 - val_loss: 0.9862 - val_accuracy: 0.8370
Epoch 26/100
2/2 [==============================] - 0s 27ms/step - loss: 0.9142 - accuracy: 0.8528 - val_loss: 0.9108 - val_accuracy: 0.8370
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8623 - accuracy: 0.8528 - val_loss: 1.0113 - val_accuracy: 0.8261
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9263 - accuracy: 0.8613 - val_loss: 0.9262 - val_accuracy: 0.8370
Epoch 29/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8882 - accuracy: 0.8589 - val_loss: 0.9359 - val_accuracy: 0.8370
Epoch 30/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8959 - accuracy: 0.8552 - val_loss: 0.9419 - val_accuracy: 0.8370
Epoch 31/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8757 - accuracy: 0.8564 - val_loss: 0.9677 - val_accuracy: 0.8370
Epoch 32/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9234 - accuracy: 0.8528 - val_loss: 1.0255 - val_accuracy: 0.8261
Epoch 33/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9557 - accuracy: 0.8552 - val_loss: 0.9746 - val_accuracy: 0.8370
Epoch 34/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8785 - accuracy: 0.8504 - val_loss: 0.9235 - val_accuracy: 0.8261
Epoch 35/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8951 - accuracy: 0.8589 - val_loss: 0.9633 - val_accuracy: 0.8261
Epoch 36/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8896 - accuracy: 0.8528 - val_loss: 0.9175 - val_accuracy: 0.8261
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8580 - accuracy: 0.8491 - val_loss: 0.9629 - val_accuracy: 0.8370
Epoch 38/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8997 - accuracy: 0.8552 - val_loss: 0.9491 - val_accuracy: 0.8370
Epoch 39/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8912 - accuracy: 0.8650 - val_loss: 0.9260 - val_accuracy: 0.8370
Epoch 40/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8824 - accuracy: 0.8479 - val_loss: 0.9177 - val_accuracy: 0.8370
Epoch 41/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8611 - accuracy: 0.8491 - val_loss: 0.9285 - val_accuracy: 0.8370
Epoch 42/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8880 - accuracy: 0.8516 - val_loss: 0.9440 - val_accuracy: 0.8478
Epoch 43/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8890 - accuracy: 0.8589 - val_loss: 0.8728 - val_accuracy: 0.8370
Epoch 44/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8181 - accuracy: 0.8564 - val_loss: 0.9084 - val_accuracy: 0.8370
Epoch 45/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8655 - accuracy: 0.8686 - val_loss: 0.9380 - val_accuracy: 0.8370
Epoch 46/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8959 - accuracy: 0.8577 - val_loss: 0.9385 - val_accuracy: 0.8370
Epoch 47/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8740 - accuracy: 0.8479 - val_loss: 0.9373 - val_accuracy: 0.8370
Epoch 48/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8674 - accuracy: 0.8516 - val_loss: 0.8936 - val_accuracy: 0.8370
Epoch 49/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8446 - accuracy: 0.8516 - val_loss: 0.9281 - val_accuracy: 0.8370
Epoch 50/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8797 - accuracy: 0.8516 - val_loss: 0.9270 - val_accuracy: 0.8370
Epoch 51/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8457 - accuracy: 0.8504 - val_loss: 0.8955 - val_accuracy: 0.8370
Epoch 52/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8538 - accuracy: 0.8516 - val_loss: 0.9303 - val_accuracy: 0.8370
Epoch 53/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8742 - accuracy: 0.8516 - val_loss: 0.9057 - val_accuracy: 0.8370
Epoch 54/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8405 - accuracy: 0.8516 - val_loss: 0.8729 - val_accuracy: 0.8370
Epoch 55/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8243 - accuracy: 0.8516 - val_loss: 0.9241 - val_accuracy: 0.8370
Epoch 56/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8600 - accuracy: 0.8516 - val_loss: 0.9126 - val_accuracy: 0.8370
Epoch 57/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8538 - accuracy: 0.8516 - val_loss: 0.8888 - val_accuracy: 0.8370
Epoch 58/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8256 - accuracy: 0.8516 - val_loss: 0.9214 - val_accuracy: 0.8370
Epoch 59/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8599 - accuracy: 0.8516 - val_loss: 0.9113 - val_accuracy: 0.8370
Epoch 60/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8555 - accuracy: 0.8540 - val_loss: 0.8887 - val_accuracy: 0.8370
Epoch 61/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8269 - accuracy: 0.8516 - val_loss: 0.8552 - val_accuracy: 0.8370
Epoch 62/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8029 - accuracy: 0.8516 - val_loss: 0.8767 - val_accuracy: 0.8370
Epoch 63/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8323 - accuracy: 0.8516 - val_loss: 0.8927 - val_accuracy: 0.8370
Epoch 64/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8344 - accuracy: 0.8516 - val_loss: 0.8998 - val_accuracy: 0.8370
Epoch 65/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8525 - accuracy: 0.8516 - val_loss: 0.9177 - val_accuracy: 0.8370
Epoch 66/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8540 - accuracy: 0.8516 - val_loss: 0.9126 - val_accuracy: 0.8370
Epoch 67/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8589 - accuracy: 0.8516 - val_loss: 0.8996 - val_accuracy: 0.8370
Epoch 68/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8474 - accuracy: 0.8516 - val_loss: 0.8860 - val_accuracy: 0.8370
Epoch 69/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8549 - accuracy: 0.8516 - val_loss: 0.9155 - val_accuracy: 0.8370
Epoch 70/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8779 - accuracy: 0.8516 - val_loss: 0.9299 - val_accuracy: 0.8370
Epoch 71/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8607 - accuracy: 0.8516 - val_loss: 0.9020 - val_accuracy: 0.8370
Epoch 72/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8468 - accuracy: 0.8516 - val_loss: 0.8853 - val_accuracy: 0.8370
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8234 - accuracy: 0.8516 - val_loss: 0.8867 - val_accuracy: 0.8370
Epoch 74/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8365 - accuracy: 0.8516 - val_loss: 0.9181 - val_accuracy: 0.8370
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8945 - accuracy: 0.8516 - val_loss: 0.9085 - val_accuracy: 0.8370
Epoch 76/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8429 - accuracy: 0.8516 - val_loss: 0.9085 - val_accuracy: 0.8370
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8782 - accuracy: 0.8516 - val_loss: 0.9246 - val_accuracy: 0.8370
Epoch 78/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8964 - accuracy: 0.8516 - val_loss: 0.8933 - val_accuracy: 0.8370
Epoch 79/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8343 - accuracy: 0.8516 - val_loss: 0.9332 - val_accuracy: 0.8370
Epoch 80/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8507 - accuracy: 0.8516 - val_loss: 0.9066 - val_accuracy: 0.8370
Epoch 81/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8605 - accuracy: 0.8516 - val_loss: 0.8934 - val_accuracy: 0.8370
Epoch 82/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8467 - accuracy: 0.8516 - val_loss: 0.8934 - val_accuracy: 0.8370
Epoch 83/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8517 - accuracy: 0.8516 - val_loss: 0.9111 - val_accuracy: 0.8370
Epoch 84/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8398 - accuracy: 0.8516 - val_loss: 0.9013 - val_accuracy: 0.8370
Epoch 85/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8472 - accuracy: 0.8516 - val_loss: 0.8882 - val_accuracy: 0.8370
Epoch 86/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8169 - accuracy: 0.8516 - val_loss: 0.8857 - val_accuracy: 0.8370
Epoch 87/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8530 - accuracy: 0.8516 - val_loss: 0.9262 - val_accuracy: 0.8370
Epoch 88/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8764 - accuracy: 0.8552 - val_loss: 0.8632 - val_accuracy: 0.8370
Epoch 89/100
2/2 [==============================] - 0s 55ms/step - loss: 0.8351 - accuracy: 0.8504 - val_loss: 0.8685 - val_accuracy: 0.8370
Epoch 90/100
2/2 [==============================] - 0s 66ms/step - loss: 0.8268 - accuracy: 0.8516 - val_loss: 0.8670 - val_accuracy: 0.8370
Epoch 91/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8351 - accuracy: 0.8516 - val_loss: 0.8822 - val_accuracy: 0.8370
Epoch 92/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8448 - accuracy: 0.8516 - val_loss: 0.8984 - val_accuracy: 0.8370
Epoch 93/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8345 - accuracy: 0.8516 - val_loss: 0.8874 - val_accuracy: 0.8370
Epoch 94/100
2/2 [==============================] - 0s 28ms/step - loss: 0.8492 - accuracy: 0.8516 - val_loss: 0.9168 - val_accuracy: 0.8370
Epoch 95/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8811 - accuracy: 0.8516 - val_loss: 0.9097 - val_accuracy: 0.8370
Epoch 96/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8656 - accuracy: 0.8516 - val_loss: 0.8501 - val_accuracy: 0.8370
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8147 - accuracy: 0.8516 - val_loss: 0.8883 - val_accuracy: 0.8370
Epoch 98/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8618 - accuracy: 0.8516 - val_loss: 0.8861 - val_accuracy: 0.8370
Epoch 99/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8583 - accuracy: 0.8516 - val_loss: 0.8666 - val_accuracy: 0.8370
Epoch 100/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8081 - accuracy: 0.8516 - val_loss: 0.9147 - val_accuracy: 0.8370
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 230ms/step - loss: 6.8412 - accuracy: 0.5243 - val_loss: 3.0947 - val_accuracy: 0.7935
Epoch 2/100
2/2 [==============================] - 0s 37ms/step - loss: 2.6541 - accuracy: 0.8564 - val_loss: 2.7750 - val_accuracy: 0.7935
Epoch 3/100
2/2 [==============================] - 0s 37ms/step - loss: 2.7989 - accuracy: 0.8564 - val_loss: 2.9010 - val_accuracy: 0.7935
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 2.7561 - accuracy: 0.8564 - val_loss: 2.3768 - val_accuracy: 0.7935
Epoch 5/100
2/2 [==============================] - 0s 41ms/step - loss: 2.2023 - accuracy: 0.8564 - val_loss: 1.8513 - val_accuracy: 0.7935
Epoch 6/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7631 - accuracy: 0.8564 - val_loss: 1.7363 - val_accuracy: 0.7935
Epoch 7/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7248 - accuracy: 0.8564 - val_loss: 1.6918 - val_accuracy: 0.7935
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6552 - accuracy: 0.8564 - val_loss: 1.5658 - val_accuracy: 0.7935
Epoch 9/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4819 - accuracy: 0.8564 - val_loss: 1.4214 - val_accuracy: 0.7935
Epoch 10/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3551 - accuracy: 0.8564 - val_loss: 1.3561 - val_accuracy: 0.7935
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2970 - accuracy: 0.8564 - val_loss: 1.2838 - val_accuracy: 0.7935
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2650 - accuracy: 0.8564 - val_loss: 1.1501 - val_accuracy: 0.7935
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1267 - accuracy: 0.8564 - val_loss: 1.0777 - val_accuracy: 0.7935
Epoch 14/100
2/2 [==============================] - 0s 45ms/step - loss: 1.0598 - accuracy: 0.8564 - val_loss: 1.1728 - val_accuracy: 0.7935
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1087 - accuracy: 0.8564 - val_loss: 1.1091 - val_accuracy: 0.7935
Epoch 16/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0393 - accuracy: 0.8564 - val_loss: 1.0123 - val_accuracy: 0.7935
Epoch 17/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9874 - accuracy: 0.8564 - val_loss: 1.0782 - val_accuracy: 0.7935
Epoch 18/100
2/2 [==============================] - 0s 35ms/step - loss: 1.0358 - accuracy: 0.8564 - val_loss: 1.0002 - val_accuracy: 0.7935
Epoch 19/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9548 - accuracy: 0.8564 - val_loss: 0.9381 - val_accuracy: 0.7935
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9277 - accuracy: 0.8564 - val_loss: 0.9845 - val_accuracy: 0.7935
Epoch 21/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9561 - accuracy: 0.8564 - val_loss: 0.9293 - val_accuracy: 0.7935
Epoch 22/100
2/2 [==============================] - 0s 27ms/step - loss: 0.8924 - accuracy: 0.8564 - val_loss: 0.9857 - val_accuracy: 0.7935
Epoch 23/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9172 - accuracy: 0.8564 - val_loss: 0.9352 - val_accuracy: 0.7935
Epoch 24/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9251 - accuracy: 0.8564 - val_loss: 0.9511 - val_accuracy: 0.7935
Epoch 25/100
2/2 [==============================] - 0s 49ms/step - loss: 0.9572 - accuracy: 0.8564 - val_loss: 0.9354 - val_accuracy: 0.7935
Epoch 26/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9070 - accuracy: 0.8564 - val_loss: 0.9595 - val_accuracy: 0.7935
Epoch 27/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9113 - accuracy: 0.8564 - val_loss: 0.9359 - val_accuracy: 0.7935
Epoch 28/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9202 - accuracy: 0.8564 - val_loss: 0.9428 - val_accuracy: 0.7935
Epoch 29/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9085 - accuracy: 0.8564 - val_loss: 0.9522 - val_accuracy: 0.7935
Epoch 30/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9149 - accuracy: 0.8564 - val_loss: 0.9263 - val_accuracy: 0.7935
Epoch 31/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9052 - accuracy: 0.8564 - val_loss: 0.8886 - val_accuracy: 0.7935
Epoch 32/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8886 - accuracy: 0.8564 - val_loss: 0.9192 - val_accuracy: 0.7935
Epoch 33/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8937 - accuracy: 0.8564 - val_loss: 0.8977 - val_accuracy: 0.7935
Epoch 34/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8728 - accuracy: 0.8564 - val_loss: 0.9090 - val_accuracy: 0.7935
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8759 - accuracy: 0.8564 - val_loss: 0.9317 - val_accuracy: 0.7935
Epoch 36/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9015 - accuracy: 0.8564 - val_loss: 0.8779 - val_accuracy: 0.7935
Epoch 37/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8552 - accuracy: 0.8564 - val_loss: 0.8819 - val_accuracy: 0.7935
Epoch 38/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8712 - accuracy: 0.8564 - val_loss: 0.9016 - val_accuracy: 0.7935
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8767 - accuracy: 0.8564 - val_loss: 0.8843 - val_accuracy: 0.7935
Epoch 40/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8695 - accuracy: 0.8564 - val_loss: 0.8517 - val_accuracy: 0.7935
Epoch 41/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8635 - accuracy: 0.8564 - val_loss: 0.8848 - val_accuracy: 0.7935
Epoch 42/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8647 - accuracy: 0.8564 - val_loss: 0.8636 - val_accuracy: 0.7935
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8911 - accuracy: 0.8564 - val_loss: 0.8701 - val_accuracy: 0.7935
Epoch 44/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8519 - accuracy: 0.8564 - val_loss: 0.8918 - val_accuracy: 0.7935
Epoch 45/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8786 - accuracy: 0.8564 - val_loss: 0.8982 - val_accuracy: 0.7935
Epoch 46/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8984 - accuracy: 0.8564 - val_loss: 0.9014 - val_accuracy: 0.7935
Epoch 47/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8819 - accuracy: 0.8552 - val_loss: 0.8918 - val_accuracy: 0.7935
Epoch 48/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8726 - accuracy: 0.8552 - val_loss: 0.9148 - val_accuracy: 0.7935
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8659 - accuracy: 0.8564 - val_loss: 0.8727 - val_accuracy: 0.7935
Epoch 50/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8514 - accuracy: 0.8564 - val_loss: 0.8753 - val_accuracy: 0.7935
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8662 - accuracy: 0.8564 - val_loss: 0.8726 - val_accuracy: 0.7935
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8442 - accuracy: 0.8552 - val_loss: 0.8624 - val_accuracy: 0.7935
Epoch 53/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8588 - accuracy: 0.8564 - val_loss: 0.8490 - val_accuracy: 0.7935
Epoch 54/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8489 - accuracy: 0.8564 - val_loss: 0.8892 - val_accuracy: 0.7935
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8493 - accuracy: 0.8564 - val_loss: 0.8823 - val_accuracy: 0.7935
Epoch 56/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8578 - accuracy: 0.8564 - val_loss: 0.8626 - val_accuracy: 0.7935
Epoch 57/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8384 - accuracy: 0.8564 - val_loss: 0.8627 - val_accuracy: 0.7935
Epoch 58/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8547 - accuracy: 0.8564 - val_loss: 0.8313 - val_accuracy: 0.7935
Epoch 59/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8537 - accuracy: 0.8625 - val_loss: 0.8683 - val_accuracy: 0.7935
Epoch 60/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8873 - accuracy: 0.8552 - val_loss: 0.8944 - val_accuracy: 0.7935
Epoch 61/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8610 - accuracy: 0.8552 - val_loss: 0.8641 - val_accuracy: 0.7935
Epoch 62/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8564 - accuracy: 0.8564 - val_loss: 0.8946 - val_accuracy: 0.7935
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8869 - accuracy: 0.8564 - val_loss: 0.8740 - val_accuracy: 0.7935
Epoch 64/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8644 - accuracy: 0.8564 - val_loss: 0.8952 - val_accuracy: 0.7935
Epoch 65/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8544 - accuracy: 0.8564 - val_loss: 0.8641 - val_accuracy: 0.7935
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8585 - accuracy: 0.8552 - val_loss: 0.9051 - val_accuracy: 0.7935
Epoch 67/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8824 - accuracy: 0.8552 - val_loss: 0.8258 - val_accuracy: 0.7935
Epoch 68/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8675 - accuracy: 0.8589 - val_loss: 0.9097 - val_accuracy: 0.7935
Epoch 69/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8755 - accuracy: 0.8564 - val_loss: 0.9405 - val_accuracy: 0.7935
Epoch 70/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8751 - accuracy: 0.8564 - val_loss: 0.9714 - val_accuracy: 0.7935
Epoch 71/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8499 - accuracy: 0.8564 - val_loss: 0.9339 - val_accuracy: 0.7935
Epoch 72/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8616 - accuracy: 0.8564 - val_loss: 0.9048 - val_accuracy: 0.7935
Epoch 73/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8704 - accuracy: 0.8564 - val_loss: 0.8913 - val_accuracy: 0.7935
Epoch 74/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8429 - accuracy: 0.8564 - val_loss: 0.8710 - val_accuracy: 0.7935
Epoch 75/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8503 - accuracy: 0.8564 - val_loss: 0.8515 - val_accuracy: 0.7935
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8265 - accuracy: 0.8564 - val_loss: 0.8765 - val_accuracy: 0.7935
Epoch 77/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8428 - accuracy: 0.8564 - val_loss: 0.8797 - val_accuracy: 0.7935
Epoch 78/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8704 - accuracy: 0.8564 - val_loss: 0.8297 - val_accuracy: 0.7935
Epoch 79/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8342 - accuracy: 0.8564 - val_loss: 0.8333 - val_accuracy: 0.7935
Epoch 80/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8264 - accuracy: 0.8564 - val_loss: 0.8892 - val_accuracy: 0.7935
Epoch 81/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8647 - accuracy: 0.8564 - val_loss: 0.8933 - val_accuracy: 0.7935
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8335 - accuracy: 0.8564 - val_loss: 0.8091 - val_accuracy: 0.7935
Epoch 83/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8254 - accuracy: 0.8564 - val_loss: 0.8705 - val_accuracy: 0.7935
Epoch 84/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8472 - accuracy: 0.8564 - val_loss: 0.8496 - val_accuracy: 0.7935
Epoch 85/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8416 - accuracy: 0.8564 - val_loss: 0.8458 - val_accuracy: 0.7935
Epoch 86/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8323 - accuracy: 0.8564 - val_loss: 0.8707 - val_accuracy: 0.7935
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8403 - accuracy: 0.8564 - val_loss: 0.8828 - val_accuracy: 0.7935
Epoch 88/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8549 - accuracy: 0.8564 - val_loss: 0.8207 - val_accuracy: 0.7935
Epoch 89/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8225 - accuracy: 0.8564 - val_loss: 0.8788 - val_accuracy: 0.7935
Epoch 90/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8689 - accuracy: 0.8564 - val_loss: 0.9117 - val_accuracy: 0.7935
Epoch 91/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8581 - accuracy: 0.8564 - val_loss: 0.8485 - val_accuracy: 0.7935
Epoch 92/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8227 - accuracy: 0.8564 - val_loss: 0.9075 - val_accuracy: 0.7935
Epoch 93/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8684 - accuracy: 0.8564 - val_loss: 0.8881 - val_accuracy: 0.7935
Epoch 94/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8317 - accuracy: 0.8564 - val_loss: 0.8442 - val_accuracy: 0.7935
Epoch 95/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8410 - accuracy: 0.8564 - val_loss: 0.8610 - val_accuracy: 0.7935
Epoch 96/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8625 - accuracy: 0.8564 - val_loss: 0.8571 - val_accuracy: 0.7935
Epoch 97/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8693 - accuracy: 0.8564 - val_loss: 0.8560 - val_accuracy: 0.7935
Epoch 98/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8503 - accuracy: 0.8564 - val_loss: 0.9414 - val_accuracy: 0.7935
Epoch 99/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8683 - accuracy: 0.8564 - val_loss: 0.8546 - val_accuracy: 0.7935
Epoch 100/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8307 - accuracy: 0.8564 - val_loss: 0.8213 - val_accuracy: 0.7935
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 233ms/step - loss: 6.5502 - accuracy: 0.4915 - val_loss: 2.9143 - val_accuracy: 0.8152
Epoch 2/100
2/2 [==============================] - 0s 49ms/step - loss: 2.6054 - accuracy: 0.8540 - val_loss: 2.8028 - val_accuracy: 0.8152
Epoch 3/100
2/2 [==============================] - 0s 34ms/step - loss: 2.7203 - accuracy: 0.8540 - val_loss: 2.8067 - val_accuracy: 0.8152
Epoch 4/100
2/2 [==============================] - 0s 33ms/step - loss: 2.5758 - accuracy: 0.8540 - val_loss: 2.2870 - val_accuracy: 0.8152
Epoch 5/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0883 - accuracy: 0.8540 - val_loss: 1.7801 - val_accuracy: 0.8152
Epoch 6/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6615 - accuracy: 0.8540 - val_loss: 1.6650 - val_accuracy: 0.8152
Epoch 7/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6347 - accuracy: 0.8528 - val_loss: 1.7210 - val_accuracy: 0.8152
Epoch 8/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6161 - accuracy: 0.8540 - val_loss: 1.4585 - val_accuracy: 0.8152
Epoch 9/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3712 - accuracy: 0.8540 - val_loss: 1.3614 - val_accuracy: 0.8152
Epoch 10/100
2/2 [==============================] - 0s 46ms/step - loss: 1.2796 - accuracy: 0.8540 - val_loss: 1.3805 - val_accuracy: 0.8152
Epoch 11/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2879 - accuracy: 0.8540 - val_loss: 1.2725 - val_accuracy: 0.8152
Epoch 12/100
2/2 [==============================] - 0s 43ms/step - loss: 1.1970 - accuracy: 0.8540 - val_loss: 1.1736 - val_accuracy: 0.8152
Epoch 13/100
2/2 [==============================] - 0s 33ms/step - loss: 1.1300 - accuracy: 0.8540 - val_loss: 1.1468 - val_accuracy: 0.8152
Epoch 14/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0656 - accuracy: 0.8540 - val_loss: 1.1079 - val_accuracy: 0.8152
Epoch 15/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0523 - accuracy: 0.8540 - val_loss: 1.0742 - val_accuracy: 0.8152
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9964 - accuracy: 0.8540 - val_loss: 1.0072 - val_accuracy: 0.8152
Epoch 17/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9324 - accuracy: 0.8540 - val_loss: 1.0466 - val_accuracy: 0.8152
Epoch 18/100
2/2 [==============================] - 0s 53ms/step - loss: 0.9687 - accuracy: 0.8540 - val_loss: 0.9840 - val_accuracy: 0.8152
Epoch 19/100
2/2 [==============================] - 0s 48ms/step - loss: 0.9119 - accuracy: 0.8577 - val_loss: 0.9683 - val_accuracy: 0.8152
Epoch 20/100
2/2 [==============================] - 0s 46ms/step - loss: 0.9145 - accuracy: 0.8540 - val_loss: 1.0142 - val_accuracy: 0.8152
Epoch 21/100
2/2 [==============================] - 0s 51ms/step - loss: 0.9266 - accuracy: 0.8540 - val_loss: 0.9342 - val_accuracy: 0.8152
Epoch 22/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8879 - accuracy: 0.8552 - val_loss: 0.9655 - val_accuracy: 0.8152
Epoch 23/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8785 - accuracy: 0.8540 - val_loss: 0.9605 - val_accuracy: 0.8152
Epoch 24/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8610 - accuracy: 0.8540 - val_loss: 0.9501 - val_accuracy: 0.8152
Epoch 25/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8743 - accuracy: 0.8528 - val_loss: 0.9538 - val_accuracy: 0.8152
Epoch 26/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8853 - accuracy: 0.8564 - val_loss: 0.9142 - val_accuracy: 0.8152
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8705 - accuracy: 0.8528 - val_loss: 0.9337 - val_accuracy: 0.8152
Epoch 28/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8712 - accuracy: 0.8528 - val_loss: 0.9288 - val_accuracy: 0.8152
Epoch 29/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8807 - accuracy: 0.8528 - val_loss: 0.9268 - val_accuracy: 0.8152
Epoch 30/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8601 - accuracy: 0.8564 - val_loss: 0.9577 - val_accuracy: 0.8261
Epoch 31/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8859 - accuracy: 0.8637 - val_loss: 0.9368 - val_accuracy: 0.8152
Epoch 32/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8953 - accuracy: 0.8528 - val_loss: 0.9517 - val_accuracy: 0.8261
Epoch 33/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8992 - accuracy: 0.8564 - val_loss: 0.9287 - val_accuracy: 0.8152
Epoch 34/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8778 - accuracy: 0.8540 - val_loss: 0.9585 - val_accuracy: 0.8152
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8853 - accuracy: 0.8516 - val_loss: 0.9277 - val_accuracy: 0.8152
Epoch 36/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8737 - accuracy: 0.8577 - val_loss: 0.8985 - val_accuracy: 0.8152
Epoch 37/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8404 - accuracy: 0.8601 - val_loss: 0.9476 - val_accuracy: 0.8152
Epoch 38/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8856 - accuracy: 0.8552 - val_loss: 0.9704 - val_accuracy: 0.8152
Epoch 39/100
2/2 [==============================] - 0s 54ms/step - loss: 0.8803 - accuracy: 0.8552 - val_loss: 0.9221 - val_accuracy: 0.8152
Epoch 40/100
2/2 [==============================] - 0s 60ms/step - loss: 0.8627 - accuracy: 0.8552 - val_loss: 0.9495 - val_accuracy: 0.8152
Epoch 41/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8762 - accuracy: 0.8540 - val_loss: 0.9323 - val_accuracy: 0.8152
Epoch 42/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8745 - accuracy: 0.8540 - val_loss: 0.9329 - val_accuracy: 0.8152
Epoch 43/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8719 - accuracy: 0.8528 - val_loss: 0.9197 - val_accuracy: 0.8152
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8486 - accuracy: 0.8613 - val_loss: 0.9298 - val_accuracy: 0.8152
Epoch 45/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8642 - accuracy: 0.8564 - val_loss: 0.9517 - val_accuracy: 0.8152
Epoch 46/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8497 - accuracy: 0.8540 - val_loss: 0.9284 - val_accuracy: 0.8152
Epoch 47/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8745 - accuracy: 0.8528 - val_loss: 0.8797 - val_accuracy: 0.8261
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8692 - accuracy: 0.8467 - val_loss: 0.9113 - val_accuracy: 0.8152
Epoch 49/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8511 - accuracy: 0.8564 - val_loss: 0.9488 - val_accuracy: 0.8152
Epoch 50/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8715 - accuracy: 0.8528 - val_loss: 0.9522 - val_accuracy: 0.8152
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8563 - accuracy: 0.8564 - val_loss: 0.8854 - val_accuracy: 0.8261
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8402 - accuracy: 0.8601 - val_loss: 0.9158 - val_accuracy: 0.8261
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8786 - accuracy: 0.8504 - val_loss: 0.9245 - val_accuracy: 0.8152
Epoch 54/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8518 - accuracy: 0.8577 - val_loss: 0.9190 - val_accuracy: 0.8152
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8661 - accuracy: 0.8491 - val_loss: 0.9591 - val_accuracy: 0.8152
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8619 - accuracy: 0.8601 - val_loss: 0.8961 - val_accuracy: 0.8261
Epoch 57/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8677 - accuracy: 0.8491 - val_loss: 0.9192 - val_accuracy: 0.8152
Epoch 58/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8587 - accuracy: 0.8552 - val_loss: 0.9298 - val_accuracy: 0.8261
Epoch 59/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8602 - accuracy: 0.8564 - val_loss: 0.9877 - val_accuracy: 0.8152
Epoch 60/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9055 - accuracy: 0.8528 - val_loss: 0.9498 - val_accuracy: 0.8152
Epoch 61/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8541 - accuracy: 0.8589 - val_loss: 0.9280 - val_accuracy: 0.8152
Epoch 62/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8589 - accuracy: 0.8516 - val_loss: 0.9053 - val_accuracy: 0.8152
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8476 - accuracy: 0.8552 - val_loss: 0.8539 - val_accuracy: 0.8152
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8343 - accuracy: 0.8528 - val_loss: 0.9260 - val_accuracy: 0.8152
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8523 - accuracy: 0.8540 - val_loss: 0.9105 - val_accuracy: 0.8152
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8245 - accuracy: 0.8540 - val_loss: 0.9001 - val_accuracy: 0.8152
Epoch 67/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8380 - accuracy: 0.8552 - val_loss: 0.9271 - val_accuracy: 0.8152
Epoch 68/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8467 - accuracy: 0.8552 - val_loss: 0.9062 - val_accuracy: 0.8152
Epoch 69/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8400 - accuracy: 0.8516 - val_loss: 0.8909 - val_accuracy: 0.8261
Epoch 70/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8600 - accuracy: 0.8613 - val_loss: 0.9399 - val_accuracy: 0.8152
Epoch 71/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8509 - accuracy: 0.8625 - val_loss: 0.8916 - val_accuracy: 0.8152
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8417 - accuracy: 0.8540 - val_loss: 0.9067 - val_accuracy: 0.8152
Epoch 73/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8508 - accuracy: 0.8528 - val_loss: 0.9529 - val_accuracy: 0.8152
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8664 - accuracy: 0.8564 - val_loss: 0.8749 - val_accuracy: 0.8152
Epoch 75/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8270 - accuracy: 0.8540 - val_loss: 0.8767 - val_accuracy: 0.8152
Epoch 76/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8204 - accuracy: 0.8564 - val_loss: 0.9586 - val_accuracy: 0.8261
Epoch 77/100
2/2 [==============================] - 0s 27ms/step - loss: 0.8635 - accuracy: 0.8637 - val_loss: 0.9674 - val_accuracy: 0.8152
Epoch 78/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8582 - accuracy: 0.8601 - val_loss: 0.8605 - val_accuracy: 0.8152
Epoch 79/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8258 - accuracy: 0.8613 - val_loss: 0.9062 - val_accuracy: 0.8152
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8542 - accuracy: 0.8601 - val_loss: 0.9217 - val_accuracy: 0.8152
Epoch 81/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8402 - accuracy: 0.8552 - val_loss: 0.9039 - val_accuracy: 0.8152
Epoch 82/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8223 - accuracy: 0.8577 - val_loss: 0.8763 - val_accuracy: 0.8261
Epoch 83/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8247 - accuracy: 0.8540 - val_loss: 0.9341 - val_accuracy: 0.8152
Epoch 84/100
2/2 [==============================] - 0s 26ms/step - loss: 0.8282 - accuracy: 0.8540 - val_loss: 0.8847 - val_accuracy: 0.8152
Epoch 85/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8216 - accuracy: 0.8589 - val_loss: 0.8849 - val_accuracy: 0.8152
Epoch 86/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8253 - accuracy: 0.8577 - val_loss: 0.9131 - val_accuracy: 0.8152
Epoch 87/100
2/2 [==============================] - 0s 28ms/step - loss: 0.8358 - accuracy: 0.8589 - val_loss: 0.8885 - val_accuracy: 0.8152
Epoch 88/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8328 - accuracy: 0.8601 - val_loss: 0.9140 - val_accuracy: 0.8152
Epoch 89/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8406 - accuracy: 0.8637 - val_loss: 0.9023 - val_accuracy: 0.8152
Epoch 90/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8157 - accuracy: 0.8613 - val_loss: 0.9311 - val_accuracy: 0.8152
Epoch 91/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8382 - accuracy: 0.8540 - val_loss: 0.8702 - val_accuracy: 0.8152
Epoch 92/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8419 - accuracy: 0.8540 - val_loss: 0.8944 - val_accuracy: 0.8152
Epoch 93/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8332 - accuracy: 0.8504 - val_loss: 0.9058 - val_accuracy: 0.8152
Epoch 94/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8294 - accuracy: 0.8467 - val_loss: 0.8881 - val_accuracy: 0.8152
Epoch 95/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8324 - accuracy: 0.8613 - val_loss: 0.9270 - val_accuracy: 0.8152
Epoch 96/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8467 - accuracy: 0.8564 - val_loss: 0.8698 - val_accuracy: 0.8370
Epoch 97/100
2/2 [==============================] - 0s 28ms/step - loss: 0.8366 - accuracy: 0.8783 - val_loss: 0.9356 - val_accuracy: 0.8152
Epoch 98/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8559 - accuracy: 0.8540 - val_loss: 0.9097 - val_accuracy: 0.8152
Epoch 99/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8156 - accuracy: 0.8540 - val_loss: 0.8411 - val_accuracy: 0.8261
Epoch 100/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8256 - accuracy: 0.8491 - val_loss: 0.9468 - val_accuracy: 0.8152
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 235ms/step - loss: 7.3567 - accuracy: 0.3942 - val_loss: 2.7978 - val_accuracy: 0.8587
Epoch 2/100
2/2 [==============================] - 0s 36ms/step - loss: 2.6569 - accuracy: 0.8479 - val_loss: 2.6374 - val_accuracy: 0.8587
Epoch 3/100
2/2 [==============================] - 0s 50ms/step - loss: 2.8346 - accuracy: 0.8491 - val_loss: 2.6888 - val_accuracy: 0.8587
Epoch 4/100
2/2 [==============================] - 0s 37ms/step - loss: 2.7262 - accuracy: 0.8491 - val_loss: 2.0782 - val_accuracy: 0.8587
Epoch 5/100
2/2 [==============================] - 0s 46ms/step - loss: 2.0949 - accuracy: 0.8491 - val_loss: 1.7298 - val_accuracy: 0.8587
Epoch 6/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7924 - accuracy: 0.8479 - val_loss: 1.6558 - val_accuracy: 0.8587
Epoch 7/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7687 - accuracy: 0.8418 - val_loss: 1.6156 - val_accuracy: 0.8587
Epoch 8/100
2/2 [==============================] - 0s 48ms/step - loss: 1.6475 - accuracy: 0.8504 - val_loss: 1.4161 - val_accuracy: 0.8587
Epoch 9/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4685 - accuracy: 0.8491 - val_loss: 1.2995 - val_accuracy: 0.8587
Epoch 10/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3611 - accuracy: 0.8491 - val_loss: 1.1510 - val_accuracy: 0.8587
Epoch 11/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2494 - accuracy: 0.8491 - val_loss: 1.1585 - val_accuracy: 0.8587
Epoch 12/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2395 - accuracy: 0.8491 - val_loss: 1.1395 - val_accuracy: 0.8587
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1835 - accuracy: 0.8491 - val_loss: 1.0475 - val_accuracy: 0.8587
Epoch 14/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0877 - accuracy: 0.8491 - val_loss: 0.9942 - val_accuracy: 0.8587
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0589 - accuracy: 0.8491 - val_loss: 0.9600 - val_accuracy: 0.8587
Epoch 16/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0368 - accuracy: 0.8491 - val_loss: 0.9240 - val_accuracy: 0.8587
Epoch 17/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9975 - accuracy: 0.8491 - val_loss: 0.9486 - val_accuracy: 0.8587
Epoch 18/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0169 - accuracy: 0.8491 - val_loss: 0.8849 - val_accuracy: 0.8587
Epoch 19/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9354 - accuracy: 0.8491 - val_loss: 0.8456 - val_accuracy: 0.8587
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9311 - accuracy: 0.8491 - val_loss: 0.9170 - val_accuracy: 0.8587
Epoch 21/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9782 - accuracy: 0.8491 - val_loss: 0.8629 - val_accuracy: 0.8587
Epoch 22/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9413 - accuracy: 0.8491 - val_loss: 0.8064 - val_accuracy: 0.8587
Epoch 23/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8985 - accuracy: 0.8491 - val_loss: 0.8491 - val_accuracy: 0.8587
Epoch 24/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9318 - accuracy: 0.8491 - val_loss: 0.8371 - val_accuracy: 0.8587
Epoch 25/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9314 - accuracy: 0.8491 - val_loss: 0.7989 - val_accuracy: 0.8587
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8739 - accuracy: 0.8491 - val_loss: 0.8001 - val_accuracy: 0.8587
Epoch 27/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8848 - accuracy: 0.8491 - val_loss: 0.8263 - val_accuracy: 0.8587
Epoch 28/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9020 - accuracy: 0.8491 - val_loss: 0.7601 - val_accuracy: 0.8587
Epoch 29/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8273 - accuracy: 0.8491 - val_loss: 0.7814 - val_accuracy: 0.8587
Epoch 30/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8895 - accuracy: 0.8491 - val_loss: 0.8440 - val_accuracy: 0.8587
Epoch 31/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8914 - accuracy: 0.8491 - val_loss: 0.7544 - val_accuracy: 0.8587
Epoch 32/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8535 - accuracy: 0.8491 - val_loss: 0.8107 - val_accuracy: 0.8587
Epoch 33/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9037 - accuracy: 0.8491 - val_loss: 0.7794 - val_accuracy: 0.8587
Epoch 34/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8705 - accuracy: 0.8491 - val_loss: 0.7684 - val_accuracy: 0.8587
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8888 - accuracy: 0.8491 - val_loss: 0.7905 - val_accuracy: 0.8587
Epoch 36/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8673 - accuracy: 0.8491 - val_loss: 0.7590 - val_accuracy: 0.8587
Epoch 37/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8646 - accuracy: 0.8491 - val_loss: 0.7981 - val_accuracy: 0.8587
Epoch 38/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8725 - accuracy: 0.8491 - val_loss: 0.7905 - val_accuracy: 0.8587
Epoch 39/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8672 - accuracy: 0.8491 - val_loss: 0.7596 - val_accuracy: 0.8587
Epoch 40/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8515 - accuracy: 0.8491 - val_loss: 0.7532 - val_accuracy: 0.8587
Epoch 41/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8483 - accuracy: 0.8491 - val_loss: 0.7862 - val_accuracy: 0.8587
Epoch 42/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8680 - accuracy: 0.8491 - val_loss: 0.7653 - val_accuracy: 0.8587
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8569 - accuracy: 0.8491 - val_loss: 0.7414 - val_accuracy: 0.8587
Epoch 44/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8391 - accuracy: 0.8491 - val_loss: 0.7804 - val_accuracy: 0.8587
Epoch 45/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8824 - accuracy: 0.8491 - val_loss: 0.7956 - val_accuracy: 0.8587
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8728 - accuracy: 0.8491 - val_loss: 0.7102 - val_accuracy: 0.8587
Epoch 47/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8248 - accuracy: 0.8491 - val_loss: 0.7799 - val_accuracy: 0.8587
Epoch 48/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8891 - accuracy: 0.8491 - val_loss: 0.7879 - val_accuracy: 0.8587
Epoch 49/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8660 - accuracy: 0.8491 - val_loss: 0.7592 - val_accuracy: 0.8587
Epoch 50/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8692 - accuracy: 0.8491 - val_loss: 0.7478 - val_accuracy: 0.8587
Epoch 51/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8620 - accuracy: 0.8491 - val_loss: 0.7715 - val_accuracy: 0.8587
Epoch 52/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8809 - accuracy: 0.8491 - val_loss: 0.8060 - val_accuracy: 0.8587
Epoch 53/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8789 - accuracy: 0.8491 - val_loss: 0.7445 - val_accuracy: 0.8587
Epoch 54/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8482 - accuracy: 0.8491 - val_loss: 0.7500 - val_accuracy: 0.8587
Epoch 55/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8609 - accuracy: 0.8491 - val_loss: 0.7982 - val_accuracy: 0.8587
Epoch 56/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8602 - accuracy: 0.8491 - val_loss: 0.7577 - val_accuracy: 0.8587
Epoch 57/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8557 - accuracy: 0.8491 - val_loss: 0.8086 - val_accuracy: 0.8587
Epoch 58/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8845 - accuracy: 0.8491 - val_loss: 0.7476 - val_accuracy: 0.8587
Epoch 59/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8561 - accuracy: 0.8491 - val_loss: 0.7648 - val_accuracy: 0.8587
Epoch 60/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8735 - accuracy: 0.8491 - val_loss: 0.7503 - val_accuracy: 0.8587
Epoch 61/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8583 - accuracy: 0.8491 - val_loss: 0.7622 - val_accuracy: 0.8587
Epoch 62/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8677 - accuracy: 0.8491 - val_loss: 0.7830 - val_accuracy: 0.8587
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8664 - accuracy: 0.8491 - val_loss: 0.7537 - val_accuracy: 0.8587
Epoch 64/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8560 - accuracy: 0.8491 - val_loss: 0.7312 - val_accuracy: 0.8587
Epoch 65/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8299 - accuracy: 0.8491 - val_loss: 0.7769 - val_accuracy: 0.8587
Epoch 66/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8770 - accuracy: 0.8491 - val_loss: 0.7736 - val_accuracy: 0.8587
Epoch 67/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8435 - accuracy: 0.8491 - val_loss: 0.7310 - val_accuracy: 0.8587
Epoch 68/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8569 - accuracy: 0.8491 - val_loss: 0.7825 - val_accuracy: 0.8587
Epoch 69/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8760 - accuracy: 0.8491 - val_loss: 0.7942 - val_accuracy: 0.8587
Epoch 70/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8774 - accuracy: 0.8491 - val_loss: 0.7595 - val_accuracy: 0.8587
Epoch 71/100
2/2 [==============================] - 0s 68ms/step - loss: 0.8434 - accuracy: 0.8491 - val_loss: 0.7693 - val_accuracy: 0.8587
Epoch 72/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8710 - accuracy: 0.8491 - val_loss: 0.7992 - val_accuracy: 0.8587
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8895 - accuracy: 0.8491 - val_loss: 0.7815 - val_accuracy: 0.8587
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8592 - accuracy: 0.8491 - val_loss: 0.7823 - val_accuracy: 0.8587
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8645 - accuracy: 0.8491 - val_loss: 0.7678 - val_accuracy: 0.8587
Epoch 76/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8526 - accuracy: 0.8491 - val_loss: 0.7439 - val_accuracy: 0.8587
Epoch 77/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8356 - accuracy: 0.8491 - val_loss: 0.7583 - val_accuracy: 0.8587
Epoch 78/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8655 - accuracy: 0.8491 - val_loss: 0.7264 - val_accuracy: 0.8587
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8449 - accuracy: 0.8479 - val_loss: 0.7490 - val_accuracy: 0.8587
Epoch 80/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8749 - accuracy: 0.8491 - val_loss: 0.7627 - val_accuracy: 0.8587
Epoch 81/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8601 - accuracy: 0.8479 - val_loss: 0.7428 - val_accuracy: 0.8587
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8224 - accuracy: 0.8491 - val_loss: 0.7616 - val_accuracy: 0.8587
Epoch 83/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8728 - accuracy: 0.8491 - val_loss: 0.8044 - val_accuracy: 0.8587
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8890 - accuracy: 0.8491 - val_loss: 0.7566 - val_accuracy: 0.8587
Epoch 85/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8651 - accuracy: 0.8491 - val_loss: 0.7646 - val_accuracy: 0.8587
Epoch 86/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8458 - accuracy: 0.8504 - val_loss: 0.7575 - val_accuracy: 0.8587
Epoch 87/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8524 - accuracy: 0.8491 - val_loss: 0.7594 - val_accuracy: 0.8587
Epoch 88/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8703 - accuracy: 0.8491 - val_loss: 0.7331 - val_accuracy: 0.8587
Epoch 89/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8400 - accuracy: 0.8491 - val_loss: 0.7909 - val_accuracy: 0.8587
Epoch 90/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8724 - accuracy: 0.8491 - val_loss: 0.7905 - val_accuracy: 0.8587
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8609 - accuracy: 0.8491 - val_loss: 0.7453 - val_accuracy: 0.8587
Epoch 92/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8452 - accuracy: 0.8491 - val_loss: 0.7997 - val_accuracy: 0.8587
Epoch 93/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8808 - accuracy: 0.8491 - val_loss: 0.8126 - val_accuracy: 0.8587
Epoch 94/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8831 - accuracy: 0.8491 - val_loss: 0.7749 - val_accuracy: 0.8587
Epoch 95/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8621 - accuracy: 0.8491 - val_loss: 0.7545 - val_accuracy: 0.8587
Epoch 96/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8483 - accuracy: 0.8491 - val_loss: 0.7649 - val_accuracy: 0.8587
Epoch 97/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8518 - accuracy: 0.8491 - val_loss: 0.7693 - val_accuracy: 0.8587
Epoch 98/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8670 - accuracy: 0.8491 - val_loss: 0.7581 - val_accuracy: 0.8587
Epoch 99/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8393 - accuracy: 0.8491 - val_loss: 0.7642 - val_accuracy: 0.8587
Epoch 100/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8688 - accuracy: 0.8491 - val_loss: 0.7687 - val_accuracy: 0.8587
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 252us/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 227ms/step - loss: 6.9394 - accuracy: 0.4447 - val_loss: 2.8640 - val_accuracy: 0.8352
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 2.6168 - accuracy: 0.8518 - val_loss: 2.5251 - val_accuracy: 0.8352
Epoch 3/100
2/2 [==============================] - 0s 41ms/step - loss: 2.6296 - accuracy: 0.8518 - val_loss: 2.6179 - val_accuracy: 0.8352
Epoch 4/100
2/2 [==============================] - 0s 37ms/step - loss: 2.5769 - accuracy: 0.8518 - val_loss: 2.0387 - val_accuracy: 0.8352
Epoch 5/100
2/2 [==============================] - 0s 50ms/step - loss: 2.0206 - accuracy: 0.8505 - val_loss: 1.6297 - val_accuracy: 0.8352
Epoch 6/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6693 - accuracy: 0.8481 - val_loss: 1.6109 - val_accuracy: 0.8352
Epoch 7/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6575 - accuracy: 0.8518 - val_loss: 1.6172 - val_accuracy: 0.8352
Epoch 8/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5889 - accuracy: 0.8518 - val_loss: 1.3953 - val_accuracy: 0.8352
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3874 - accuracy: 0.8518 - val_loss: 1.2679 - val_accuracy: 0.8352
Epoch 10/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2972 - accuracy: 0.8518 - val_loss: 1.2529 - val_accuracy: 0.8352
Epoch 11/100
2/2 [==============================] - 0s 48ms/step - loss: 1.2866 - accuracy: 0.8518 - val_loss: 1.2234 - val_accuracy: 0.8352
Epoch 12/100
2/2 [==============================] - 0s 48ms/step - loss: 1.2353 - accuracy: 0.8518 - val_loss: 1.0767 - val_accuracy: 0.8352
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1135 - accuracy: 0.8518 - val_loss: 1.0708 - val_accuracy: 0.8352
Epoch 14/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1014 - accuracy: 0.8518 - val_loss: 1.0700 - val_accuracy: 0.8352
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0867 - accuracy: 0.8518 - val_loss: 0.9626 - val_accuracy: 0.8352
Epoch 16/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0183 - accuracy: 0.8518 - val_loss: 0.9423 - val_accuracy: 0.8352
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9890 - accuracy: 0.8518 - val_loss: 0.9763 - val_accuracy: 0.8352
Epoch 18/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0026 - accuracy: 0.8518 - val_loss: 0.9208 - val_accuracy: 0.8352
Epoch 19/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9640 - accuracy: 0.8518 - val_loss: 0.9077 - val_accuracy: 0.8352
Epoch 20/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9542 - accuracy: 0.8518 - val_loss: 0.9212 - val_accuracy: 0.8352
Epoch 21/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9598 - accuracy: 0.8518 - val_loss: 0.8977 - val_accuracy: 0.8352
Epoch 22/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9277 - accuracy: 0.8518 - val_loss: 0.8760 - val_accuracy: 0.8352
Epoch 23/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9189 - accuracy: 0.8518 - val_loss: 0.8893 - val_accuracy: 0.8352
Epoch 24/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9277 - accuracy: 0.8518 - val_loss: 0.8795 - val_accuracy: 0.8352
Epoch 25/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9378 - accuracy: 0.8518 - val_loss: 0.8876 - val_accuracy: 0.8352
Epoch 26/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9354 - accuracy: 0.8518 - val_loss: 0.8622 - val_accuracy: 0.8352
Epoch 27/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9061 - accuracy: 0.8518 - val_loss: 0.8119 - val_accuracy: 0.8352
Epoch 28/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8949 - accuracy: 0.8518 - val_loss: 0.8676 - val_accuracy: 0.8352
Epoch 29/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9067 - accuracy: 0.8518 - val_loss: 0.8461 - val_accuracy: 0.8352
Epoch 30/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8911 - accuracy: 0.8518 - val_loss: 0.8416 - val_accuracy: 0.8352
Epoch 31/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8894 - accuracy: 0.8518 - val_loss: 0.8188 - val_accuracy: 0.8352
Epoch 32/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8669 - accuracy: 0.8518 - val_loss: 0.8540 - val_accuracy: 0.8352
Epoch 33/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8962 - accuracy: 0.8542 - val_loss: 0.7884 - val_accuracy: 0.8352
Epoch 34/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8575 - accuracy: 0.8433 - val_loss: 0.8346 - val_accuracy: 0.8352
Epoch 35/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8880 - accuracy: 0.8518 - val_loss: 0.8040 - val_accuracy: 0.8352
Epoch 36/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8473 - accuracy: 0.8530 - val_loss: 0.8092 - val_accuracy: 0.8352
Epoch 37/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8615 - accuracy: 0.8518 - val_loss: 0.8258 - val_accuracy: 0.8352
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8572 - accuracy: 0.8518 - val_loss: 0.8051 - val_accuracy: 0.8352
Epoch 39/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8650 - accuracy: 0.8530 - val_loss: 0.8087 - val_accuracy: 0.8352
Epoch 40/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8571 - accuracy: 0.8518 - val_loss: 0.8003 - val_accuracy: 0.8352
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8579 - accuracy: 0.8518 - val_loss: 0.8137 - val_accuracy: 0.8352
Epoch 42/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8835 - accuracy: 0.8554 - val_loss: 0.7859 - val_accuracy: 0.8352
Epoch 43/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8704 - accuracy: 0.8530 - val_loss: 0.8290 - val_accuracy: 0.8352
Epoch 44/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8860 - accuracy: 0.8518 - val_loss: 0.8287 - val_accuracy: 0.8352
Epoch 45/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8818 - accuracy: 0.8518 - val_loss: 0.7998 - val_accuracy: 0.8352
Epoch 46/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8801 - accuracy: 0.8505 - val_loss: 0.8234 - val_accuracy: 0.8352
Epoch 47/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8635 - accuracy: 0.8530 - val_loss: 0.8135 - val_accuracy: 0.8352
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8770 - accuracy: 0.8518 - val_loss: 0.8263 - val_accuracy: 0.8352
Epoch 49/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8851 - accuracy: 0.8530 - val_loss: 0.8162 - val_accuracy: 0.8352
Epoch 50/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8655 - accuracy: 0.8505 - val_loss: 0.8918 - val_accuracy: 0.8352
Epoch 51/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9174 - accuracy: 0.8493 - val_loss: 0.8294 - val_accuracy: 0.8352
Epoch 52/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8852 - accuracy: 0.8518 - val_loss: 0.8385 - val_accuracy: 0.8352
Epoch 53/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8856 - accuracy: 0.8518 - val_loss: 0.8734 - val_accuracy: 0.8352
Epoch 54/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9064 - accuracy: 0.8518 - val_loss: 0.7922 - val_accuracy: 0.8352
Epoch 55/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8517 - accuracy: 0.8518 - val_loss: 0.8188 - val_accuracy: 0.8352
Epoch 56/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8813 - accuracy: 0.8493 - val_loss: 0.8258 - val_accuracy: 0.8352
Epoch 57/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8944 - accuracy: 0.8505 - val_loss: 0.7961 - val_accuracy: 0.8352
Epoch 58/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8629 - accuracy: 0.8566 - val_loss: 0.8136 - val_accuracy: 0.8352
Epoch 59/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8702 - accuracy: 0.8530 - val_loss: 0.8582 - val_accuracy: 0.8352
Epoch 60/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8956 - accuracy: 0.8518 - val_loss: 0.7851 - val_accuracy: 0.8352
Epoch 61/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8483 - accuracy: 0.8505 - val_loss: 0.8074 - val_accuracy: 0.8352
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8616 - accuracy: 0.8518 - val_loss: 0.8002 - val_accuracy: 0.8352
Epoch 63/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8553 - accuracy: 0.8493 - val_loss: 0.7836 - val_accuracy: 0.8352
Epoch 64/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8487 - accuracy: 0.8518 - val_loss: 0.8151 - val_accuracy: 0.8352
Epoch 65/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8592 - accuracy: 0.8518 - val_loss: 0.8143 - val_accuracy: 0.8352
Epoch 66/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8584 - accuracy: 0.8518 - val_loss: 0.8199 - val_accuracy: 0.8352
Epoch 67/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8608 - accuracy: 0.8493 - val_loss: 0.7928 - val_accuracy: 0.8352
Epoch 68/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8602 - accuracy: 0.8591 - val_loss: 0.7967 - val_accuracy: 0.8352
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8607 - accuracy: 0.8627 - val_loss: 0.7877 - val_accuracy: 0.8352
Epoch 70/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8577 - accuracy: 0.8542 - val_loss: 0.8172 - val_accuracy: 0.8352
Epoch 71/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8799 - accuracy: 0.8518 - val_loss: 0.7873 - val_accuracy: 0.8352
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8627 - accuracy: 0.8578 - val_loss: 0.8411 - val_accuracy: 0.8352
Epoch 73/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8762 - accuracy: 0.8518 - val_loss: 0.8271 - val_accuracy: 0.8352
Epoch 74/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8622 - accuracy: 0.8505 - val_loss: 0.8490 - val_accuracy: 0.8352
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8936 - accuracy: 0.8542 - val_loss: 0.7907 - val_accuracy: 0.8352
Epoch 76/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8528 - accuracy: 0.8505 - val_loss: 0.8228 - val_accuracy: 0.8352
Epoch 77/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8776 - accuracy: 0.8481 - val_loss: 0.8292 - val_accuracy: 0.8352
Epoch 78/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8948 - accuracy: 0.8518 - val_loss: 0.8338 - val_accuracy: 0.8352
Epoch 79/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8939 - accuracy: 0.8505 - val_loss: 0.8368 - val_accuracy: 0.8352
Epoch 80/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8816 - accuracy: 0.8530 - val_loss: 0.8420 - val_accuracy: 0.8352
Epoch 81/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8698 - accuracy: 0.8518 - val_loss: 0.8205 - val_accuracy: 0.8352
Epoch 82/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8939 - accuracy: 0.8518 - val_loss: 0.8144 - val_accuracy: 0.8352
Epoch 83/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8753 - accuracy: 0.8505 - val_loss: 0.8407 - val_accuracy: 0.8352
Epoch 84/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8833 - accuracy: 0.8518 - val_loss: 0.8135 - val_accuracy: 0.8352
Epoch 85/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8943 - accuracy: 0.8518 - val_loss: 0.8198 - val_accuracy: 0.8352
Epoch 86/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8666 - accuracy: 0.8542 - val_loss: 0.8551 - val_accuracy: 0.8352
Epoch 87/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9139 - accuracy: 0.8505 - val_loss: 0.8406 - val_accuracy: 0.8352
Epoch 88/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9099 - accuracy: 0.8457 - val_loss: 0.8241 - val_accuracy: 0.8352
Epoch 89/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8852 - accuracy: 0.8518 - val_loss: 0.8370 - val_accuracy: 0.8352
Epoch 90/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8797 - accuracy: 0.8518 - val_loss: 0.8120 - val_accuracy: 0.8352
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8522 - accuracy: 0.8518 - val_loss: 0.8425 - val_accuracy: 0.8352
Epoch 92/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8874 - accuracy: 0.8518 - val_loss: 0.7981 - val_accuracy: 0.8352
Epoch 93/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8621 - accuracy: 0.8518 - val_loss: 0.8145 - val_accuracy: 0.8352
Epoch 94/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8818 - accuracy: 0.8505 - val_loss: 0.8578 - val_accuracy: 0.8352
Epoch 95/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9029 - accuracy: 0.8505 - val_loss: 0.8045 - val_accuracy: 0.8462
Epoch 96/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8917 - accuracy: 0.8591 - val_loss: 0.8049 - val_accuracy: 0.8352
Epoch 97/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8864 - accuracy: 0.8578 - val_loss: 0.8345 - val_accuracy: 0.8352
Epoch 98/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8767 - accuracy: 0.8518 - val_loss: 0.8352 - val_accuracy: 0.8352
Epoch 99/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8859 - accuracy: 0.8518 - val_loss: 0.8331 - val_accuracy: 0.8352
Epoch 100/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8664 - accuracy: 0.8518 - val_loss: 0.8045 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 218ms/step - loss: 7.1448 - accuracy: 0.4970 - val_loss: 3.1019 - val_accuracy: 0.8681
Epoch 2/100
2/2 [==============================] - 0s 40ms/step - loss: 2.7899 - accuracy: 0.8481 - val_loss: 2.5875 - val_accuracy: 0.8681
Epoch 3/100
2/2 [==============================] - 0s 50ms/step - loss: 2.7224 - accuracy: 0.8481 - val_loss: 2.9327 - val_accuracy: 0.8681
Epoch 4/100
2/2 [==============================] - 0s 36ms/step - loss: 2.7706 - accuracy: 0.8481 - val_loss: 2.3731 - val_accuracy: 0.8681
Epoch 5/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1898 - accuracy: 0.8481 - val_loss: 1.8579 - val_accuracy: 0.8681
Epoch 6/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7734 - accuracy: 0.8505 - val_loss: 1.6627 - val_accuracy: 0.8681
Epoch 7/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7197 - accuracy: 0.8469 - val_loss: 1.6734 - val_accuracy: 0.8681
Epoch 8/100
2/2 [==============================] - 0s 65ms/step - loss: 1.6394 - accuracy: 0.8481 - val_loss: 1.5283 - val_accuracy: 0.8681
Epoch 9/100
2/2 [==============================] - 0s 29ms/step - loss: 1.4872 - accuracy: 0.8481 - val_loss: 1.4099 - val_accuracy: 0.8681
Epoch 10/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3627 - accuracy: 0.8481 - val_loss: 1.3196 - val_accuracy: 0.8681
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2815 - accuracy: 0.8481 - val_loss: 1.2782 - val_accuracy: 0.8681
Epoch 12/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2582 - accuracy: 0.8481 - val_loss: 1.1296 - val_accuracy: 0.8681
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1445 - accuracy: 0.8481 - val_loss: 1.0960 - val_accuracy: 0.8681
Epoch 14/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0970 - accuracy: 0.8493 - val_loss: 1.1019 - val_accuracy: 0.8681
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0787 - accuracy: 0.8481 - val_loss: 1.0313 - val_accuracy: 0.8681
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0457 - accuracy: 0.8481 - val_loss: 0.9759 - val_accuracy: 0.8681
Epoch 17/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9828 - accuracy: 0.8481 - val_loss: 1.0056 - val_accuracy: 0.8681
Epoch 18/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9992 - accuracy: 0.8481 - val_loss: 0.9588 - val_accuracy: 0.8681
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9419 - accuracy: 0.8481 - val_loss: 0.9153 - val_accuracy: 0.8681
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9077 - accuracy: 0.8481 - val_loss: 0.9240 - val_accuracy: 0.8681
Epoch 21/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9257 - accuracy: 0.8481 - val_loss: 0.8809 - val_accuracy: 0.8681
Epoch 22/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8934 - accuracy: 0.8481 - val_loss: 0.9451 - val_accuracy: 0.8681
Epoch 23/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9279 - accuracy: 0.8481 - val_loss: 0.9030 - val_accuracy: 0.8681
Epoch 24/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8863 - accuracy: 0.8481 - val_loss: 0.8816 - val_accuracy: 0.8681
Epoch 25/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8940 - accuracy: 0.8481 - val_loss: 0.8964 - val_accuracy: 0.8681
Epoch 26/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8915 - accuracy: 0.8481 - val_loss: 0.8937 - val_accuracy: 0.8681
Epoch 27/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8866 - accuracy: 0.8481 - val_loss: 0.8577 - val_accuracy: 0.8681
Epoch 28/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8678 - accuracy: 0.8481 - val_loss: 0.8871 - val_accuracy: 0.8681
Epoch 29/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8882 - accuracy: 0.8481 - val_loss: 0.9415 - val_accuracy: 0.8681
Epoch 30/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9293 - accuracy: 0.8481 - val_loss: 0.8920 - val_accuracy: 0.8681
Epoch 31/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8841 - accuracy: 0.8481 - val_loss: 0.8862 - val_accuracy: 0.8681
Epoch 32/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8921 - accuracy: 0.8481 - val_loss: 0.8898 - val_accuracy: 0.8681
Epoch 33/100
2/2 [==============================] - 0s 71ms/step - loss: 0.8787 - accuracy: 0.8493 - val_loss: 0.8557 - val_accuracy: 0.8681
Epoch 34/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8628 - accuracy: 0.8481 - val_loss: 0.8917 - val_accuracy: 0.8681
Epoch 35/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8864 - accuracy: 0.8481 - val_loss: 0.8917 - val_accuracy: 0.8681
Epoch 36/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8749 - accuracy: 0.8493 - val_loss: 0.8442 - val_accuracy: 0.8681
Epoch 37/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8470 - accuracy: 0.8542 - val_loss: 0.8949 - val_accuracy: 0.8681
Epoch 38/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8722 - accuracy: 0.8481 - val_loss: 0.8513 - val_accuracy: 0.8681
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8545 - accuracy: 0.8481 - val_loss: 0.8867 - val_accuracy: 0.8681
Epoch 40/100
2/2 [==============================] - 0s 25ms/step - loss: 0.8814 - accuracy: 0.8445 - val_loss: 0.8980 - val_accuracy: 0.8681
Epoch 41/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8808 - accuracy: 0.8530 - val_loss: 0.8778 - val_accuracy: 0.8681
Epoch 42/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8675 - accuracy: 0.8481 - val_loss: 0.8822 - val_accuracy: 0.8681
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8852 - accuracy: 0.8493 - val_loss: 0.8688 - val_accuracy: 0.8681
Epoch 44/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8322 - accuracy: 0.8481 - val_loss: 0.8640 - val_accuracy: 0.8681
Epoch 45/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8568 - accuracy: 0.8481 - val_loss: 0.8609 - val_accuracy: 0.8681
Epoch 46/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8594 - accuracy: 0.8481 - val_loss: 0.8423 - val_accuracy: 0.8681
Epoch 47/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8469 - accuracy: 0.8542 - val_loss: 0.8859 - val_accuracy: 0.8681
Epoch 48/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8524 - accuracy: 0.8518 - val_loss: 0.8418 - val_accuracy: 0.8681
Epoch 49/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8357 - accuracy: 0.8457 - val_loss: 0.8271 - val_accuracy: 0.8681
Epoch 50/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8466 - accuracy: 0.8372 - val_loss: 0.8959 - val_accuracy: 0.8681
Epoch 51/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8838 - accuracy: 0.8433 - val_loss: 0.8713 - val_accuracy: 0.8681
Epoch 52/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8555 - accuracy: 0.8493 - val_loss: 0.8536 - val_accuracy: 0.8681
Epoch 53/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8642 - accuracy: 0.8481 - val_loss: 0.8218 - val_accuracy: 0.8681
Epoch 54/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8250 - accuracy: 0.8481 - val_loss: 0.8604 - val_accuracy: 0.8681
Epoch 55/100
2/2 [==============================] - 0s 27ms/step - loss: 0.8480 - accuracy: 0.8493 - val_loss: 0.8734 - val_accuracy: 0.8681
Epoch 56/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8476 - accuracy: 0.8493 - val_loss: 0.8533 - val_accuracy: 0.8681
Epoch 57/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8574 - accuracy: 0.8445 - val_loss: 0.8200 - val_accuracy: 0.8681
Epoch 58/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8270 - accuracy: 0.8469 - val_loss: 0.8372 - val_accuracy: 0.8681
Epoch 59/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8376 - accuracy: 0.8518 - val_loss: 0.8680 - val_accuracy: 0.8681
Epoch 60/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8642 - accuracy: 0.8554 - val_loss: 0.8283 - val_accuracy: 0.8681
Epoch 61/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8436 - accuracy: 0.8530 - val_loss: 0.8635 - val_accuracy: 0.8571
Epoch 62/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8470 - accuracy: 0.8591 - val_loss: 0.8755 - val_accuracy: 0.8681
Epoch 63/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8635 - accuracy: 0.8518 - val_loss: 0.8248 - val_accuracy: 0.8681
Epoch 64/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8416 - accuracy: 0.8445 - val_loss: 0.8192 - val_accuracy: 0.8681
Epoch 65/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8337 - accuracy: 0.8591 - val_loss: 0.8621 - val_accuracy: 0.8681
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8606 - accuracy: 0.8481 - val_loss: 0.8126 - val_accuracy: 0.8681
Epoch 67/100
2/2 [==============================] - 0s 26ms/step - loss: 0.8593 - accuracy: 0.8469 - val_loss: 0.8840 - val_accuracy: 0.8681
Epoch 68/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8790 - accuracy: 0.8481 - val_loss: 0.8747 - val_accuracy: 0.8681
Epoch 69/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8653 - accuracy: 0.8481 - val_loss: 0.8590 - val_accuracy: 0.8681
Epoch 70/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8582 - accuracy: 0.8505 - val_loss: 0.8650 - val_accuracy: 0.8681
Epoch 71/100
2/2 [==============================] - 0s 23ms/step - loss: 0.8525 - accuracy: 0.8481 - val_loss: 0.8420 - val_accuracy: 0.8681
Epoch 72/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8410 - accuracy: 0.8481 - val_loss: 0.8608 - val_accuracy: 0.8681
Epoch 73/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8609 - accuracy: 0.8566 - val_loss: 0.8845 - val_accuracy: 0.8681
Epoch 74/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8611 - accuracy: 0.8481 - val_loss: 0.8493 - val_accuracy: 0.8681
Epoch 75/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8167 - accuracy: 0.8481 - val_loss: 0.8291 - val_accuracy: 0.8681
Epoch 76/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8253 - accuracy: 0.8445 - val_loss: 0.8623 - val_accuracy: 0.8681
Epoch 77/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8536 - accuracy: 0.8493 - val_loss: 0.8670 - val_accuracy: 0.8681
Epoch 78/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8364 - accuracy: 0.8481 - val_loss: 0.8045 - val_accuracy: 0.8681
Epoch 79/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8376 - accuracy: 0.8505 - val_loss: 0.8419 - val_accuracy: 0.8681
Epoch 80/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8420 - accuracy: 0.8542 - val_loss: 0.8700 - val_accuracy: 0.8681
Epoch 81/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8432 - accuracy: 0.8433 - val_loss: 0.8482 - val_accuracy: 0.8681
Epoch 82/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8215 - accuracy: 0.8505 - val_loss: 0.7672 - val_accuracy: 0.8681
Epoch 83/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7976 - accuracy: 0.8481 - val_loss: 0.8308 - val_accuracy: 0.8681
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8351 - accuracy: 0.8433 - val_loss: 0.8801 - val_accuracy: 0.8681
Epoch 85/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8593 - accuracy: 0.8530 - val_loss: 0.8199 - val_accuracy: 0.8681
Epoch 86/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8109 - accuracy: 0.8481 - val_loss: 0.8054 - val_accuracy: 0.8681
Epoch 87/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8161 - accuracy: 0.8481 - val_loss: 0.8994 - val_accuracy: 0.8681
Epoch 88/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8402 - accuracy: 0.8566 - val_loss: 0.8339 - val_accuracy: 0.8681
Epoch 89/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8287 - accuracy: 0.8457 - val_loss: 0.8519 - val_accuracy: 0.8681
Epoch 90/100
2/2 [==============================] - 0s 27ms/step - loss: 0.8541 - accuracy: 0.8481 - val_loss: 0.8410 - val_accuracy: 0.8681
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8208 - accuracy: 0.8481 - val_loss: 0.8434 - val_accuracy: 0.8681
Epoch 92/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8155 - accuracy: 0.8469 - val_loss: 0.8268 - val_accuracy: 0.8681
Epoch 93/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8513 - accuracy: 0.8493 - val_loss: 0.8448 - val_accuracy: 0.8681
Epoch 94/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8592 - accuracy: 0.8481 - val_loss: 0.8624 - val_accuracy: 0.8681
Epoch 95/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8602 - accuracy: 0.8469 - val_loss: 0.8637 - val_accuracy: 0.8681
Epoch 96/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8421 - accuracy: 0.8481 - val_loss: 0.8104 - val_accuracy: 0.8681
Epoch 97/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8414 - accuracy: 0.8481 - val_loss: 0.8248 - val_accuracy: 0.8681
Epoch 98/100
2/2 [==============================] - 0s 26ms/step - loss: 0.8288 - accuracy: 0.8481 - val_loss: 0.8297 - val_accuracy: 0.8681
Epoch 99/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8354 - accuracy: 0.8481 - val_loss: 0.8427 - val_accuracy: 0.8681
Epoch 100/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8493 - accuracy: 0.8481 - val_loss: 0.8628 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 235ms/step - loss: 6.3799 - accuracy: 0.4313 - val_loss: 2.5556 - val_accuracy: 0.9011
Epoch 2/100
2/2 [==============================] - 0s 35ms/step - loss: 2.5463 - accuracy: 0.8433 - val_loss: 2.4792 - val_accuracy: 0.9011
Epoch 3/100
2/2 [==============================] - 0s 33ms/step - loss: 2.6799 - accuracy: 0.8445 - val_loss: 2.4493 - val_accuracy: 0.9011
Epoch 4/100
2/2 [==============================] - 0s 50ms/step - loss: 2.4720 - accuracy: 0.8445 - val_loss: 1.8655 - val_accuracy: 0.9011
Epoch 5/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9411 - accuracy: 0.8445 - val_loss: 1.7266 - val_accuracy: 0.9011
Epoch 6/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7738 - accuracy: 0.8445 - val_loss: 1.6053 - val_accuracy: 0.9011
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6710 - accuracy: 0.8445 - val_loss: 1.4979 - val_accuracy: 0.9011
Epoch 8/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5525 - accuracy: 0.8445 - val_loss: 1.3555 - val_accuracy: 0.9011
Epoch 9/100
2/2 [==============================] - 0s 54ms/step - loss: 1.4255 - accuracy: 0.8445 - val_loss: 1.2256 - val_accuracy: 0.9011
Epoch 10/100
2/2 [==============================] - 0s 48ms/step - loss: 1.2906 - accuracy: 0.8445 - val_loss: 1.1363 - val_accuracy: 0.9011
Epoch 11/100
2/2 [==============================] - 0s 24ms/step - loss: 1.2153 - accuracy: 0.8445 - val_loss: 1.1470 - val_accuracy: 0.9011
Epoch 12/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2280 - accuracy: 0.8445 - val_loss: 1.0706 - val_accuracy: 0.9011
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1318 - accuracy: 0.8445 - val_loss: 0.9810 - val_accuracy: 0.9011
Epoch 14/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0714 - accuracy: 0.8445 - val_loss: 1.0442 - val_accuracy: 0.9011
Epoch 15/100
2/2 [==============================] - 0s 48ms/step - loss: 1.1078 - accuracy: 0.8445 - val_loss: 0.9697 - val_accuracy: 0.9011
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0461 - accuracy: 0.8445 - val_loss: 0.9048 - val_accuracy: 0.9011
Epoch 17/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9975 - accuracy: 0.8445 - val_loss: 0.9498 - val_accuracy: 0.9011
Epoch 18/100
2/2 [==============================] - 0s 33ms/step - loss: 1.0271 - accuracy: 0.8445 - val_loss: 0.8851 - val_accuracy: 0.9011
Epoch 19/100
2/2 [==============================] - 0s 52ms/step - loss: 0.9660 - accuracy: 0.8445 - val_loss: 0.8728 - val_accuracy: 0.9011
Epoch 20/100
2/2 [==============================] - 0s 48ms/step - loss: 0.9672 - accuracy: 0.8445 - val_loss: 0.9297 - val_accuracy: 0.9011
Epoch 21/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9857 - accuracy: 0.8445 - val_loss: 0.8578 - val_accuracy: 0.9011
Epoch 22/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9545 - accuracy: 0.8445 - val_loss: 0.8566 - val_accuracy: 0.9011
Epoch 23/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9684 - accuracy: 0.8445 - val_loss: 0.8627 - val_accuracy: 0.9011
Epoch 24/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9448 - accuracy: 0.8445 - val_loss: 0.8644 - val_accuracy: 0.9011
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9246 - accuracy: 0.8445 - val_loss: 0.8052 - val_accuracy: 0.9011
Epoch 26/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8791 - accuracy: 0.8445 - val_loss: 0.8301 - val_accuracy: 0.9011
Epoch 27/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9165 - accuracy: 0.8445 - val_loss: 0.8400 - val_accuracy: 0.9011
Epoch 28/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8970 - accuracy: 0.8445 - val_loss: 0.8327 - val_accuracy: 0.9011
Epoch 29/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8995 - accuracy: 0.8445 - val_loss: 0.8827 - val_accuracy: 0.9011
Epoch 30/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9620 - accuracy: 0.8445 - val_loss: 0.8375 - val_accuracy: 0.9011
Epoch 31/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9006 - accuracy: 0.8445 - val_loss: 0.8259 - val_accuracy: 0.9011
Epoch 32/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8930 - accuracy: 0.8445 - val_loss: 0.8328 - val_accuracy: 0.9011
Epoch 33/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9154 - accuracy: 0.8445 - val_loss: 0.7948 - val_accuracy: 0.9011
Epoch 34/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8983 - accuracy: 0.8469 - val_loss: 0.8622 - val_accuracy: 0.9011
Epoch 35/100
2/2 [==============================] - 0s 51ms/step - loss: 0.9564 - accuracy: 0.8445 - val_loss: 0.8589 - val_accuracy: 0.9011
Epoch 36/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9233 - accuracy: 0.8445 - val_loss: 0.7976 - val_accuracy: 0.9011
Epoch 37/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8877 - accuracy: 0.8445 - val_loss: 0.8292 - val_accuracy: 0.9011
Epoch 38/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9073 - accuracy: 0.8457 - val_loss: 0.8305 - val_accuracy: 0.9011
Epoch 39/100
2/2 [==============================] - 0s 54ms/step - loss: 0.9049 - accuracy: 0.8445 - val_loss: 0.8374 - val_accuracy: 0.9011
Epoch 40/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9138 - accuracy: 0.8445 - val_loss: 0.8304 - val_accuracy: 0.9011
Epoch 41/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9126 - accuracy: 0.8505 - val_loss: 0.8194 - val_accuracy: 0.9011
Epoch 42/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9408 - accuracy: 0.8469 - val_loss: 0.8239 - val_accuracy: 0.9011
Epoch 43/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9077 - accuracy: 0.8445 - val_loss: 0.8335 - val_accuracy: 0.9011
Epoch 44/100
2/2 [==============================] - 0s 28ms/step - loss: 0.9099 - accuracy: 0.8433 - val_loss: 0.8738 - val_accuracy: 0.9011
Epoch 45/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9310 - accuracy: 0.8445 - val_loss: 0.8016 - val_accuracy: 0.9011
Epoch 46/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9073 - accuracy: 0.8433 - val_loss: 0.8104 - val_accuracy: 0.9121
Epoch 47/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8808 - accuracy: 0.8505 - val_loss: 0.8588 - val_accuracy: 0.9011
Epoch 48/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9256 - accuracy: 0.8481 - val_loss: 0.8176 - val_accuracy: 0.9011
Epoch 49/100
2/2 [==============================] - 0s 23ms/step - loss: 0.9003 - accuracy: 0.8433 - val_loss: 0.8149 - val_accuracy: 0.9011
Epoch 50/100
2/2 [==============================] - 0s 28ms/step - loss: 0.9195 - accuracy: 0.8420 - val_loss: 0.8768 - val_accuracy: 0.8901
Epoch 51/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9296 - accuracy: 0.8445 - val_loss: 0.8533 - val_accuracy: 0.9011
Epoch 52/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9099 - accuracy: 0.8445 - val_loss: 0.8344 - val_accuracy: 0.9011
Epoch 53/100
2/2 [==============================] - 0s 52ms/step - loss: 0.9085 - accuracy: 0.8445 - val_loss: 0.8090 - val_accuracy: 0.9011
Epoch 54/100
2/2 [==============================] - 0s 66ms/step - loss: 0.8996 - accuracy: 0.8530 - val_loss: 0.8344 - val_accuracy: 0.9011
Epoch 55/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9100 - accuracy: 0.8408 - val_loss: 0.7965 - val_accuracy: 0.9011
Epoch 56/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8833 - accuracy: 0.8518 - val_loss: 0.8289 - val_accuracy: 0.9011
Epoch 57/100
2/2 [==============================] - 0s 46ms/step - loss: 0.9222 - accuracy: 0.8445 - val_loss: 0.8297 - val_accuracy: 0.9011
Epoch 58/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8899 - accuracy: 0.8469 - val_loss: 0.8113 - val_accuracy: 0.9011
Epoch 59/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8891 - accuracy: 0.8433 - val_loss: 0.8427 - val_accuracy: 0.9011
Epoch 60/100
2/2 [==============================] - 0s 49ms/step - loss: 0.9183 - accuracy: 0.8433 - val_loss: 0.7911 - val_accuracy: 0.9011
Epoch 61/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8546 - accuracy: 0.8445 - val_loss: 0.7762 - val_accuracy: 0.9011
Epoch 62/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8645 - accuracy: 0.8530 - val_loss: 0.8332 - val_accuracy: 0.9011
Epoch 63/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9100 - accuracy: 0.8530 - val_loss: 0.7857 - val_accuracy: 0.9011
Epoch 64/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8561 - accuracy: 0.8530 - val_loss: 0.7877 - val_accuracy: 0.9121
Epoch 65/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8797 - accuracy: 0.8457 - val_loss: 0.7835 - val_accuracy: 0.9011
Epoch 66/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8931 - accuracy: 0.8433 - val_loss: 0.8005 - val_accuracy: 0.9011
Epoch 67/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8832 - accuracy: 0.8469 - val_loss: 0.8115 - val_accuracy: 0.8901
Epoch 68/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8723 - accuracy: 0.8481 - val_loss: 0.7987 - val_accuracy: 0.9011
Epoch 69/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8928 - accuracy: 0.8469 - val_loss: 0.7941 - val_accuracy: 0.9011
Epoch 70/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8851 - accuracy: 0.8445 - val_loss: 0.8075 - val_accuracy: 0.9011
Epoch 71/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8858 - accuracy: 0.8469 - val_loss: 0.8021 - val_accuracy: 0.9011
Epoch 72/100
2/2 [==============================] - 0s 52ms/step - loss: 0.8819 - accuracy: 0.8542 - val_loss: 0.8068 - val_accuracy: 0.9011
Epoch 73/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8953 - accuracy: 0.8457 - val_loss: 0.7993 - val_accuracy: 0.8901
Epoch 74/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8730 - accuracy: 0.8554 - val_loss: 0.8580 - val_accuracy: 0.9011
Epoch 75/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9248 - accuracy: 0.8445 - val_loss: 0.8080 - val_accuracy: 0.9011
Epoch 76/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8848 - accuracy: 0.8445 - val_loss: 0.8142 - val_accuracy: 0.9011
Epoch 77/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8925 - accuracy: 0.8433 - val_loss: 0.8510 - val_accuracy: 0.8901
Epoch 78/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9048 - accuracy: 0.8493 - val_loss: 0.7877 - val_accuracy: 0.9011
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8642 - accuracy: 0.8542 - val_loss: 0.7770 - val_accuracy: 0.9011
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8606 - accuracy: 0.8445 - val_loss: 0.8085 - val_accuracy: 0.9011
Epoch 81/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8953 - accuracy: 0.8408 - val_loss: 0.8063 - val_accuracy: 0.9011
Epoch 82/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8824 - accuracy: 0.8445 - val_loss: 0.8304 - val_accuracy: 0.9011
Epoch 83/100
2/2 [==============================] - 0s 49ms/step - loss: 0.9148 - accuracy: 0.8445 - val_loss: 0.8091 - val_accuracy: 0.9011
Epoch 84/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8732 - accuracy: 0.8469 - val_loss: 0.8000 - val_accuracy: 0.9011
Epoch 85/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8768 - accuracy: 0.8481 - val_loss: 0.7966 - val_accuracy: 0.9121
Epoch 86/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8894 - accuracy: 0.8348 - val_loss: 0.8073 - val_accuracy: 0.9011
Epoch 87/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9055 - accuracy: 0.8445 - val_loss: 0.8012 - val_accuracy: 0.9011
Epoch 88/100
2/2 [==============================] - 0s 56ms/step - loss: 0.8887 - accuracy: 0.8420 - val_loss: 0.7815 - val_accuracy: 0.9011
Epoch 89/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8733 - accuracy: 0.8578 - val_loss: 0.8262 - val_accuracy: 0.9011
Epoch 90/100
2/2 [==============================] - 0s 24ms/step - loss: 0.9097 - accuracy: 0.8469 - val_loss: 0.8130 - val_accuracy: 0.9011
Epoch 91/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8714 - accuracy: 0.8505 - val_loss: 0.7917 - val_accuracy: 0.9011
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8711 - accuracy: 0.8518 - val_loss: 0.8280 - val_accuracy: 0.9121
Epoch 93/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9202 - accuracy: 0.8518 - val_loss: 0.8339 - val_accuracy: 0.9121
Epoch 94/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8897 - accuracy: 0.8505 - val_loss: 0.8181 - val_accuracy: 0.9011
Epoch 95/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9084 - accuracy: 0.8493 - val_loss: 0.8234 - val_accuracy: 0.9011
Epoch 96/100
2/2 [==============================] - 0s 28ms/step - loss: 0.9152 - accuracy: 0.8469 - val_loss: 0.7982 - val_accuracy: 0.9011
Epoch 97/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8844 - accuracy: 0.8433 - val_loss: 0.8007 - val_accuracy: 0.9011
Epoch 98/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8781 - accuracy: 0.8433 - val_loss: 0.8067 - val_accuracy: 0.9011
Epoch 99/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9149 - accuracy: 0.8372 - val_loss: 0.8060 - val_accuracy: 0.9011
Epoch 100/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8752 - accuracy: 0.8493 - val_loss: 0.8226 - val_accuracy: 0.9011
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 224ms/step - loss: 6.8501 - accuracy: 0.4107 - val_loss: 2.7636 - val_accuracy: 0.8681
Epoch 2/100
2/2 [==============================] - 0s 42ms/step - loss: 2.6205 - accuracy: 0.8481 - val_loss: 2.6704 - val_accuracy: 0.8681
Epoch 3/100
2/2 [==============================] - 0s 32ms/step - loss: 2.8034 - accuracy: 0.8481 - val_loss: 2.8238 - val_accuracy: 0.8681
Epoch 4/100
2/2 [==============================] - 0s 52ms/step - loss: 2.7238 - accuracy: 0.8481 - val_loss: 2.1149 - val_accuracy: 0.8681
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0692 - accuracy: 0.8493 - val_loss: 1.7351 - val_accuracy: 0.8681
Epoch 6/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7415 - accuracy: 0.8518 - val_loss: 1.7073 - val_accuracy: 0.8681
Epoch 7/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7602 - accuracy: 0.8457 - val_loss: 1.6501 - val_accuracy: 0.8681
Epoch 8/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6694 - accuracy: 0.8493 - val_loss: 1.4181 - val_accuracy: 0.8681
Epoch 9/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4531 - accuracy: 0.8481 - val_loss: 1.2952 - val_accuracy: 0.8681
Epoch 10/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3330 - accuracy: 0.8481 - val_loss: 1.3325 - val_accuracy: 0.8681
Epoch 11/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3522 - accuracy: 0.8481 - val_loss: 1.2330 - val_accuracy: 0.8681
Epoch 12/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2391 - accuracy: 0.8481 - val_loss: 1.0902 - val_accuracy: 0.8681
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1277 - accuracy: 0.8481 - val_loss: 1.0505 - val_accuracy: 0.8681
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0763 - accuracy: 0.8481 - val_loss: 1.0466 - val_accuracy: 0.8681
Epoch 15/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0659 - accuracy: 0.8481 - val_loss: 1.0023 - val_accuracy: 0.8681
Epoch 16/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0206 - accuracy: 0.8481 - val_loss: 0.9310 - val_accuracy: 0.8681
Epoch 17/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9694 - accuracy: 0.8481 - val_loss: 0.9566 - val_accuracy: 0.8681
Epoch 18/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9699 - accuracy: 0.8481 - val_loss: 0.9141 - val_accuracy: 0.8681
Epoch 19/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9107 - accuracy: 0.8481 - val_loss: 0.8777 - val_accuracy: 0.8681
Epoch 20/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9150 - accuracy: 0.8481 - val_loss: 0.9303 - val_accuracy: 0.8681
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9228 - accuracy: 0.8493 - val_loss: 0.8735 - val_accuracy: 0.8681
Epoch 22/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8737 - accuracy: 0.8481 - val_loss: 0.8624 - val_accuracy: 0.8681
Epoch 23/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8717 - accuracy: 0.8505 - val_loss: 0.8962 - val_accuracy: 0.8681
Epoch 24/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8982 - accuracy: 0.8493 - val_loss: 0.8829 - val_accuracy: 0.8681
Epoch 25/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9006 - accuracy: 0.8505 - val_loss: 0.8751 - val_accuracy: 0.8681
Epoch 26/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8968 - accuracy: 0.8457 - val_loss: 0.8953 - val_accuracy: 0.8681
Epoch 27/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8839 - accuracy: 0.8420 - val_loss: 0.8632 - val_accuracy: 0.8681
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8809 - accuracy: 0.8469 - val_loss: 0.8340 - val_accuracy: 0.8681
Epoch 29/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8679 - accuracy: 0.8603 - val_loss: 0.8921 - val_accuracy: 0.8681
Epoch 30/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9058 - accuracy: 0.8566 - val_loss: 0.8284 - val_accuracy: 0.8681
Epoch 31/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8411 - accuracy: 0.8505 - val_loss: 0.8112 - val_accuracy: 0.8681
Epoch 32/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8335 - accuracy: 0.8481 - val_loss: 0.8843 - val_accuracy: 0.8681
Epoch 33/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8707 - accuracy: 0.8615 - val_loss: 0.8494 - val_accuracy: 0.8571
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8584 - accuracy: 0.8542 - val_loss: 0.8476 - val_accuracy: 0.8462
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8442 - accuracy: 0.8639 - val_loss: 0.8626 - val_accuracy: 0.8681
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8595 - accuracy: 0.8603 - val_loss: 0.8191 - val_accuracy: 0.8681
Epoch 37/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8180 - accuracy: 0.8493 - val_loss: 0.8051 - val_accuracy: 0.8681
Epoch 38/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8081 - accuracy: 0.8542 - val_loss: 0.8744 - val_accuracy: 0.8681
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8547 - accuracy: 0.8396 - val_loss: 0.8541 - val_accuracy: 0.8791
Epoch 40/100
2/2 [==============================] - 0s 60ms/step - loss: 0.8362 - accuracy: 0.8603 - val_loss: 0.8391 - val_accuracy: 0.8571
Epoch 41/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8184 - accuracy: 0.8663 - val_loss: 0.8600 - val_accuracy: 0.8681
Epoch 42/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8655 - accuracy: 0.8627 - val_loss: 0.9098 - val_accuracy: 0.8571
Epoch 43/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8700 - accuracy: 0.8469 - val_loss: 0.8381 - val_accuracy: 0.8681
Epoch 44/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8288 - accuracy: 0.8505 - val_loss: 0.8628 - val_accuracy: 0.8681
Epoch 45/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8692 - accuracy: 0.8603 - val_loss: 0.8502 - val_accuracy: 0.8571
Epoch 46/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8417 - accuracy: 0.8469 - val_loss: 0.8789 - val_accuracy: 0.8571
Epoch 47/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8385 - accuracy: 0.8530 - val_loss: 0.8445 - val_accuracy: 0.8681
Epoch 48/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8224 - accuracy: 0.8554 - val_loss: 0.8121 - val_accuracy: 0.8681
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8382 - accuracy: 0.8481 - val_loss: 0.8724 - val_accuracy: 0.8791
Epoch 50/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8664 - accuracy: 0.8530 - val_loss: 0.8857 - val_accuracy: 0.8681
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8676 - accuracy: 0.8445 - val_loss: 0.8556 - val_accuracy: 0.8681
Epoch 52/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8501 - accuracy: 0.8481 - val_loss: 0.8558 - val_accuracy: 0.8571
Epoch 53/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8505 - accuracy: 0.8578 - val_loss: 0.8661 - val_accuracy: 0.8462
Epoch 54/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8654 - accuracy: 0.8505 - val_loss: 0.8522 - val_accuracy: 0.8681
Epoch 55/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8271 - accuracy: 0.8578 - val_loss: 0.8344 - val_accuracy: 0.8681
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8296 - accuracy: 0.8518 - val_loss: 0.8482 - val_accuracy: 0.8791
Epoch 57/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8682 - accuracy: 0.8360 - val_loss: 0.8810 - val_accuracy: 0.8571
Epoch 58/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8792 - accuracy: 0.8469 - val_loss: 0.9014 - val_accuracy: 0.8352
Epoch 59/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8518 - accuracy: 0.8530 - val_loss: 0.8879 - val_accuracy: 0.8681
Epoch 60/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8920 - accuracy: 0.8518 - val_loss: 0.8773 - val_accuracy: 0.8681
Epoch 61/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8817 - accuracy: 0.8578 - val_loss: 0.8668 - val_accuracy: 0.8352
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8485 - accuracy: 0.8505 - val_loss: 0.9007 - val_accuracy: 0.8681
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8859 - accuracy: 0.8505 - val_loss: 0.8565 - val_accuracy: 0.8681
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8162 - accuracy: 0.8481 - val_loss: 0.8227 - val_accuracy: 0.8681
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8296 - accuracy: 0.8518 - val_loss: 0.8123 - val_accuracy: 0.8681
Epoch 66/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8105 - accuracy: 0.8469 - val_loss: 0.8009 - val_accuracy: 0.8571
Epoch 67/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8014 - accuracy: 0.8481 - val_loss: 0.8235 - val_accuracy: 0.8681
Epoch 68/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8400 - accuracy: 0.8542 - val_loss: 0.8317 - val_accuracy: 0.8462
Epoch 69/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8398 - accuracy: 0.8481 - val_loss: 0.8390 - val_accuracy: 0.8681
Epoch 70/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8356 - accuracy: 0.8530 - val_loss: 0.8515 - val_accuracy: 0.8681
Epoch 71/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8485 - accuracy: 0.8469 - val_loss: 0.8628 - val_accuracy: 0.8571
Epoch 72/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8409 - accuracy: 0.8639 - val_loss: 0.8565 - val_accuracy: 0.8681
Epoch 73/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8356 - accuracy: 0.8505 - val_loss: 0.8176 - val_accuracy: 0.8681
Epoch 74/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8161 - accuracy: 0.8518 - val_loss: 0.8398 - val_accuracy: 0.8571
Epoch 75/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8432 - accuracy: 0.8566 - val_loss: 0.8758 - val_accuracy: 0.8571
Epoch 76/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8376 - accuracy: 0.8615 - val_loss: 0.8345 - val_accuracy: 0.8681
Epoch 77/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8433 - accuracy: 0.8481 - val_loss: 0.8634 - val_accuracy: 0.8681
Epoch 78/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8673 - accuracy: 0.8493 - val_loss: 0.8406 - val_accuracy: 0.8681
Epoch 79/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8410 - accuracy: 0.8505 - val_loss: 0.8408 - val_accuracy: 0.8681
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8289 - accuracy: 0.8615 - val_loss: 0.8549 - val_accuracy: 0.8681
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8677 - accuracy: 0.8505 - val_loss: 0.8475 - val_accuracy: 0.8462
Epoch 82/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8278 - accuracy: 0.8542 - val_loss: 0.8334 - val_accuracy: 0.8681
Epoch 83/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8508 - accuracy: 0.8493 - val_loss: 0.8549 - val_accuracy: 0.8681
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8637 - accuracy: 0.8481 - val_loss: 0.8500 - val_accuracy: 0.8681
Epoch 85/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8288 - accuracy: 0.8627 - val_loss: 0.8824 - val_accuracy: 0.8571
Epoch 86/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8439 - accuracy: 0.8505 - val_loss: 0.8682 - val_accuracy: 0.8571
Epoch 87/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8553 - accuracy: 0.8578 - val_loss: 0.8557 - val_accuracy: 0.8681
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8541 - accuracy: 0.8481 - val_loss: 0.8308 - val_accuracy: 0.8681
Epoch 89/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8311 - accuracy: 0.8457 - val_loss: 0.8747 - val_accuracy: 0.8681
Epoch 90/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8251 - accuracy: 0.8663 - val_loss: 0.8465 - val_accuracy: 0.8571
Epoch 91/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8103 - accuracy: 0.8554 - val_loss: 0.8380 - val_accuracy: 0.8462
Epoch 92/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7882 - accuracy: 0.8676 - val_loss: 0.8306 - val_accuracy: 0.8681
Epoch 93/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8265 - accuracy: 0.8493 - val_loss: 0.8431 - val_accuracy: 0.8681
Epoch 94/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7979 - accuracy: 0.8639 - val_loss: 0.8165 - val_accuracy: 0.8571
Epoch 95/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7871 - accuracy: 0.8615 - val_loss: 0.8499 - val_accuracy: 0.8681
Epoch 96/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8287 - accuracy: 0.8481 - val_loss: 0.8642 - val_accuracy: 0.8462
Epoch 97/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8281 - accuracy: 0.8603 - val_loss: 0.8386 - val_accuracy: 0.8571
Epoch 98/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8215 - accuracy: 0.8530 - val_loss: 0.8545 - val_accuracy: 0.8681
Epoch 99/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8592 - accuracy: 0.8578 - val_loss: 0.8460 - val_accuracy: 0.8681
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8396 - accuracy: 0.8518 - val_loss: 0.8076 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 230ms/step - loss: 6.6034 - accuracy: 0.5273 - val_loss: 2.7389 - val_accuracy: 0.8901
Epoch 2/100
2/2 [==============================] - 0s 42ms/step - loss: 2.6105 - accuracy: 0.8457 - val_loss: 2.4939 - val_accuracy: 0.8901
Epoch 3/100
2/2 [==============================] - 0s 39ms/step - loss: 2.7176 - accuracy: 0.8457 - val_loss: 2.6219 - val_accuracy: 0.8901
Epoch 4/100
2/2 [==============================] - 0s 39ms/step - loss: 2.6345 - accuracy: 0.8591 - val_loss: 2.1108 - val_accuracy: 0.8791
Epoch 5/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1292 - accuracy: 0.8433 - val_loss: 1.6519 - val_accuracy: 0.8901
Epoch 6/100
2/2 [==============================] - 0s 46ms/step - loss: 1.7470 - accuracy: 0.8457 - val_loss: 1.5230 - val_accuracy: 0.8901
Epoch 7/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6934 - accuracy: 0.8457 - val_loss: 1.5045 - val_accuracy: 0.8901
Epoch 8/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5877 - accuracy: 0.8420 - val_loss: 1.3694 - val_accuracy: 0.9011
Epoch 9/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4302 - accuracy: 0.8408 - val_loss: 1.2108 - val_accuracy: 0.8901
Epoch 10/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2902 - accuracy: 0.8469 - val_loss: 1.2070 - val_accuracy: 0.8901
Epoch 11/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3052 - accuracy: 0.8457 - val_loss: 1.1140 - val_accuracy: 0.8901
Epoch 12/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2047 - accuracy: 0.8457 - val_loss: 0.9909 - val_accuracy: 0.8901
Epoch 13/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0916 - accuracy: 0.8457 - val_loss: 1.0713 - val_accuracy: 0.8901
Epoch 14/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1403 - accuracy: 0.8469 - val_loss: 0.9723 - val_accuracy: 0.8901
Epoch 15/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0526 - accuracy: 0.8469 - val_loss: 0.8971 - val_accuracy: 0.8901
Epoch 16/100
2/2 [==============================] - 0s 68ms/step - loss: 0.9772 - accuracy: 0.8469 - val_loss: 0.9166 - val_accuracy: 0.8901
Epoch 17/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9976 - accuracy: 0.8518 - val_loss: 0.9046 - val_accuracy: 0.8901
Epoch 18/100
2/2 [==============================] - 0s 33ms/step - loss: 1.0065 - accuracy: 0.8457 - val_loss: 0.8794 - val_accuracy: 0.8901
Epoch 19/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9695 - accuracy: 0.8481 - val_loss: 0.8177 - val_accuracy: 0.8901
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9277 - accuracy: 0.8469 - val_loss: 0.8455 - val_accuracy: 0.8901
Epoch 21/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9410 - accuracy: 0.8433 - val_loss: 0.8336 - val_accuracy: 0.8901
Epoch 22/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9166 - accuracy: 0.8457 - val_loss: 0.8479 - val_accuracy: 0.8901
Epoch 23/100
2/2 [==============================] - 0s 44ms/step - loss: 0.9101 - accuracy: 0.8505 - val_loss: 0.8417 - val_accuracy: 0.8901
Epoch 24/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9256 - accuracy: 0.8445 - val_loss: 0.8102 - val_accuracy: 0.8901
Epoch 25/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9002 - accuracy: 0.8493 - val_loss: 0.7999 - val_accuracy: 0.9011
Epoch 26/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8715 - accuracy: 0.8578 - val_loss: 0.7992 - val_accuracy: 0.8901
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8908 - accuracy: 0.8481 - val_loss: 0.8132 - val_accuracy: 0.8901
Epoch 28/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9210 - accuracy: 0.8433 - val_loss: 0.8175 - val_accuracy: 0.8901
Epoch 29/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8949 - accuracy: 0.8493 - val_loss: 0.8082 - val_accuracy: 0.8901
Epoch 30/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8887 - accuracy: 0.8457 - val_loss: 0.8077 - val_accuracy: 0.8901
Epoch 31/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9024 - accuracy: 0.8420 - val_loss: 0.8022 - val_accuracy: 0.9121
Epoch 32/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8879 - accuracy: 0.8518 - val_loss: 0.7911 - val_accuracy: 0.8901
Epoch 33/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9161 - accuracy: 0.8457 - val_loss: 0.7992 - val_accuracy: 0.8901
Epoch 34/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9074 - accuracy: 0.8481 - val_loss: 0.8078 - val_accuracy: 0.9011
Epoch 35/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9113 - accuracy: 0.8542 - val_loss: 0.7830 - val_accuracy: 0.8901
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9062 - accuracy: 0.8457 - val_loss: 0.7602 - val_accuracy: 0.8901
Epoch 37/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8522 - accuracy: 0.8457 - val_loss: 0.7915 - val_accuracy: 0.8901
Epoch 38/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8732 - accuracy: 0.8530 - val_loss: 0.8047 - val_accuracy: 0.9011
Epoch 39/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9056 - accuracy: 0.8627 - val_loss: 0.7576 - val_accuracy: 0.9011
Epoch 40/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8769 - accuracy: 0.8457 - val_loss: 0.7634 - val_accuracy: 0.8901
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8889 - accuracy: 0.8481 - val_loss: 0.8032 - val_accuracy: 0.8901
Epoch 42/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8853 - accuracy: 0.8323 - val_loss: 0.7947 - val_accuracy: 0.8901
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8699 - accuracy: 0.8457 - val_loss: 0.7830 - val_accuracy: 0.8901
Epoch 44/100
2/2 [==============================] - 0s 28ms/step - loss: 0.8629 - accuracy: 0.8493 - val_loss: 0.7549 - val_accuracy: 0.9011
Epoch 45/100
2/2 [==============================] - 0s 52ms/step - loss: 0.8553 - accuracy: 0.8591 - val_loss: 0.7932 - val_accuracy: 0.8901
Epoch 46/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8845 - accuracy: 0.8493 - val_loss: 0.7787 - val_accuracy: 0.9011
Epoch 47/100
2/2 [==============================] - 0s 63ms/step - loss: 0.8716 - accuracy: 0.8384 - val_loss: 0.7900 - val_accuracy: 0.8901
Epoch 48/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8756 - accuracy: 0.8530 - val_loss: 0.8048 - val_accuracy: 0.8901
Epoch 49/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9187 - accuracy: 0.8542 - val_loss: 0.8517 - val_accuracy: 0.8901
Epoch 50/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8947 - accuracy: 0.8627 - val_loss: 0.8400 - val_accuracy: 0.8901
Epoch 51/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8992 - accuracy: 0.8591 - val_loss: 0.7792 - val_accuracy: 0.8901
Epoch 52/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8735 - accuracy: 0.8469 - val_loss: 0.7971 - val_accuracy: 0.9121
Epoch 53/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8923 - accuracy: 0.8554 - val_loss: 0.8226 - val_accuracy: 0.9011
Epoch 54/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9062 - accuracy: 0.8578 - val_loss: 0.7719 - val_accuracy: 0.8901
Epoch 55/100
2/2 [==============================] - 0s 57ms/step - loss: 0.8819 - accuracy: 0.8469 - val_loss: 0.7664 - val_accuracy: 0.8901
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8649 - accuracy: 0.8433 - val_loss: 0.7880 - val_accuracy: 0.8901
Epoch 57/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8979 - accuracy: 0.8420 - val_loss: 0.7922 - val_accuracy: 0.8901
Epoch 58/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8851 - accuracy: 0.8396 - val_loss: 0.7997 - val_accuracy: 0.8901
Epoch 59/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8855 - accuracy: 0.8566 - val_loss: 0.8099 - val_accuracy: 0.8901
Epoch 60/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8923 - accuracy: 0.8433 - val_loss: 0.7716 - val_accuracy: 0.8901
Epoch 61/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8688 - accuracy: 0.8457 - val_loss: 0.8086 - val_accuracy: 0.8901
Epoch 62/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8891 - accuracy: 0.8518 - val_loss: 0.8060 - val_accuracy: 0.8901
Epoch 63/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8913 - accuracy: 0.8530 - val_loss: 0.7923 - val_accuracy: 0.8901
Epoch 64/100
2/2 [==============================] - 0s 57ms/step - loss: 0.8862 - accuracy: 0.8554 - val_loss: 0.7934 - val_accuracy: 0.8901
Epoch 65/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8680 - accuracy: 0.8530 - val_loss: 0.7940 - val_accuracy: 0.9011
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9069 - accuracy: 0.8554 - val_loss: 0.7896 - val_accuracy: 0.9011
Epoch 67/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8797 - accuracy: 0.8518 - val_loss: 0.8065 - val_accuracy: 0.8901
Epoch 68/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8827 - accuracy: 0.8469 - val_loss: 0.7926 - val_accuracy: 0.9011
Epoch 69/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8776 - accuracy: 0.8518 - val_loss: 0.8066 - val_accuracy: 0.8901
Epoch 70/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8631 - accuracy: 0.8518 - val_loss: 0.7797 - val_accuracy: 0.9011
Epoch 71/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8815 - accuracy: 0.8420 - val_loss: 0.7644 - val_accuracy: 0.8901
Epoch 72/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8599 - accuracy: 0.8420 - val_loss: 0.7548 - val_accuracy: 0.8901
Epoch 73/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8527 - accuracy: 0.8457 - val_loss: 0.7799 - val_accuracy: 0.8791
Epoch 74/100
2/2 [==============================] - 0s 52ms/step - loss: 0.8643 - accuracy: 0.8493 - val_loss: 0.7644 - val_accuracy: 0.9011
Epoch 75/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8359 - accuracy: 0.8530 - val_loss: 0.7796 - val_accuracy: 0.8901
Epoch 76/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8674 - accuracy: 0.8518 - val_loss: 0.7972 - val_accuracy: 0.8901
Epoch 77/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8750 - accuracy: 0.8505 - val_loss: 0.7710 - val_accuracy: 0.8901
Epoch 78/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8535 - accuracy: 0.8542 - val_loss: 0.7789 - val_accuracy: 0.8901
Epoch 79/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8522 - accuracy: 0.8518 - val_loss: 0.7837 - val_accuracy: 0.8901
Epoch 80/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8403 - accuracy: 0.8481 - val_loss: 0.7834 - val_accuracy: 0.8901
Epoch 81/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8591 - accuracy: 0.8505 - val_loss: 0.7575 - val_accuracy: 0.9011
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8370 - accuracy: 0.8505 - val_loss: 0.7495 - val_accuracy: 0.8901
Epoch 83/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8412 - accuracy: 0.8433 - val_loss: 0.7894 - val_accuracy: 0.8901
Epoch 84/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8742 - accuracy: 0.8396 - val_loss: 0.7525 - val_accuracy: 0.9011
Epoch 85/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8678 - accuracy: 0.8372 - val_loss: 0.7902 - val_accuracy: 0.8901
Epoch 86/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8708 - accuracy: 0.8469 - val_loss: 0.7818 - val_accuracy: 0.8901
Epoch 87/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8742 - accuracy: 0.8457 - val_loss: 0.7872 - val_accuracy: 0.8901
Epoch 88/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8546 - accuracy: 0.8481 - val_loss: 0.7492 - val_accuracy: 0.8901
Epoch 89/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8382 - accuracy: 0.8445 - val_loss: 0.7623 - val_accuracy: 0.8901
Epoch 90/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8468 - accuracy: 0.8457 - val_loss: 0.7489 - val_accuracy: 0.8901
Epoch 91/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8334 - accuracy: 0.8518 - val_loss: 0.7479 - val_accuracy: 0.8901
Epoch 92/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8542 - accuracy: 0.8469 - val_loss: 0.7909 - val_accuracy: 0.8901
Epoch 93/100
2/2 [==============================] - 0s 53ms/step - loss: 0.8535 - accuracy: 0.8578 - val_loss: 0.7710 - val_accuracy: 0.8901
Epoch 94/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8376 - accuracy: 0.8408 - val_loss: 0.7564 - val_accuracy: 0.8901
Epoch 95/100
2/2 [==============================] - 0s 26ms/step - loss: 0.8662 - accuracy: 0.8420 - val_loss: 0.7874 - val_accuracy: 0.8901
Epoch 96/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8639 - accuracy: 0.8457 - val_loss: 0.7418 - val_accuracy: 0.8901
Epoch 97/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8304 - accuracy: 0.8457 - val_loss: 0.7863 - val_accuracy: 0.8901
Epoch 98/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8515 - accuracy: 0.8457 - val_loss: 0.7671 - val_accuracy: 0.8901
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8542 - accuracy: 0.8445 - val_loss: 0.7929 - val_accuracy: 0.8901
Epoch 100/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8576 - accuracy: 0.8457 - val_loss: 0.7703 - val_accuracy: 0.8901
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 231ms/step - loss: 7.0000 - accuracy: 0.5091 - val_loss: 2.9063 - val_accuracy: 0.8352
Epoch 2/100
2/2 [==============================] - 0s 33ms/step - loss: 2.6250 - accuracy: 0.8518 - val_loss: 2.7943 - val_accuracy: 0.8352
Epoch 3/100
2/2 [==============================] - 0s 43ms/step - loss: 2.8199 - accuracy: 0.8518 - val_loss: 2.8652 - val_accuracy: 0.8352
Epoch 4/100
2/2 [==============================] - 0s 35ms/step - loss: 2.6914 - accuracy: 0.8518 - val_loss: 2.1504 - val_accuracy: 0.8352
Epoch 5/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0323 - accuracy: 0.8505 - val_loss: 1.8313 - val_accuracy: 0.8352
Epoch 6/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7539 - accuracy: 0.8530 - val_loss: 1.8280 - val_accuracy: 0.8352
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7722 - accuracy: 0.8518 - val_loss: 1.7283 - val_accuracy: 0.8352
Epoch 8/100
2/2 [==============================] - 0s 50ms/step - loss: 1.6366 - accuracy: 0.8505 - val_loss: 1.5714 - val_accuracy: 0.8352
Epoch 9/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4924 - accuracy: 0.8505 - val_loss: 1.4361 - val_accuracy: 0.8352
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3744 - accuracy: 0.8518 - val_loss: 1.3621 - val_accuracy: 0.8352
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2901 - accuracy: 0.8505 - val_loss: 1.2999 - val_accuracy: 0.8352
Epoch 12/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2328 - accuracy: 0.8518 - val_loss: 1.2167 - val_accuracy: 0.8352
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1711 - accuracy: 0.8518 - val_loss: 1.1324 - val_accuracy: 0.8352
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0886 - accuracy: 0.8518 - val_loss: 1.1317 - val_accuracy: 0.8352
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0736 - accuracy: 0.8530 - val_loss: 1.0894 - val_accuracy: 0.8352
Epoch 16/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0274 - accuracy: 0.8518 - val_loss: 1.0124 - val_accuracy: 0.8352
Epoch 17/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9796 - accuracy: 0.8518 - val_loss: 1.0710 - val_accuracy: 0.8352
Epoch 18/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9966 - accuracy: 0.8518 - val_loss: 0.9752 - val_accuracy: 0.8352
Epoch 19/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9304 - accuracy: 0.8566 - val_loss: 0.9562 - val_accuracy: 0.8352
Epoch 20/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9163 - accuracy: 0.8554 - val_loss: 1.0151 - val_accuracy: 0.8352
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9508 - accuracy: 0.8518 - val_loss: 0.9850 - val_accuracy: 0.8352
Epoch 22/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9365 - accuracy: 0.8493 - val_loss: 0.9502 - val_accuracy: 0.8352
Epoch 23/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9228 - accuracy: 0.8578 - val_loss: 0.9259 - val_accuracy: 0.8352
Epoch 24/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9155 - accuracy: 0.8518 - val_loss: 0.9713 - val_accuracy: 0.8352
Epoch 25/100
2/2 [==============================] - 0s 30ms/step - loss: 0.9229 - accuracy: 0.8493 - val_loss: 0.9602 - val_accuracy: 0.8352
Epoch 26/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9164 - accuracy: 0.8518 - val_loss: 0.9691 - val_accuracy: 0.8352
Epoch 27/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9303 - accuracy: 0.8530 - val_loss: 0.9460 - val_accuracy: 0.8242
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8960 - accuracy: 0.8530 - val_loss: 0.9669 - val_accuracy: 0.8352
Epoch 29/100
2/2 [==============================] - 0s 48ms/step - loss: 0.9141 - accuracy: 0.8591 - val_loss: 0.9446 - val_accuracy: 0.8352
Epoch 30/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8790 - accuracy: 0.8530 - val_loss: 0.9013 - val_accuracy: 0.8352
Epoch 31/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8645 - accuracy: 0.8518 - val_loss: 0.9110 - val_accuracy: 0.8352
Epoch 32/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8831 - accuracy: 0.8530 - val_loss: 0.9344 - val_accuracy: 0.8352
Epoch 33/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8688 - accuracy: 0.8518 - val_loss: 0.9409 - val_accuracy: 0.8352
Epoch 34/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8727 - accuracy: 0.8518 - val_loss: 0.8995 - val_accuracy: 0.8352
Epoch 35/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8457 - accuracy: 0.8530 - val_loss: 0.8989 - val_accuracy: 0.8352
Epoch 36/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8602 - accuracy: 0.8566 - val_loss: 0.8967 - val_accuracy: 0.8242
Epoch 37/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8326 - accuracy: 0.8615 - val_loss: 0.8932 - val_accuracy: 0.8242
Epoch 38/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8376 - accuracy: 0.8700 - val_loss: 0.9465 - val_accuracy: 0.8352
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8878 - accuracy: 0.8542 - val_loss: 0.8975 - val_accuracy: 0.8352
Epoch 40/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8396 - accuracy: 0.8505 - val_loss: 0.8734 - val_accuracy: 0.8352
Epoch 41/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8517 - accuracy: 0.8530 - val_loss: 0.9053 - val_accuracy: 0.8352
Epoch 42/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8423 - accuracy: 0.8530 - val_loss: 0.9392 - val_accuracy: 0.8352
Epoch 43/100
2/2 [==============================] - 0s 69ms/step - loss: 0.8792 - accuracy: 0.8518 - val_loss: 0.9173 - val_accuracy: 0.8352
Epoch 44/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8536 - accuracy: 0.8481 - val_loss: 0.9433 - val_accuracy: 0.8352
Epoch 45/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8835 - accuracy: 0.8530 - val_loss: 0.9038 - val_accuracy: 0.8352
Epoch 46/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8741 - accuracy: 0.8542 - val_loss: 0.9404 - val_accuracy: 0.8352
Epoch 47/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8946 - accuracy: 0.8505 - val_loss: 0.9467 - val_accuracy: 0.8352
Epoch 48/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8691 - accuracy: 0.8663 - val_loss: 0.9369 - val_accuracy: 0.8242
Epoch 49/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8780 - accuracy: 0.8542 - val_loss: 0.9552 - val_accuracy: 0.8352
Epoch 50/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8647 - accuracy: 0.8493 - val_loss: 0.8894 - val_accuracy: 0.8352
Epoch 51/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8646 - accuracy: 0.8493 - val_loss: 0.9216 - val_accuracy: 0.8352
Epoch 52/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8626 - accuracy: 0.8518 - val_loss: 0.9368 - val_accuracy: 0.8352
Epoch 53/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8753 - accuracy: 0.8542 - val_loss: 0.9132 - val_accuracy: 0.8462
Epoch 54/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8651 - accuracy: 0.8591 - val_loss: 0.9245 - val_accuracy: 0.8352
Epoch 55/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8529 - accuracy: 0.8505 - val_loss: 0.8776 - val_accuracy: 0.8352
Epoch 56/100
2/2 [==============================] - 0s 52ms/step - loss: 0.8331 - accuracy: 0.8627 - val_loss: 0.9316 - val_accuracy: 0.8352
Epoch 57/100
2/2 [==============================] - 0s 52ms/step - loss: 0.8694 - accuracy: 0.8615 - val_loss: 0.9287 - val_accuracy: 0.8352
Epoch 58/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8587 - accuracy: 0.8639 - val_loss: 0.9156 - val_accuracy: 0.8352
Epoch 59/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8603 - accuracy: 0.8615 - val_loss: 0.9191 - val_accuracy: 0.8352
Epoch 60/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8630 - accuracy: 0.8578 - val_loss: 0.9123 - val_accuracy: 0.8352
Epoch 61/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8411 - accuracy: 0.8566 - val_loss: 0.8877 - val_accuracy: 0.8352
Epoch 62/100
2/2 [==============================] - 0s 28ms/step - loss: 0.8291 - accuracy: 0.8518 - val_loss: 0.9139 - val_accuracy: 0.8352
Epoch 63/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8589 - accuracy: 0.8518 - val_loss: 0.8813 - val_accuracy: 0.8352
Epoch 64/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8380 - accuracy: 0.8518 - val_loss: 0.8820 - val_accuracy: 0.8352
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8431 - accuracy: 0.8518 - val_loss: 0.8927 - val_accuracy: 0.8352
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8339 - accuracy: 0.8518 - val_loss: 0.8935 - val_accuracy: 0.8352
Epoch 67/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8523 - accuracy: 0.8530 - val_loss: 0.8776 - val_accuracy: 0.8352
Epoch 68/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8455 - accuracy: 0.8518 - val_loss: 0.8971 - val_accuracy: 0.8352
Epoch 69/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8521 - accuracy: 0.8518 - val_loss: 0.8848 - val_accuracy: 0.8352
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8433 - accuracy: 0.8518 - val_loss: 0.8934 - val_accuracy: 0.8352
Epoch 71/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8571 - accuracy: 0.8518 - val_loss: 0.8923 - val_accuracy: 0.8352
Epoch 72/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8402 - accuracy: 0.8518 - val_loss: 0.8690 - val_accuracy: 0.8352
Epoch 73/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8339 - accuracy: 0.8518 - val_loss: 0.8919 - val_accuracy: 0.8352
Epoch 74/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8603 - accuracy: 0.8518 - val_loss: 0.9413 - val_accuracy: 0.8352
Epoch 75/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8979 - accuracy: 0.8505 - val_loss: 0.8925 - val_accuracy: 0.8352
Epoch 76/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8424 - accuracy: 0.8518 - val_loss: 0.9256 - val_accuracy: 0.8352
Epoch 77/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8630 - accuracy: 0.8518 - val_loss: 0.9314 - val_accuracy: 0.8352
Epoch 78/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8727 - accuracy: 0.8518 - val_loss: 0.8872 - val_accuracy: 0.8352
Epoch 79/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8467 - accuracy: 0.8518 - val_loss: 0.8858 - val_accuracy: 0.8352
Epoch 80/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8512 - accuracy: 0.8518 - val_loss: 0.9406 - val_accuracy: 0.8352
Epoch 81/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8728 - accuracy: 0.8518 - val_loss: 0.9163 - val_accuracy: 0.8352
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8455 - accuracy: 0.8518 - val_loss: 0.8896 - val_accuracy: 0.8352
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8547 - accuracy: 0.8530 - val_loss: 0.8913 - val_accuracy: 0.8352
Epoch 84/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8612 - accuracy: 0.8518 - val_loss: 0.9171 - val_accuracy: 0.8352
Epoch 85/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8501 - accuracy: 0.8530 - val_loss: 0.8977 - val_accuracy: 0.8352
Epoch 86/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8649 - accuracy: 0.8493 - val_loss: 0.9497 - val_accuracy: 0.8352
Epoch 87/100
2/2 [==============================] - 0s 53ms/step - loss: 0.9048 - accuracy: 0.8505 - val_loss: 0.9161 - val_accuracy: 0.8352
Epoch 88/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8734 - accuracy: 0.8518 - val_loss: 0.9084 - val_accuracy: 0.8352
Epoch 89/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8762 - accuracy: 0.8518 - val_loss: 0.9175 - val_accuracy: 0.8352
Epoch 90/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8989 - accuracy: 0.8518 - val_loss: 0.8989 - val_accuracy: 0.8352
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8660 - accuracy: 0.8518 - val_loss: 0.9194 - val_accuracy: 0.8352
Epoch 92/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8891 - accuracy: 0.8518 - val_loss: 0.8904 - val_accuracy: 0.8352
Epoch 93/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8546 - accuracy: 0.8518 - val_loss: 0.9038 - val_accuracy: 0.8352
Epoch 94/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8551 - accuracy: 0.8518 - val_loss: 0.8940 - val_accuracy: 0.8352
Epoch 95/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8788 - accuracy: 0.8518 - val_loss: 0.9307 - val_accuracy: 0.8352
Epoch 96/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9095 - accuracy: 0.8518 - val_loss: 0.8869 - val_accuracy: 0.8352
Epoch 97/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8584 - accuracy: 0.8518 - val_loss: 0.8976 - val_accuracy: 0.8352
Epoch 98/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8653 - accuracy: 0.8518 - val_loss: 0.9425 - val_accuracy: 0.8352
Epoch 99/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8780 - accuracy: 0.8518 - val_loss: 0.8945 - val_accuracy: 0.8352
Epoch 100/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8707 - accuracy: 0.8518 - val_loss: 0.9001 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Experiment number: 5
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 224ms/step - loss: 2.9647 - accuracy: 0.4599 - val_loss: 2.8495 - val_accuracy: 0.3913
Epoch 2/100
2/2 [==============================] - 0s 50ms/step - loss: 2.9499 - accuracy: 0.4526 - val_loss: 2.8481 - val_accuracy: 0.3913
Epoch 3/100
2/2 [==============================] - 0s 34ms/step - loss: 2.9938 - accuracy: 0.4416 - val_loss: 2.8458 - val_accuracy: 0.3913
Epoch 4/100
2/2 [==============================] - 0s 37ms/step - loss: 2.9797 - accuracy: 0.4453 - val_loss: 2.8427 - val_accuracy: 0.3913
Epoch 5/100
2/2 [==============================] - 0s 45ms/step - loss: 2.9638 - accuracy: 0.4428 - val_loss: 2.8388 - val_accuracy: 0.3913
Epoch 6/100
2/2 [==============================] - 0s 34ms/step - loss: 2.9621 - accuracy: 0.4526 - val_loss: 2.8341 - val_accuracy: 0.4022
Epoch 7/100
2/2 [==============================] - 0s 33ms/step - loss: 2.9506 - accuracy: 0.4258 - val_loss: 2.8287 - val_accuracy: 0.4022
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 2.9471 - accuracy: 0.4659 - val_loss: 2.8226 - val_accuracy: 0.4130
Epoch 9/100
2/2 [==============================] - 0s 50ms/step - loss: 2.9314 - accuracy: 0.4793 - val_loss: 2.8158 - val_accuracy: 0.4130
Epoch 10/100
2/2 [==============================] - 0s 49ms/step - loss: 2.9418 - accuracy: 0.4392 - val_loss: 2.8084 - val_accuracy: 0.4239
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 2.9073 - accuracy: 0.4635 - val_loss: 2.8003 - val_accuracy: 0.4239
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 2.9138 - accuracy: 0.4623 - val_loss: 2.7916 - val_accuracy: 0.4348
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 2.9065 - accuracy: 0.4672 - val_loss: 2.7823 - val_accuracy: 0.4348
Epoch 14/100
2/2 [==============================] - 0s 36ms/step - loss: 2.8906 - accuracy: 0.4805 - val_loss: 2.7725 - val_accuracy: 0.4457
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8791 - accuracy: 0.4672 - val_loss: 2.7621 - val_accuracy: 0.4565
Epoch 16/100
2/2 [==============================] - 0s 35ms/step - loss: 2.8742 - accuracy: 0.4781 - val_loss: 2.7512 - val_accuracy: 0.4565
Epoch 17/100
2/2 [==============================] - 0s 32ms/step - loss: 2.8489 - accuracy: 0.4976 - val_loss: 2.7398 - val_accuracy: 0.4565
Epoch 18/100
2/2 [==============================] - 0s 33ms/step - loss: 2.8546 - accuracy: 0.4891 - val_loss: 2.7279 - val_accuracy: 0.4783
Epoch 19/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8725 - accuracy: 0.4830 - val_loss: 2.7156 - val_accuracy: 0.5109
Epoch 20/100
2/2 [==============================] - 0s 36ms/step - loss: 2.8341 - accuracy: 0.4842 - val_loss: 2.7029 - val_accuracy: 0.5217
Epoch 21/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8045 - accuracy: 0.5146 - val_loss: 2.6898 - val_accuracy: 0.5326
Epoch 22/100
2/2 [==============================] - 0s 38ms/step - loss: 2.7996 - accuracy: 0.5170 - val_loss: 2.6763 - val_accuracy: 0.5326
Epoch 23/100
2/2 [==============================] - 0s 46ms/step - loss: 2.7912 - accuracy: 0.5255 - val_loss: 2.6625 - val_accuracy: 0.5435
Epoch 24/100
2/2 [==============================] - 0s 40ms/step - loss: 2.7668 - accuracy: 0.5316 - val_loss: 2.6484 - val_accuracy: 0.5761
Epoch 25/100
2/2 [==============================] - 0s 47ms/step - loss: 2.7491 - accuracy: 0.5560 - val_loss: 2.6341 - val_accuracy: 0.5761
Epoch 26/100
2/2 [==============================] - 0s 40ms/step - loss: 2.7325 - accuracy: 0.5511 - val_loss: 2.6194 - val_accuracy: 0.5870
Epoch 27/100
2/2 [==============================] - 0s 34ms/step - loss: 2.7299 - accuracy: 0.5328 - val_loss: 2.6045 - val_accuracy: 0.5870
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 2.7008 - accuracy: 0.5693 - val_loss: 2.5894 - val_accuracy: 0.6087
Epoch 29/100
2/2 [==============================] - 0s 32ms/step - loss: 2.6536 - accuracy: 0.5827 - val_loss: 2.5742 - val_accuracy: 0.6196
Epoch 30/100
2/2 [==============================] - 0s 40ms/step - loss: 2.6852 - accuracy: 0.5633 - val_loss: 2.5587 - val_accuracy: 0.6196
Epoch 31/100
2/2 [==============================] - 0s 36ms/step - loss: 2.6679 - accuracy: 0.5827 - val_loss: 2.5432 - val_accuracy: 0.6413
Epoch 32/100
2/2 [==============================] - 0s 38ms/step - loss: 2.6419 - accuracy: 0.5985 - val_loss: 2.5275 - val_accuracy: 0.6522
Epoch 33/100
2/2 [==============================] - 0s 34ms/step - loss: 2.6280 - accuracy: 0.6010 - val_loss: 2.5117 - val_accuracy: 0.6739
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 2.5964 - accuracy: 0.6058 - val_loss: 2.4958 - val_accuracy: 0.7065
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 2.5822 - accuracy: 0.6168 - val_loss: 2.4798 - val_accuracy: 0.7174
Epoch 36/100
2/2 [==============================] - 0s 72ms/step - loss: 2.5809 - accuracy: 0.6375 - val_loss: 2.4638 - val_accuracy: 0.7283
Epoch 37/100
2/2 [==============================] - 0s 32ms/step - loss: 2.5450 - accuracy: 0.6399 - val_loss: 2.4477 - val_accuracy: 0.7391
Epoch 38/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5365 - accuracy: 0.6655 - val_loss: 2.4316 - val_accuracy: 0.7500
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 2.4978 - accuracy: 0.6764 - val_loss: 2.4155 - val_accuracy: 0.7609
Epoch 40/100
2/2 [==============================] - 0s 35ms/step - loss: 2.4983 - accuracy: 0.6655 - val_loss: 2.3994 - val_accuracy: 0.7717
Epoch 41/100
2/2 [==============================] - 0s 50ms/step - loss: 2.4829 - accuracy: 0.6642 - val_loss: 2.3833 - val_accuracy: 0.7826
Epoch 42/100
2/2 [==============================] - 0s 41ms/step - loss: 2.4546 - accuracy: 0.6715 - val_loss: 2.3672 - val_accuracy: 0.7826
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 2.4543 - accuracy: 0.6825 - val_loss: 2.3511 - val_accuracy: 0.7826
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 2.4190 - accuracy: 0.6946 - val_loss: 2.3351 - val_accuracy: 0.7826
Epoch 45/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3972 - accuracy: 0.7056 - val_loss: 2.3191 - val_accuracy: 0.7826
Epoch 46/100
2/2 [==============================] - 0s 49ms/step - loss: 2.3738 - accuracy: 0.7263 - val_loss: 2.3031 - val_accuracy: 0.7826
Epoch 47/100
2/2 [==============================] - 0s 31ms/step - loss: 2.3870 - accuracy: 0.6983 - val_loss: 2.2873 - val_accuracy: 0.7935
Epoch 48/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3657 - accuracy: 0.7141 - val_loss: 2.2715 - val_accuracy: 0.8043
Epoch 49/100
2/2 [==============================] - 0s 40ms/step - loss: 2.3366 - accuracy: 0.7287 - val_loss: 2.2557 - val_accuracy: 0.8043
Epoch 50/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3037 - accuracy: 0.7409 - val_loss: 2.2401 - val_accuracy: 0.8043
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3332 - accuracy: 0.7275 - val_loss: 2.2246 - val_accuracy: 0.8043
Epoch 52/100
2/2 [==============================] - 0s 38ms/step - loss: 2.2920 - accuracy: 0.7506 - val_loss: 2.2091 - val_accuracy: 0.8043
Epoch 53/100
2/2 [==============================] - 0s 35ms/step - loss: 2.2757 - accuracy: 0.7372 - val_loss: 2.1937 - val_accuracy: 0.8043
Epoch 54/100
2/2 [==============================] - 0s 36ms/step - loss: 2.2581 - accuracy: 0.7652 - val_loss: 2.1784 - val_accuracy: 0.8043
Epoch 55/100
2/2 [==============================] - 0s 47ms/step - loss: 2.2467 - accuracy: 0.7518 - val_loss: 2.1632 - val_accuracy: 0.8043
Epoch 56/100
2/2 [==============================] - 0s 30ms/step - loss: 2.2229 - accuracy: 0.7774 - val_loss: 2.1482 - val_accuracy: 0.8043
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 2.2108 - accuracy: 0.7628 - val_loss: 2.1332 - val_accuracy: 0.8152
Epoch 58/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1830 - accuracy: 0.7859 - val_loss: 2.1183 - val_accuracy: 0.8261
Epoch 59/100
2/2 [==============================] - 0s 44ms/step - loss: 2.1703 - accuracy: 0.7859 - val_loss: 2.1036 - val_accuracy: 0.8370
Epoch 60/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1505 - accuracy: 0.7810 - val_loss: 2.0889 - val_accuracy: 0.8370
Epoch 61/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1383 - accuracy: 0.7981 - val_loss: 2.0744 - val_accuracy: 0.8370
Epoch 62/100
2/2 [==============================] - 0s 45ms/step - loss: 2.1048 - accuracy: 0.8041 - val_loss: 2.0600 - val_accuracy: 0.8370
Epoch 63/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1131 - accuracy: 0.7993 - val_loss: 2.0458 - val_accuracy: 0.8370
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0798 - accuracy: 0.8005 - val_loss: 2.0316 - val_accuracy: 0.8370
Epoch 65/100
2/2 [==============================] - 0s 36ms/step - loss: 2.0811 - accuracy: 0.8090 - val_loss: 2.0176 - val_accuracy: 0.8370
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0664 - accuracy: 0.8151 - val_loss: 2.0036 - val_accuracy: 0.8370
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0574 - accuracy: 0.8127 - val_loss: 1.9898 - val_accuracy: 0.8370
Epoch 68/100
2/2 [==============================] - 0s 28ms/step - loss: 2.0327 - accuracy: 0.8200 - val_loss: 1.9761 - val_accuracy: 0.8370
Epoch 69/100
2/2 [==============================] - 0s 31ms/step - loss: 2.0187 - accuracy: 0.8273 - val_loss: 1.9626 - val_accuracy: 0.8370
Epoch 70/100
2/2 [==============================] - 0s 32ms/step - loss: 2.0221 - accuracy: 0.8114 - val_loss: 1.9491 - val_accuracy: 0.8370
Epoch 71/100
2/2 [==============================] - 0s 52ms/step - loss: 1.9920 - accuracy: 0.8260 - val_loss: 1.9357 - val_accuracy: 0.8370
Epoch 72/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9847 - accuracy: 0.8309 - val_loss: 1.9225 - val_accuracy: 0.8370
Epoch 73/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9455 - accuracy: 0.8394 - val_loss: 1.9094 - val_accuracy: 0.8370
Epoch 74/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9559 - accuracy: 0.8260 - val_loss: 1.8964 - val_accuracy: 0.8370
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9380 - accuracy: 0.8309 - val_loss: 1.8835 - val_accuracy: 0.8370
Epoch 76/100
2/2 [==============================] - 0s 44ms/step - loss: 1.9064 - accuracy: 0.8479 - val_loss: 1.8707 - val_accuracy: 0.8370
Epoch 77/100
2/2 [==============================] - 0s 48ms/step - loss: 1.8987 - accuracy: 0.8382 - val_loss: 1.8580 - val_accuracy: 0.8370
Epoch 78/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9003 - accuracy: 0.8370 - val_loss: 1.8455 - val_accuracy: 0.8370
Epoch 79/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8971 - accuracy: 0.8370 - val_loss: 1.8330 - val_accuracy: 0.8370
Epoch 80/100
2/2 [==============================] - 0s 44ms/step - loss: 1.8664 - accuracy: 0.8418 - val_loss: 1.8207 - val_accuracy: 0.8370
Epoch 81/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8536 - accuracy: 0.8394 - val_loss: 1.8084 - val_accuracy: 0.8370
Epoch 82/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8502 - accuracy: 0.8418 - val_loss: 1.7963 - val_accuracy: 0.8370
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8302 - accuracy: 0.8431 - val_loss: 1.7843 - val_accuracy: 0.8370
Epoch 84/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8035 - accuracy: 0.8382 - val_loss: 1.7724 - val_accuracy: 0.8370
Epoch 85/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7988 - accuracy: 0.8467 - val_loss: 1.7605 - val_accuracy: 0.8370
Epoch 86/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7922 - accuracy: 0.8491 - val_loss: 1.7488 - val_accuracy: 0.8370
Epoch 87/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7746 - accuracy: 0.8455 - val_loss: 1.7371 - val_accuracy: 0.8370
Epoch 88/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7660 - accuracy: 0.8418 - val_loss: 1.7256 - val_accuracy: 0.8370
Epoch 89/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7598 - accuracy: 0.8467 - val_loss: 1.7141 - val_accuracy: 0.8370
Epoch 90/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7353 - accuracy: 0.8491 - val_loss: 1.7028 - val_accuracy: 0.8370
Epoch 91/100
2/2 [==============================] - 0s 45ms/step - loss: 1.7377 - accuracy: 0.8455 - val_loss: 1.6915 - val_accuracy: 0.8370
Epoch 92/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7171 - accuracy: 0.8443 - val_loss: 1.6803 - val_accuracy: 0.8370
Epoch 93/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6972 - accuracy: 0.8516 - val_loss: 1.6692 - val_accuracy: 0.8370
Epoch 94/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7012 - accuracy: 0.8467 - val_loss: 1.6582 - val_accuracy: 0.8370
Epoch 95/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6794 - accuracy: 0.8431 - val_loss: 1.6473 - val_accuracy: 0.8370
Epoch 96/100
2/2 [==============================] - 0s 28ms/step - loss: 1.6762 - accuracy: 0.8504 - val_loss: 1.6364 - val_accuracy: 0.8370
Epoch 97/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6693 - accuracy: 0.8479 - val_loss: 1.6257 - val_accuracy: 0.8370
Epoch 98/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6468 - accuracy: 0.8491 - val_loss: 1.6151 - val_accuracy: 0.8370
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6444 - accuracy: 0.8479 - val_loss: 1.6045 - val_accuracy: 0.8370
Epoch 100/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6277 - accuracy: 0.8479 - val_loss: 1.5940 - val_accuracy: 0.8370
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 242ms/step - loss: 3.3041 - accuracy: 0.4002 - val_loss: 3.3686 - val_accuracy: 0.3370
Epoch 2/100
2/2 [==============================] - 0s 50ms/step - loss: 3.2953 - accuracy: 0.4002 - val_loss: 3.3662 - val_accuracy: 0.3370
Epoch 3/100
2/2 [==============================] - 0s 27ms/step - loss: 3.3232 - accuracy: 0.3942 - val_loss: 3.3626 - val_accuracy: 0.3370
Epoch 4/100
2/2 [==============================] - 0s 86ms/step - loss: 3.2691 - accuracy: 0.4331 - val_loss: 3.3576 - val_accuracy: 0.3370
Epoch 5/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2608 - accuracy: 0.3917 - val_loss: 3.3514 - val_accuracy: 0.3370
Epoch 6/100
2/2 [==============================] - 0s 53ms/step - loss: 3.2445 - accuracy: 0.4088 - val_loss: 3.3440 - val_accuracy: 0.3370
Epoch 7/100
2/2 [==============================] - 0s 35ms/step - loss: 3.2921 - accuracy: 0.4112 - val_loss: 3.3355 - val_accuracy: 0.3478
Epoch 8/100
2/2 [==============================] - 0s 31ms/step - loss: 3.2316 - accuracy: 0.4075 - val_loss: 3.3259 - val_accuracy: 0.3587
Epoch 9/100
2/2 [==============================] - 0s 36ms/step - loss: 3.2271 - accuracy: 0.4343 - val_loss: 3.3152 - val_accuracy: 0.3696
Epoch 10/100
2/2 [==============================] - 0s 48ms/step - loss: 3.2222 - accuracy: 0.4221 - val_loss: 3.3036 - val_accuracy: 0.3696
Epoch 11/100
2/2 [==============================] - 0s 34ms/step - loss: 3.2343 - accuracy: 0.4258 - val_loss: 3.2909 - val_accuracy: 0.3587
Epoch 12/100
2/2 [==============================] - 0s 34ms/step - loss: 3.2209 - accuracy: 0.4002 - val_loss: 3.2773 - val_accuracy: 0.3587
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 3.1820 - accuracy: 0.4331 - val_loss: 3.2628 - val_accuracy: 0.3696
Epoch 14/100
2/2 [==============================] - 0s 51ms/step - loss: 3.2071 - accuracy: 0.4246 - val_loss: 3.2475 - val_accuracy: 0.3696
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 3.0939 - accuracy: 0.4659 - val_loss: 3.2314 - val_accuracy: 0.3696
Epoch 16/100
2/2 [==============================] - 0s 38ms/step - loss: 3.1457 - accuracy: 0.4538 - val_loss: 3.2146 - val_accuracy: 0.3696
Epoch 17/100
2/2 [==============================] - 0s 48ms/step - loss: 3.1055 - accuracy: 0.4453 - val_loss: 3.1970 - val_accuracy: 0.3696
Epoch 18/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1158 - accuracy: 0.4538 - val_loss: 3.1788 - val_accuracy: 0.3804
Epoch 19/100
2/2 [==============================] - 0s 27ms/step - loss: 3.0989 - accuracy: 0.4392 - val_loss: 3.1599 - val_accuracy: 0.3913
Epoch 20/100
2/2 [==============================] - 0s 49ms/step - loss: 3.0628 - accuracy: 0.4732 - val_loss: 3.1406 - val_accuracy: 0.4022
Epoch 21/100
2/2 [==============================] - 0s 41ms/step - loss: 3.0775 - accuracy: 0.4526 - val_loss: 3.1207 - val_accuracy: 0.4239
Epoch 22/100
2/2 [==============================] - 0s 33ms/step - loss: 3.0043 - accuracy: 0.4939 - val_loss: 3.1003 - val_accuracy: 0.4565
Epoch 23/100
2/2 [==============================] - 0s 35ms/step - loss: 3.0222 - accuracy: 0.4732 - val_loss: 3.0795 - val_accuracy: 0.4674
Epoch 24/100
2/2 [==============================] - 0s 50ms/step - loss: 2.9868 - accuracy: 0.4854 - val_loss: 3.0584 - val_accuracy: 0.4674
Epoch 25/100
2/2 [==============================] - 0s 49ms/step - loss: 3.0030 - accuracy: 0.4684 - val_loss: 3.0369 - val_accuracy: 0.4674
Epoch 26/100
2/2 [==============================] - 0s 27ms/step - loss: 2.9400 - accuracy: 0.4939 - val_loss: 3.0151 - val_accuracy: 0.4674
Epoch 27/100
2/2 [==============================] - 0s 42ms/step - loss: 2.9019 - accuracy: 0.5134 - val_loss: 2.9930 - val_accuracy: 0.4783
Epoch 28/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8709 - accuracy: 0.5268 - val_loss: 2.9708 - val_accuracy: 0.4674
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8871 - accuracy: 0.5219 - val_loss: 2.9484 - val_accuracy: 0.4674
Epoch 30/100
2/2 [==============================] - 0s 50ms/step - loss: 2.8505 - accuracy: 0.5268 - val_loss: 2.9258 - val_accuracy: 0.4674
Epoch 31/100
2/2 [==============================] - 0s 28ms/step - loss: 2.7947 - accuracy: 0.5596 - val_loss: 2.9032 - val_accuracy: 0.4674
Epoch 32/100
2/2 [==============================] - 0s 33ms/step - loss: 2.8020 - accuracy: 0.5487 - val_loss: 2.8805 - val_accuracy: 0.4783
Epoch 33/100
2/2 [==============================] - 0s 29ms/step - loss: 2.7612 - accuracy: 0.5560 - val_loss: 2.8578 - val_accuracy: 0.4783
Epoch 34/100
2/2 [==============================] - 0s 32ms/step - loss: 2.7335 - accuracy: 0.5876 - val_loss: 2.8350 - val_accuracy: 0.5000
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 2.7139 - accuracy: 0.5791 - val_loss: 2.8123 - val_accuracy: 0.5109
Epoch 36/100
2/2 [==============================] - 0s 45ms/step - loss: 2.6914 - accuracy: 0.5961 - val_loss: 2.7896 - val_accuracy: 0.5217
Epoch 37/100
2/2 [==============================] - 0s 44ms/step - loss: 2.6701 - accuracy: 0.5888 - val_loss: 2.7670 - val_accuracy: 0.5435
Epoch 38/100
2/2 [==============================] - 0s 34ms/step - loss: 2.6554 - accuracy: 0.5925 - val_loss: 2.7446 - val_accuracy: 0.5435
Epoch 39/100
2/2 [==============================] - 0s 41ms/step - loss: 2.6204 - accuracy: 0.6046 - val_loss: 2.7223 - val_accuracy: 0.5435
Epoch 40/100
2/2 [==============================] - 0s 36ms/step - loss: 2.6383 - accuracy: 0.6046 - val_loss: 2.7001 - val_accuracy: 0.5652
Epoch 41/100
2/2 [==============================] - 0s 31ms/step - loss: 2.6000 - accuracy: 0.6277 - val_loss: 2.6782 - val_accuracy: 0.5761
Epoch 42/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5471 - accuracy: 0.6423 - val_loss: 2.6564 - val_accuracy: 0.5761
Epoch 43/100
2/2 [==============================] - 0s 52ms/step - loss: 2.5624 - accuracy: 0.6168 - val_loss: 2.6349 - val_accuracy: 0.5761
Epoch 44/100
2/2 [==============================] - 0s 40ms/step - loss: 2.5024 - accuracy: 0.6715 - val_loss: 2.6136 - val_accuracy: 0.5870
Epoch 45/100
2/2 [==============================] - 0s 44ms/step - loss: 2.5095 - accuracy: 0.6642 - val_loss: 2.5925 - val_accuracy: 0.5978
Epoch 46/100
2/2 [==============================] - 0s 39ms/step - loss: 2.4539 - accuracy: 0.6837 - val_loss: 2.5717 - val_accuracy: 0.5978
Epoch 47/100
2/2 [==============================] - 0s 37ms/step - loss: 2.4460 - accuracy: 0.6922 - val_loss: 2.5511 - val_accuracy: 0.6304
Epoch 48/100
2/2 [==============================] - 0s 45ms/step - loss: 2.4190 - accuracy: 0.6922 - val_loss: 2.5307 - val_accuracy: 0.6413
Epoch 49/100
2/2 [==============================] - 0s 44ms/step - loss: 2.4102 - accuracy: 0.7007 - val_loss: 2.5106 - val_accuracy: 0.6413
Epoch 50/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3656 - accuracy: 0.7348 - val_loss: 2.4908 - val_accuracy: 0.6522
Epoch 51/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3447 - accuracy: 0.7202 - val_loss: 2.4713 - val_accuracy: 0.6630
Epoch 52/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3440 - accuracy: 0.7202 - val_loss: 2.4521 - val_accuracy: 0.6739
Epoch 53/100
2/2 [==============================] - 0s 31ms/step - loss: 2.3025 - accuracy: 0.7397 - val_loss: 2.4331 - val_accuracy: 0.6848
Epoch 54/100
2/2 [==============================] - 0s 33ms/step - loss: 2.2723 - accuracy: 0.7494 - val_loss: 2.4145 - val_accuracy: 0.6848
Epoch 55/100
2/2 [==============================] - 0s 36ms/step - loss: 2.2742 - accuracy: 0.7397 - val_loss: 2.3961 - val_accuracy: 0.6957
Epoch 56/100
2/2 [==============================] - 0s 44ms/step - loss: 2.2454 - accuracy: 0.7591 - val_loss: 2.3780 - val_accuracy: 0.6957
Epoch 57/100
2/2 [==============================] - 0s 33ms/step - loss: 2.2299 - accuracy: 0.7713 - val_loss: 2.3602 - val_accuracy: 0.6957
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2048 - accuracy: 0.7774 - val_loss: 2.3427 - val_accuracy: 0.7065
Epoch 59/100
2/2 [==============================] - 0s 40ms/step - loss: 2.2080 - accuracy: 0.7725 - val_loss: 2.3255 - val_accuracy: 0.7174
Epoch 60/100
2/2 [==============================] - 0s 26ms/step - loss: 2.1898 - accuracy: 0.7762 - val_loss: 2.3085 - val_accuracy: 0.7174
Epoch 61/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1922 - accuracy: 0.7616 - val_loss: 2.2919 - val_accuracy: 0.7174
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 2.1581 - accuracy: 0.7920 - val_loss: 2.2754 - val_accuracy: 0.7391
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1340 - accuracy: 0.7932 - val_loss: 2.2592 - val_accuracy: 0.7500
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1217 - accuracy: 0.8017 - val_loss: 2.2432 - val_accuracy: 0.7500
Epoch 65/100
2/2 [==============================] - 0s 30ms/step - loss: 2.0934 - accuracy: 0.7920 - val_loss: 2.2275 - val_accuracy: 0.7609
Epoch 66/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0688 - accuracy: 0.8139 - val_loss: 2.2120 - val_accuracy: 0.7609
Epoch 67/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0674 - accuracy: 0.8054 - val_loss: 2.1968 - val_accuracy: 0.7717
Epoch 68/100
2/2 [==============================] - 0s 52ms/step - loss: 2.0473 - accuracy: 0.8078 - val_loss: 2.1817 - val_accuracy: 0.7717
Epoch 69/100
2/2 [==============================] - 0s 50ms/step - loss: 2.0289 - accuracy: 0.8236 - val_loss: 2.1669 - val_accuracy: 0.7500
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0234 - accuracy: 0.8054 - val_loss: 2.1522 - val_accuracy: 0.7500
Epoch 71/100
2/2 [==============================] - 0s 29ms/step - loss: 1.9989 - accuracy: 0.8248 - val_loss: 2.1378 - val_accuracy: 0.7500
Epoch 72/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9830 - accuracy: 0.8212 - val_loss: 2.1235 - val_accuracy: 0.7609
Epoch 73/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9735 - accuracy: 0.8212 - val_loss: 2.1094 - val_accuracy: 0.7609
Epoch 74/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9604 - accuracy: 0.8273 - val_loss: 2.0955 - val_accuracy: 0.7717
Epoch 75/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9490 - accuracy: 0.8321 - val_loss: 2.0818 - val_accuracy: 0.7717
Epoch 76/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9334 - accuracy: 0.8358 - val_loss: 2.0683 - val_accuracy: 0.7717
Epoch 77/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9121 - accuracy: 0.8382 - val_loss: 2.0549 - val_accuracy: 0.7717
Epoch 78/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8904 - accuracy: 0.8443 - val_loss: 2.0417 - val_accuracy: 0.7935
Epoch 79/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9144 - accuracy: 0.8285 - val_loss: 2.0287 - val_accuracy: 0.7935
Epoch 80/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8574 - accuracy: 0.8418 - val_loss: 2.0158 - val_accuracy: 0.7935
Epoch 81/100
2/2 [==============================] - 0s 25ms/step - loss: 1.8763 - accuracy: 0.8394 - val_loss: 2.0030 - val_accuracy: 0.8043
Epoch 82/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8360 - accuracy: 0.8431 - val_loss: 1.9904 - val_accuracy: 0.8043
Epoch 83/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8320 - accuracy: 0.8418 - val_loss: 1.9779 - val_accuracy: 0.8043
Epoch 84/100
2/2 [==============================] - 0s 46ms/step - loss: 1.8253 - accuracy: 0.8382 - val_loss: 1.9655 - val_accuracy: 0.8043
Epoch 85/100
2/2 [==============================] - 0s 24ms/step - loss: 1.8097 - accuracy: 0.8431 - val_loss: 1.9533 - val_accuracy: 0.7935
Epoch 86/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8021 - accuracy: 0.8418 - val_loss: 1.9412 - val_accuracy: 0.7935
Epoch 87/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7911 - accuracy: 0.8382 - val_loss: 1.9291 - val_accuracy: 0.7935
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7728 - accuracy: 0.8455 - val_loss: 1.9172 - val_accuracy: 0.7935
Epoch 89/100
2/2 [==============================] - 0s 27ms/step - loss: 1.7495 - accuracy: 0.8528 - val_loss: 1.9054 - val_accuracy: 0.7935
Epoch 90/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7403 - accuracy: 0.8552 - val_loss: 1.8937 - val_accuracy: 0.7935
Epoch 91/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7547 - accuracy: 0.8479 - val_loss: 1.8821 - val_accuracy: 0.7935
Epoch 92/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7362 - accuracy: 0.8552 - val_loss: 1.8706 - val_accuracy: 0.7935
Epoch 93/100
2/2 [==============================] - 0s 27ms/step - loss: 1.7212 - accuracy: 0.8540 - val_loss: 1.8592 - val_accuracy: 0.7935
Epoch 94/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7072 - accuracy: 0.8431 - val_loss: 1.8478 - val_accuracy: 0.7935
Epoch 95/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6964 - accuracy: 0.8552 - val_loss: 1.8366 - val_accuracy: 0.7935
Epoch 96/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6841 - accuracy: 0.8528 - val_loss: 1.8254 - val_accuracy: 0.7935
Epoch 97/100
2/2 [==============================] - 0s 49ms/step - loss: 1.6693 - accuracy: 0.8552 - val_loss: 1.8143 - val_accuracy: 0.7935
Epoch 98/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6650 - accuracy: 0.8516 - val_loss: 1.8033 - val_accuracy: 0.7935
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6407 - accuracy: 0.8564 - val_loss: 1.7923 - val_accuracy: 0.7935
Epoch 100/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6327 - accuracy: 0.8625 - val_loss: 1.7815 - val_accuracy: 0.7935
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 232ms/step - loss: 2.6041 - accuracy: 0.5754 - val_loss: 2.5219 - val_accuracy: 0.6304
Epoch 2/100
2/2 [==============================] - 0s 37ms/step - loss: 2.5759 - accuracy: 0.6144 - val_loss: 2.5207 - val_accuracy: 0.6304
Epoch 3/100
2/2 [==============================] - 0s 33ms/step - loss: 2.5742 - accuracy: 0.6119 - val_loss: 2.5190 - val_accuracy: 0.6304
Epoch 4/100
2/2 [==============================] - 0s 36ms/step - loss: 2.5698 - accuracy: 0.6229 - val_loss: 2.5166 - val_accuracy: 0.6304
Epoch 5/100
2/2 [==============================] - 0s 31ms/step - loss: 2.5703 - accuracy: 0.6022 - val_loss: 2.5137 - val_accuracy: 0.6304
Epoch 6/100
2/2 [==============================] - 0s 37ms/step - loss: 2.5591 - accuracy: 0.6180 - val_loss: 2.5101 - val_accuracy: 0.6304
Epoch 7/100
2/2 [==============================] - 0s 48ms/step - loss: 2.5661 - accuracy: 0.6265 - val_loss: 2.5060 - val_accuracy: 0.6413
Epoch 8/100
2/2 [==============================] - 0s 32ms/step - loss: 2.5635 - accuracy: 0.6083 - val_loss: 2.5014 - val_accuracy: 0.6413
Epoch 9/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5548 - accuracy: 0.6071 - val_loss: 2.4962 - val_accuracy: 0.6413
Epoch 10/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5403 - accuracy: 0.6350 - val_loss: 2.4906 - val_accuracy: 0.6522
Epoch 11/100
2/2 [==============================] - 0s 41ms/step - loss: 2.5526 - accuracy: 0.6046 - val_loss: 2.4844 - val_accuracy: 0.6522
Epoch 12/100
2/2 [==============================] - 0s 36ms/step - loss: 2.5236 - accuracy: 0.6241 - val_loss: 2.4778 - val_accuracy: 0.6522
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 2.5299 - accuracy: 0.6168 - val_loss: 2.4708 - val_accuracy: 0.6630
Epoch 14/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5186 - accuracy: 0.6314 - val_loss: 2.4633 - val_accuracy: 0.6739
Epoch 15/100
2/2 [==============================] - 0s 36ms/step - loss: 2.4925 - accuracy: 0.6326 - val_loss: 2.4553 - val_accuracy: 0.6739
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 2.5017 - accuracy: 0.6338 - val_loss: 2.4470 - val_accuracy: 0.6848
Epoch 17/100
2/2 [==============================] - 0s 36ms/step - loss: 2.5056 - accuracy: 0.6387 - val_loss: 2.4383 - val_accuracy: 0.6848
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 2.4886 - accuracy: 0.6460 - val_loss: 2.4293 - val_accuracy: 0.6848
Epoch 19/100
2/2 [==============================] - 0s 34ms/step - loss: 2.4901 - accuracy: 0.6448 - val_loss: 2.4199 - val_accuracy: 0.6957
Epoch 20/100
2/2 [==============================] - 0s 51ms/step - loss: 2.4689 - accuracy: 0.6363 - val_loss: 2.4102 - val_accuracy: 0.6957
Epoch 21/100
2/2 [==============================] - 0s 38ms/step - loss: 2.4834 - accuracy: 0.6204 - val_loss: 2.4002 - val_accuracy: 0.6957
Epoch 22/100
2/2 [==============================] - 0s 28ms/step - loss: 2.4673 - accuracy: 0.6277 - val_loss: 2.3898 - val_accuracy: 0.7065
Epoch 23/100
2/2 [==============================] - 0s 32ms/step - loss: 2.4611 - accuracy: 0.6350 - val_loss: 2.3792 - val_accuracy: 0.7065
Epoch 24/100
2/2 [==============================] - 0s 41ms/step - loss: 2.4250 - accuracy: 0.6667 - val_loss: 2.3684 - val_accuracy: 0.7065
Epoch 25/100
2/2 [==============================] - 0s 36ms/step - loss: 2.4357 - accuracy: 0.6521 - val_loss: 2.3573 - val_accuracy: 0.7065
Epoch 26/100
2/2 [==============================] - 0s 48ms/step - loss: 2.4171 - accuracy: 0.6557 - val_loss: 2.3459 - val_accuracy: 0.7065
Epoch 27/100
2/2 [==============================] - 0s 25ms/step - loss: 2.3718 - accuracy: 0.6691 - val_loss: 2.3344 - val_accuracy: 0.7283
Epoch 28/100
2/2 [==============================] - 0s 32ms/step - loss: 2.3777 - accuracy: 0.6655 - val_loss: 2.3227 - val_accuracy: 0.7283
Epoch 29/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3646 - accuracy: 0.6776 - val_loss: 2.3108 - val_accuracy: 0.7391
Epoch 30/100
2/2 [==============================] - 0s 32ms/step - loss: 2.3386 - accuracy: 0.6934 - val_loss: 2.2988 - val_accuracy: 0.7391
Epoch 31/100
2/2 [==============================] - 0s 32ms/step - loss: 2.3199 - accuracy: 0.6934 - val_loss: 2.2866 - val_accuracy: 0.7500
Epoch 32/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3114 - accuracy: 0.7068 - val_loss: 2.2743 - val_accuracy: 0.7500
Epoch 33/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3166 - accuracy: 0.6752 - val_loss: 2.2618 - val_accuracy: 0.7609
Epoch 34/100
2/2 [==============================] - 0s 34ms/step - loss: 2.2911 - accuracy: 0.7080 - val_loss: 2.2493 - val_accuracy: 0.7609
Epoch 35/100
2/2 [==============================] - 0s 31ms/step - loss: 2.2850 - accuracy: 0.6971 - val_loss: 2.2367 - val_accuracy: 0.7717
Epoch 36/100
2/2 [==============================] - 0s 31ms/step - loss: 2.2565 - accuracy: 0.7117 - val_loss: 2.2240 - val_accuracy: 0.7717
Epoch 37/100
2/2 [==============================] - 0s 51ms/step - loss: 2.2597 - accuracy: 0.7141 - val_loss: 2.2112 - val_accuracy: 0.7826
Epoch 38/100
2/2 [==============================] - 0s 32ms/step - loss: 2.2226 - accuracy: 0.7348 - val_loss: 2.1984 - val_accuracy: 0.7826
Epoch 39/100
2/2 [==============================] - 0s 35ms/step - loss: 2.2091 - accuracy: 0.7336 - val_loss: 2.1856 - val_accuracy: 0.7826
Epoch 40/100
2/2 [==============================] - 0s 35ms/step - loss: 2.2099 - accuracy: 0.7372 - val_loss: 2.1727 - val_accuracy: 0.7826
Epoch 41/100
2/2 [==============================] - 0s 32ms/step - loss: 2.1789 - accuracy: 0.7506 - val_loss: 2.1598 - val_accuracy: 0.7826
Epoch 42/100
2/2 [==============================] - 0s 43ms/step - loss: 2.1792 - accuracy: 0.7494 - val_loss: 2.1469 - val_accuracy: 0.7826
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1685 - accuracy: 0.7433 - val_loss: 2.1340 - val_accuracy: 0.7826
Epoch 44/100
2/2 [==============================] - 0s 32ms/step - loss: 2.1525 - accuracy: 0.7153 - val_loss: 2.1211 - val_accuracy: 0.7717
Epoch 45/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1300 - accuracy: 0.7664 - val_loss: 2.1082 - val_accuracy: 0.7717
Epoch 46/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1278 - accuracy: 0.7470 - val_loss: 2.0954 - val_accuracy: 0.7717
Epoch 47/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1194 - accuracy: 0.7506 - val_loss: 2.0826 - val_accuracy: 0.7717
Epoch 48/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1040 - accuracy: 0.7567 - val_loss: 2.0698 - val_accuracy: 0.7826
Epoch 49/100
2/2 [==============================] - 0s 29ms/step - loss: 2.0807 - accuracy: 0.7616 - val_loss: 2.0570 - val_accuracy: 0.7717
Epoch 50/100
2/2 [==============================] - 0s 32ms/step - loss: 2.0691 - accuracy: 0.7652 - val_loss: 2.0443 - val_accuracy: 0.7717
Epoch 51/100
2/2 [==============================] - 0s 53ms/step - loss: 2.0350 - accuracy: 0.7822 - val_loss: 2.0318 - val_accuracy: 0.7826
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 2.0196 - accuracy: 0.8005 - val_loss: 2.0192 - val_accuracy: 0.7826
Epoch 53/100
2/2 [==============================] - 0s 31ms/step - loss: 2.0164 - accuracy: 0.7835 - val_loss: 2.0067 - val_accuracy: 0.7826
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0110 - accuracy: 0.7762 - val_loss: 1.9943 - val_accuracy: 0.7826
Epoch 55/100
2/2 [==============================] - 0s 46ms/step - loss: 1.9794 - accuracy: 0.7920 - val_loss: 1.9820 - val_accuracy: 0.7826
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9764 - accuracy: 0.7871 - val_loss: 1.9698 - val_accuracy: 0.7826
Epoch 57/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9691 - accuracy: 0.7847 - val_loss: 1.9576 - val_accuracy: 0.7717
Epoch 58/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9529 - accuracy: 0.7920 - val_loss: 1.9455 - val_accuracy: 0.7717
Epoch 59/100
2/2 [==============================] - 0s 49ms/step - loss: 1.9538 - accuracy: 0.7859 - val_loss: 1.9335 - val_accuracy: 0.7826
Epoch 60/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9230 - accuracy: 0.8041 - val_loss: 1.9215 - val_accuracy: 0.7826
Epoch 61/100
2/2 [==============================] - 0s 32ms/step - loss: 1.9053 - accuracy: 0.8200 - val_loss: 1.9097 - val_accuracy: 0.7935
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8941 - accuracy: 0.8029 - val_loss: 1.8979 - val_accuracy: 0.7935
Epoch 63/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8743 - accuracy: 0.8066 - val_loss: 1.8863 - val_accuracy: 0.7935
Epoch 64/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8585 - accuracy: 0.8163 - val_loss: 1.8747 - val_accuracy: 0.8043
Epoch 65/100
2/2 [==============================] - 0s 29ms/step - loss: 1.8651 - accuracy: 0.8187 - val_loss: 1.8633 - val_accuracy: 0.8043
Epoch 66/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8317 - accuracy: 0.8078 - val_loss: 1.8519 - val_accuracy: 0.8043
Epoch 67/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8358 - accuracy: 0.8090 - val_loss: 1.8407 - val_accuracy: 0.8152
Epoch 68/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8226 - accuracy: 0.8029 - val_loss: 1.8295 - val_accuracy: 0.8152
Epoch 69/100
2/2 [==============================] - 0s 29ms/step - loss: 1.8140 - accuracy: 0.8297 - val_loss: 1.8185 - val_accuracy: 0.8152
Epoch 70/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7855 - accuracy: 0.8382 - val_loss: 1.8076 - val_accuracy: 0.8152
Epoch 71/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7809 - accuracy: 0.8151 - val_loss: 1.7967 - val_accuracy: 0.8152
Epoch 72/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7676 - accuracy: 0.8333 - val_loss: 1.7860 - val_accuracy: 0.8152
Epoch 73/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7648 - accuracy: 0.8297 - val_loss: 1.7753 - val_accuracy: 0.8152
Epoch 74/100
2/2 [==============================] - 0s 30ms/step - loss: 1.7471 - accuracy: 0.8443 - val_loss: 1.7648 - val_accuracy: 0.8043
Epoch 75/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7242 - accuracy: 0.8370 - val_loss: 1.7543 - val_accuracy: 0.8043
Epoch 76/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7193 - accuracy: 0.8479 - val_loss: 1.7440 - val_accuracy: 0.8043
Epoch 77/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7092 - accuracy: 0.8394 - val_loss: 1.7337 - val_accuracy: 0.8043
Epoch 78/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7040 - accuracy: 0.8358 - val_loss: 1.7235 - val_accuracy: 0.8043
Epoch 79/100
2/2 [==============================] - 0s 67ms/step - loss: 1.6712 - accuracy: 0.8516 - val_loss: 1.7134 - val_accuracy: 0.8043
Epoch 80/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6721 - accuracy: 0.8394 - val_loss: 1.7035 - val_accuracy: 0.8043
Epoch 81/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6584 - accuracy: 0.8479 - val_loss: 1.6936 - val_accuracy: 0.8152
Epoch 82/100
2/2 [==============================] - 0s 53ms/step - loss: 1.6422 - accuracy: 0.8443 - val_loss: 1.6838 - val_accuracy: 0.8152
Epoch 83/100
2/2 [==============================] - 0s 23ms/step - loss: 1.6372 - accuracy: 0.8564 - val_loss: 1.6741 - val_accuracy: 0.8152
Epoch 84/100
2/2 [==============================] - 0s 51ms/step - loss: 1.6333 - accuracy: 0.8504 - val_loss: 1.6645 - val_accuracy: 0.8370
Epoch 85/100
2/2 [==============================] - 0s 29ms/step - loss: 1.6252 - accuracy: 0.8479 - val_loss: 1.6549 - val_accuracy: 0.8370
Epoch 86/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6075 - accuracy: 0.8552 - val_loss: 1.6454 - val_accuracy: 0.8370
Epoch 87/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5976 - accuracy: 0.8625 - val_loss: 1.6360 - val_accuracy: 0.8261
Epoch 88/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5964 - accuracy: 0.8589 - val_loss: 1.6267 - val_accuracy: 0.8261
Epoch 89/100
2/2 [==============================] - 0s 26ms/step - loss: 1.5654 - accuracy: 0.8637 - val_loss: 1.6174 - val_accuracy: 0.8261
Epoch 90/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5764 - accuracy: 0.8443 - val_loss: 1.6082 - val_accuracy: 0.8261
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5688 - accuracy: 0.8504 - val_loss: 1.5991 - val_accuracy: 0.8261
Epoch 92/100
2/2 [==============================] - 0s 56ms/step - loss: 1.5401 - accuracy: 0.8528 - val_loss: 1.5901 - val_accuracy: 0.8261
Epoch 93/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5346 - accuracy: 0.8613 - val_loss: 1.5811 - val_accuracy: 0.8152
Epoch 94/100
2/2 [==============================] - 0s 28ms/step - loss: 1.5472 - accuracy: 0.8516 - val_loss: 1.5722 - val_accuracy: 0.8152
Epoch 95/100
2/2 [==============================] - 0s 30ms/step - loss: 1.5202 - accuracy: 0.8528 - val_loss: 1.5634 - val_accuracy: 0.8152
Epoch 96/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5025 - accuracy: 0.8540 - val_loss: 1.5547 - val_accuracy: 0.8152
Epoch 97/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5075 - accuracy: 0.8504 - val_loss: 1.5461 - val_accuracy: 0.8152
Epoch 98/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4870 - accuracy: 0.8540 - val_loss: 1.5375 - val_accuracy: 0.8152
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4847 - accuracy: 0.8528 - val_loss: 1.5289 - val_accuracy: 0.8152
Epoch 100/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4693 - accuracy: 0.8613 - val_loss: 1.5205 - val_accuracy: 0.8152
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 214ms/step - loss: 3.2282 - accuracy: 0.2713 - val_loss: 3.1756 - val_accuracy: 0.3043
Epoch 2/100
2/2 [==============================] - 0s 43ms/step - loss: 3.2357 - accuracy: 0.2871 - val_loss: 3.1734 - val_accuracy: 0.3043
Epoch 3/100
2/2 [==============================] - 0s 41ms/step - loss: 3.2264 - accuracy: 0.2725 - val_loss: 3.1699 - val_accuracy: 0.3043
Epoch 4/100
2/2 [==============================] - 0s 39ms/step - loss: 3.2386 - accuracy: 0.2774 - val_loss: 3.1652 - val_accuracy: 0.3043
Epoch 5/100
2/2 [==============================] - 0s 33ms/step - loss: 3.2175 - accuracy: 0.2835 - val_loss: 3.1594 - val_accuracy: 0.3043
Epoch 6/100
2/2 [==============================] - 0s 37ms/step - loss: 3.2120 - accuracy: 0.3029 - val_loss: 3.1524 - val_accuracy: 0.3152
Epoch 7/100
2/2 [==============================] - 0s 40ms/step - loss: 3.2223 - accuracy: 0.2932 - val_loss: 3.1443 - val_accuracy: 0.3152
Epoch 8/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2034 - accuracy: 0.3175 - val_loss: 3.1351 - val_accuracy: 0.3152
Epoch 9/100
2/2 [==============================] - 0s 31ms/step - loss: 3.2106 - accuracy: 0.2883 - val_loss: 3.1249 - val_accuracy: 0.3152
Epoch 10/100
2/2 [==============================] - 0s 34ms/step - loss: 3.1886 - accuracy: 0.3054 - val_loss: 3.1137 - val_accuracy: 0.3152
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 3.1974 - accuracy: 0.2968 - val_loss: 3.1014 - val_accuracy: 0.3152
Epoch 12/100
2/2 [==============================] - 0s 49ms/step - loss: 3.1998 - accuracy: 0.2847 - val_loss: 3.0883 - val_accuracy: 0.3152
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 3.1464 - accuracy: 0.3127 - val_loss: 3.0742 - val_accuracy: 0.3152
Epoch 14/100
2/2 [==============================] - 0s 35ms/step - loss: 3.1620 - accuracy: 0.2920 - val_loss: 3.0593 - val_accuracy: 0.3152
Epoch 15/100
2/2 [==============================] - 0s 50ms/step - loss: 3.1314 - accuracy: 0.3260 - val_loss: 3.0435 - val_accuracy: 0.3152
Epoch 16/100
2/2 [==============================] - 0s 50ms/step - loss: 3.1109 - accuracy: 0.3248 - val_loss: 3.0270 - val_accuracy: 0.3261
Epoch 17/100
2/2 [==============================] - 0s 51ms/step - loss: 3.1298 - accuracy: 0.3090 - val_loss: 3.0098 - val_accuracy: 0.3370
Epoch 18/100
2/2 [==============================] - 0s 33ms/step - loss: 3.0602 - accuracy: 0.3370 - val_loss: 2.9918 - val_accuracy: 0.3478
Epoch 19/100
2/2 [==============================] - 0s 37ms/step - loss: 3.0360 - accuracy: 0.3528 - val_loss: 2.9732 - val_accuracy: 0.3478
Epoch 20/100
2/2 [==============================] - 0s 24ms/step - loss: 3.0368 - accuracy: 0.3564 - val_loss: 2.9540 - val_accuracy: 0.3478
Epoch 21/100
2/2 [==============================] - 0s 35ms/step - loss: 3.0252 - accuracy: 0.3406 - val_loss: 2.9343 - val_accuracy: 0.3478
Epoch 22/100
2/2 [==============================] - 0s 33ms/step - loss: 2.9745 - accuracy: 0.3710 - val_loss: 2.9140 - val_accuracy: 0.3478
Epoch 23/100
2/2 [==============================] - 0s 51ms/step - loss: 2.9659 - accuracy: 0.3589 - val_loss: 2.8932 - val_accuracy: 0.3587
Epoch 24/100
2/2 [==============================] - 0s 35ms/step - loss: 2.9583 - accuracy: 0.3869 - val_loss: 2.8719 - val_accuracy: 0.3804
Epoch 25/100
2/2 [==============================] - 0s 37ms/step - loss: 2.9530 - accuracy: 0.3723 - val_loss: 2.8502 - val_accuracy: 0.3804
Epoch 26/100
2/2 [==============================] - 0s 47ms/step - loss: 2.9076 - accuracy: 0.4015 - val_loss: 2.8282 - val_accuracy: 0.3804
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 2.8954 - accuracy: 0.3978 - val_loss: 2.8057 - val_accuracy: 0.3913
Epoch 28/100
2/2 [==============================] - 0s 33ms/step - loss: 2.8830 - accuracy: 0.3978 - val_loss: 2.7830 - val_accuracy: 0.4239
Epoch 29/100
2/2 [==============================] - 0s 49ms/step - loss: 2.8422 - accuracy: 0.4209 - val_loss: 2.7600 - val_accuracy: 0.4457
Epoch 30/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8168 - accuracy: 0.4282 - val_loss: 2.7368 - val_accuracy: 0.4457
Epoch 31/100
2/2 [==============================] - 0s 32ms/step - loss: 2.7987 - accuracy: 0.4428 - val_loss: 2.7133 - val_accuracy: 0.4674
Epoch 32/100
2/2 [==============================] - 0s 50ms/step - loss: 2.7390 - accuracy: 0.4550 - val_loss: 2.6897 - val_accuracy: 0.4783
Epoch 33/100
2/2 [==============================] - 0s 28ms/step - loss: 2.7599 - accuracy: 0.4599 - val_loss: 2.6660 - val_accuracy: 0.5109
Epoch 34/100
2/2 [==============================] - 0s 37ms/step - loss: 2.7261 - accuracy: 0.4440 - val_loss: 2.6421 - val_accuracy: 0.5435
Epoch 35/100
2/2 [==============================] - 0s 35ms/step - loss: 2.7113 - accuracy: 0.4550 - val_loss: 2.6182 - val_accuracy: 0.5543
Epoch 36/100
2/2 [==============================] - 0s 37ms/step - loss: 2.6921 - accuracy: 0.4891 - val_loss: 2.5941 - val_accuracy: 0.5543
Epoch 37/100
2/2 [==============================] - 0s 37ms/step - loss: 2.6624 - accuracy: 0.5000 - val_loss: 2.5701 - val_accuracy: 0.5543
Epoch 38/100
2/2 [==============================] - 0s 36ms/step - loss: 2.6037 - accuracy: 0.5316 - val_loss: 2.5461 - val_accuracy: 0.5761
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 2.5798 - accuracy: 0.5292 - val_loss: 2.5221 - val_accuracy: 0.5978
Epoch 40/100
2/2 [==============================] - 0s 30ms/step - loss: 2.5588 - accuracy: 0.5426 - val_loss: 2.4981 - val_accuracy: 0.6087
Epoch 41/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5425 - accuracy: 0.5292 - val_loss: 2.4743 - val_accuracy: 0.6196
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 2.5217 - accuracy: 0.5450 - val_loss: 2.4505 - val_accuracy: 0.6196
Epoch 43/100
2/2 [==============================] - 0s 30ms/step - loss: 2.4915 - accuracy: 0.5535 - val_loss: 2.4269 - val_accuracy: 0.6196
Epoch 44/100
2/2 [==============================] - 0s 29ms/step - loss: 2.4924 - accuracy: 0.5888 - val_loss: 2.4034 - val_accuracy: 0.6413
Epoch 45/100
2/2 [==============================] - 0s 36ms/step - loss: 2.4609 - accuracy: 0.6034 - val_loss: 2.3800 - val_accuracy: 0.6413
Epoch 46/100
2/2 [==============================] - 0s 45ms/step - loss: 2.4479 - accuracy: 0.5937 - val_loss: 2.3568 - val_accuracy: 0.6413
Epoch 47/100
2/2 [==============================] - 0s 33ms/step - loss: 2.4117 - accuracy: 0.6083 - val_loss: 2.3338 - val_accuracy: 0.6413
Epoch 48/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3763 - accuracy: 0.6290 - val_loss: 2.3110 - val_accuracy: 0.6522
Epoch 49/100
2/2 [==============================] - 0s 41ms/step - loss: 2.3740 - accuracy: 0.6326 - val_loss: 2.2884 - val_accuracy: 0.6522
Epoch 50/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3363 - accuracy: 0.6582 - val_loss: 2.2660 - val_accuracy: 0.6413
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3284 - accuracy: 0.6411 - val_loss: 2.2438 - val_accuracy: 0.6413
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 2.2711 - accuracy: 0.6667 - val_loss: 2.2219 - val_accuracy: 0.6739
Epoch 53/100
2/2 [==============================] - 0s 34ms/step - loss: 2.2799 - accuracy: 0.6618 - val_loss: 2.2003 - val_accuracy: 0.6957
Epoch 54/100
2/2 [==============================] - 0s 36ms/step - loss: 2.2691 - accuracy: 0.6582 - val_loss: 2.1789 - val_accuracy: 0.7065
Epoch 55/100
2/2 [==============================] - 0s 31ms/step - loss: 2.2114 - accuracy: 0.6971 - val_loss: 2.1578 - val_accuracy: 0.7065
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2017 - accuracy: 0.6873 - val_loss: 2.1369 - val_accuracy: 0.7391
Epoch 57/100
2/2 [==============================] - 0s 43ms/step - loss: 2.1816 - accuracy: 0.7044 - val_loss: 2.1164 - val_accuracy: 0.7391
Epoch 58/100
2/2 [==============================] - 0s 34ms/step - loss: 2.1689 - accuracy: 0.7092 - val_loss: 2.0961 - val_accuracy: 0.7717
Epoch 59/100
2/2 [==============================] - 0s 32ms/step - loss: 2.1644 - accuracy: 0.7019 - val_loss: 2.0760 - val_accuracy: 0.7826
Epoch 60/100
2/2 [==============================] - 0s 41ms/step - loss: 2.1299 - accuracy: 0.7287 - val_loss: 2.0563 - val_accuracy: 0.7826
Epoch 61/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1158 - accuracy: 0.7263 - val_loss: 2.0369 - val_accuracy: 0.8043
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1063 - accuracy: 0.7445 - val_loss: 2.0177 - val_accuracy: 0.8043
Epoch 63/100
2/2 [==============================] - 0s 42ms/step - loss: 2.0660 - accuracy: 0.7652 - val_loss: 1.9989 - val_accuracy: 0.8152
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0424 - accuracy: 0.7409 - val_loss: 1.9803 - val_accuracy: 0.8478
Epoch 65/100
2/2 [==============================] - 0s 36ms/step - loss: 2.0315 - accuracy: 0.7567 - val_loss: 1.9620 - val_accuracy: 0.8478
Epoch 66/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0304 - accuracy: 0.7591 - val_loss: 1.9440 - val_accuracy: 0.8478
Epoch 67/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9931 - accuracy: 0.7676 - val_loss: 1.9263 - val_accuracy: 0.8478
Epoch 68/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9724 - accuracy: 0.7762 - val_loss: 1.9089 - val_accuracy: 0.8370
Epoch 69/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9593 - accuracy: 0.7883 - val_loss: 1.8918 - val_accuracy: 0.8478
Epoch 70/100
2/2 [==============================] - 0s 33ms/step - loss: 1.9498 - accuracy: 0.7895 - val_loss: 1.8749 - val_accuracy: 0.8478
Epoch 71/100
2/2 [==============================] - 0s 50ms/step - loss: 1.9244 - accuracy: 0.7944 - val_loss: 1.8583 - val_accuracy: 0.8478
Epoch 72/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9164 - accuracy: 0.7944 - val_loss: 1.8419 - val_accuracy: 0.8478
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9125 - accuracy: 0.7822 - val_loss: 1.8259 - val_accuracy: 0.8478
Epoch 74/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8742 - accuracy: 0.8200 - val_loss: 1.8100 - val_accuracy: 0.8478
Epoch 75/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8715 - accuracy: 0.7968 - val_loss: 1.7944 - val_accuracy: 0.8478
Epoch 76/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8493 - accuracy: 0.8078 - val_loss: 1.7791 - val_accuracy: 0.8587
Epoch 77/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8385 - accuracy: 0.8187 - val_loss: 1.7640 - val_accuracy: 0.8587
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8135 - accuracy: 0.8273 - val_loss: 1.7491 - val_accuracy: 0.8587
Epoch 79/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7900 - accuracy: 0.8224 - val_loss: 1.7345 - val_accuracy: 0.8587
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7886 - accuracy: 0.8236 - val_loss: 1.7201 - val_accuracy: 0.8587
Epoch 81/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7769 - accuracy: 0.8236 - val_loss: 1.7059 - val_accuracy: 0.8587
Epoch 82/100
2/2 [==============================] - 0s 46ms/step - loss: 1.7545 - accuracy: 0.8309 - val_loss: 1.6919 - val_accuracy: 0.8587
Epoch 83/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7347 - accuracy: 0.8297 - val_loss: 1.6782 - val_accuracy: 0.8587
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7309 - accuracy: 0.8333 - val_loss: 1.6646 - val_accuracy: 0.8587
Epoch 85/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7173 - accuracy: 0.8285 - val_loss: 1.6513 - val_accuracy: 0.8587
Epoch 86/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7080 - accuracy: 0.8333 - val_loss: 1.6381 - val_accuracy: 0.8478
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6885 - accuracy: 0.8418 - val_loss: 1.6252 - val_accuracy: 0.8478
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6866 - accuracy: 0.8370 - val_loss: 1.6124 - val_accuracy: 0.8478
Epoch 89/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6604 - accuracy: 0.8406 - val_loss: 1.5998 - val_accuracy: 0.8587
Epoch 90/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6514 - accuracy: 0.8370 - val_loss: 1.5874 - val_accuracy: 0.8587
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6564 - accuracy: 0.8443 - val_loss: 1.5751 - val_accuracy: 0.8587
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6339 - accuracy: 0.8431 - val_loss: 1.5630 - val_accuracy: 0.8587
Epoch 93/100
2/2 [==============================] - 0s 26ms/step - loss: 1.6137 - accuracy: 0.8443 - val_loss: 1.5510 - val_accuracy: 0.8587
Epoch 94/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6077 - accuracy: 0.8431 - val_loss: 1.5392 - val_accuracy: 0.8587
Epoch 95/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5826 - accuracy: 0.8540 - val_loss: 1.5276 - val_accuracy: 0.8587
Epoch 96/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5997 - accuracy: 0.8418 - val_loss: 1.5161 - val_accuracy: 0.8587
Epoch 97/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5715 - accuracy: 0.8467 - val_loss: 1.5048 - val_accuracy: 0.8587
Epoch 98/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5614 - accuracy: 0.8491 - val_loss: 1.4935 - val_accuracy: 0.8587
Epoch 99/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5513 - accuracy: 0.8455 - val_loss: 1.4825 - val_accuracy: 0.8587
Epoch 100/100
2/2 [==============================] - 0s 24ms/step - loss: 1.5463 - accuracy: 0.8479 - val_loss: 1.4715 - val_accuracy: 0.8587
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 203ms/step - loss: 3.6362 - accuracy: 0.1179 - val_loss: 3.6309 - val_accuracy: 0.0989
Epoch 2/100
2/2 [==============================] - 0s 33ms/step - loss: 3.6455 - accuracy: 0.1142 - val_loss: 3.6280 - val_accuracy: 0.0989
Epoch 3/100
2/2 [==============================] - 0s 38ms/step - loss: 3.6925 - accuracy: 0.1081 - val_loss: 3.6235 - val_accuracy: 0.0989
Epoch 4/100
2/2 [==============================] - 0s 34ms/step - loss: 3.6756 - accuracy: 0.1227 - val_loss: 3.6174 - val_accuracy: 0.0989
Epoch 5/100
2/2 [==============================] - 0s 49ms/step - loss: 3.6499 - accuracy: 0.1324 - val_loss: 3.6098 - val_accuracy: 0.0989
Epoch 6/100
2/2 [==============================] - 0s 51ms/step - loss: 3.6302 - accuracy: 0.1227 - val_loss: 3.6007 - val_accuracy: 0.0989
Epoch 7/100
2/2 [==============================] - 0s 51ms/step - loss: 3.6264 - accuracy: 0.1409 - val_loss: 3.5901 - val_accuracy: 0.0989
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 3.6024 - accuracy: 0.1434 - val_loss: 3.5782 - val_accuracy: 0.0989
Epoch 9/100
2/2 [==============================] - 0s 49ms/step - loss: 3.6560 - accuracy: 0.1191 - val_loss: 3.5648 - val_accuracy: 0.1099
Epoch 10/100
2/2 [==============================] - 0s 32ms/step - loss: 3.6281 - accuracy: 0.1191 - val_loss: 3.5502 - val_accuracy: 0.1099
Epoch 11/100
2/2 [==============================] - 0s 33ms/step - loss: 3.5698 - accuracy: 0.1446 - val_loss: 3.5343 - val_accuracy: 0.1099
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 3.5435 - accuracy: 0.1385 - val_loss: 3.5172 - val_accuracy: 0.1099
Epoch 13/100
2/2 [==============================] - 0s 45ms/step - loss: 3.5590 - accuracy: 0.1373 - val_loss: 3.4990 - val_accuracy: 0.1099
Epoch 14/100
2/2 [==============================] - 0s 41ms/step - loss: 3.5140 - accuracy: 0.1385 - val_loss: 3.4797 - val_accuracy: 0.1099
Epoch 15/100
2/2 [==============================] - 0s 44ms/step - loss: 3.4999 - accuracy: 0.1361 - val_loss: 3.4594 - val_accuracy: 0.1099
Epoch 16/100
2/2 [==============================] - 0s 29ms/step - loss: 3.4952 - accuracy: 0.1422 - val_loss: 3.4381 - val_accuracy: 0.1099
Epoch 17/100
2/2 [==============================] - 0s 35ms/step - loss: 3.4571 - accuracy: 0.1701 - val_loss: 3.4159 - val_accuracy: 0.1319
Epoch 18/100
2/2 [==============================] - 0s 34ms/step - loss: 3.4920 - accuracy: 0.1519 - val_loss: 3.3928 - val_accuracy: 0.1319
Epoch 19/100
2/2 [==============================] - 0s 51ms/step - loss: 3.4434 - accuracy: 0.1701 - val_loss: 3.3689 - val_accuracy: 0.1319
Epoch 20/100
2/2 [==============================] - 0s 25ms/step - loss: 3.4607 - accuracy: 0.1422 - val_loss: 3.3442 - val_accuracy: 0.1319
Epoch 21/100
2/2 [==============================] - 0s 43ms/step - loss: 3.3972 - accuracy: 0.1555 - val_loss: 3.3188 - val_accuracy: 0.1319
Epoch 22/100
2/2 [==============================] - 0s 45ms/step - loss: 3.3403 - accuracy: 0.1665 - val_loss: 3.2927 - val_accuracy: 0.1319
Epoch 23/100
2/2 [==============================] - 0s 39ms/step - loss: 3.3521 - accuracy: 0.1786 - val_loss: 3.2660 - val_accuracy: 0.1319
Epoch 24/100
2/2 [==============================] - 0s 32ms/step - loss: 3.3020 - accuracy: 0.2005 - val_loss: 3.2387 - val_accuracy: 0.1319
Epoch 25/100
2/2 [==============================] - 0s 36ms/step - loss: 3.2816 - accuracy: 0.1908 - val_loss: 3.2110 - val_accuracy: 0.1429
Epoch 26/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2678 - accuracy: 0.2029 - val_loss: 3.1829 - val_accuracy: 0.1429
Epoch 27/100
2/2 [==============================] - 0s 33ms/step - loss: 3.2953 - accuracy: 0.1968 - val_loss: 3.1543 - val_accuracy: 0.1429
Epoch 28/100
2/2 [==============================] - 0s 35ms/step - loss: 3.1946 - accuracy: 0.2321 - val_loss: 3.1254 - val_accuracy: 0.1538
Epoch 29/100
2/2 [==============================] - 0s 50ms/step - loss: 3.1899 - accuracy: 0.2321 - val_loss: 3.0963 - val_accuracy: 0.1868
Epoch 30/100
2/2 [==============================] - 0s 37ms/step - loss: 3.1325 - accuracy: 0.2454 - val_loss: 3.0669 - val_accuracy: 0.2088
Epoch 31/100
2/2 [==============================] - 0s 37ms/step - loss: 3.1197 - accuracy: 0.2394 - val_loss: 3.0373 - val_accuracy: 0.2308
Epoch 32/100
2/2 [==============================] - 0s 31ms/step - loss: 3.0809 - accuracy: 0.2539 - val_loss: 3.0075 - val_accuracy: 0.2418
Epoch 33/100
2/2 [==============================] - 0s 35ms/step - loss: 3.0292 - accuracy: 0.2746 - val_loss: 2.9777 - val_accuracy: 0.2527
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 3.0190 - accuracy: 0.2697 - val_loss: 2.9478 - val_accuracy: 0.2637
Epoch 35/100
2/2 [==============================] - 0s 27ms/step - loss: 2.9832 - accuracy: 0.3026 - val_loss: 2.9179 - val_accuracy: 0.2857
Epoch 36/100
2/2 [==============================] - 0s 32ms/step - loss: 2.9730 - accuracy: 0.3086 - val_loss: 2.8881 - val_accuracy: 0.2857
Epoch 37/100
2/2 [==============================] - 0s 36ms/step - loss: 2.8900 - accuracy: 0.3341 - val_loss: 2.8583 - val_accuracy: 0.2967
Epoch 38/100
2/2 [==============================] - 0s 49ms/step - loss: 2.9041 - accuracy: 0.3269 - val_loss: 2.8287 - val_accuracy: 0.3077
Epoch 39/100
2/2 [==============================] - 0s 33ms/step - loss: 2.8899 - accuracy: 0.3451 - val_loss: 2.7991 - val_accuracy: 0.3407
Epoch 40/100
2/2 [==============================] - 0s 35ms/step - loss: 2.8670 - accuracy: 0.3487 - val_loss: 2.7696 - val_accuracy: 0.3626
Epoch 41/100
2/2 [==============================] - 0s 36ms/step - loss: 2.8177 - accuracy: 0.3888 - val_loss: 2.7403 - val_accuracy: 0.3846
Epoch 42/100
2/2 [==============================] - 0s 48ms/step - loss: 2.7876 - accuracy: 0.4010 - val_loss: 2.7112 - val_accuracy: 0.4176
Epoch 43/100
2/2 [==============================] - 0s 35ms/step - loss: 2.7610 - accuracy: 0.4034 - val_loss: 2.6823 - val_accuracy: 0.4396
Epoch 44/100
2/2 [==============================] - 0s 34ms/step - loss: 2.6998 - accuracy: 0.4350 - val_loss: 2.6537 - val_accuracy: 0.4505
Epoch 45/100
2/2 [==============================] - 0s 38ms/step - loss: 2.6796 - accuracy: 0.4593 - val_loss: 2.6254 - val_accuracy: 0.4505
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 2.6576 - accuracy: 0.4642 - val_loss: 2.5973 - val_accuracy: 0.4615
Epoch 47/100
2/2 [==============================] - 0s 33ms/step - loss: 2.6394 - accuracy: 0.4605 - val_loss: 2.5696 - val_accuracy: 0.4835
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 2.6090 - accuracy: 0.4885 - val_loss: 2.5422 - val_accuracy: 0.5275
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 2.5852 - accuracy: 0.5164 - val_loss: 2.5151 - val_accuracy: 0.5385
Epoch 50/100
2/2 [==============================] - 0s 41ms/step - loss: 2.5499 - accuracy: 0.5310 - val_loss: 2.4884 - val_accuracy: 0.5714
Epoch 51/100
2/2 [==============================] - 0s 37ms/step - loss: 2.5184 - accuracy: 0.5443 - val_loss: 2.4619 - val_accuracy: 0.5934
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 2.5026 - accuracy: 0.5638 - val_loss: 2.4359 - val_accuracy: 0.6044
Epoch 53/100
2/2 [==============================] - 0s 39ms/step - loss: 2.4794 - accuracy: 0.5638 - val_loss: 2.4102 - val_accuracy: 0.6374
Epoch 54/100
2/2 [==============================] - 0s 35ms/step - loss: 2.4431 - accuracy: 0.6051 - val_loss: 2.3848 - val_accuracy: 0.6593
Epoch 55/100
2/2 [==============================] - 0s 38ms/step - loss: 2.4119 - accuracy: 0.5942 - val_loss: 2.3599 - val_accuracy: 0.6813
Epoch 56/100
2/2 [==============================] - 0s 26ms/step - loss: 2.3849 - accuracy: 0.6197 - val_loss: 2.3353 - val_accuracy: 0.6813
Epoch 57/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3783 - accuracy: 0.6318 - val_loss: 2.3111 - val_accuracy: 0.6923
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3574 - accuracy: 0.6416 - val_loss: 2.2874 - val_accuracy: 0.7143
Epoch 59/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3475 - accuracy: 0.6574 - val_loss: 2.2640 - val_accuracy: 0.7143
Epoch 60/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3072 - accuracy: 0.6501 - val_loss: 2.2411 - val_accuracy: 0.7253
Epoch 61/100
2/2 [==============================] - 0s 38ms/step - loss: 2.2594 - accuracy: 0.7023 - val_loss: 2.2185 - val_accuracy: 0.7363
Epoch 62/100
2/2 [==============================] - 0s 45ms/step - loss: 2.2451 - accuracy: 0.7242 - val_loss: 2.1963 - val_accuracy: 0.7473
Epoch 63/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2353 - accuracy: 0.7278 - val_loss: 2.1745 - val_accuracy: 0.7582
Epoch 64/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1971 - accuracy: 0.7303 - val_loss: 2.1531 - val_accuracy: 0.7692
Epoch 65/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1825 - accuracy: 0.7485 - val_loss: 2.1321 - val_accuracy: 0.8022
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1479 - accuracy: 0.7606 - val_loss: 2.1114 - val_accuracy: 0.8242
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1576 - accuracy: 0.7521 - val_loss: 2.0912 - val_accuracy: 0.8352
Epoch 68/100
2/2 [==============================] - 0s 43ms/step - loss: 2.1311 - accuracy: 0.7643 - val_loss: 2.0712 - val_accuracy: 0.8352
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1104 - accuracy: 0.7679 - val_loss: 2.0516 - val_accuracy: 0.8352
Epoch 70/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0906 - accuracy: 0.7752 - val_loss: 2.0323 - val_accuracy: 0.8352
Epoch 71/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0622 - accuracy: 0.7910 - val_loss: 2.0134 - val_accuracy: 0.8352
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0454 - accuracy: 0.7959 - val_loss: 1.9947 - val_accuracy: 0.8352
Epoch 73/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0189 - accuracy: 0.8056 - val_loss: 1.9764 - val_accuracy: 0.8352
Epoch 74/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9972 - accuracy: 0.8165 - val_loss: 1.9584 - val_accuracy: 0.8352
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9836 - accuracy: 0.8202 - val_loss: 1.9406 - val_accuracy: 0.8352
Epoch 76/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9566 - accuracy: 0.8275 - val_loss: 1.9232 - val_accuracy: 0.8352
Epoch 77/100
2/2 [==============================] - 0s 48ms/step - loss: 1.9373 - accuracy: 0.8348 - val_loss: 1.9061 - val_accuracy: 0.8352
Epoch 78/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9302 - accuracy: 0.8250 - val_loss: 1.8892 - val_accuracy: 0.8352
Epoch 79/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9088 - accuracy: 0.8202 - val_loss: 1.8726 - val_accuracy: 0.8352
Epoch 80/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9031 - accuracy: 0.8384 - val_loss: 1.8563 - val_accuracy: 0.8352
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8722 - accuracy: 0.8457 - val_loss: 1.8402 - val_accuracy: 0.8352
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8666 - accuracy: 0.8335 - val_loss: 1.8244 - val_accuracy: 0.8352
Epoch 83/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8378 - accuracy: 0.8396 - val_loss: 1.8089 - val_accuracy: 0.8352
Epoch 84/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8448 - accuracy: 0.8287 - val_loss: 1.7935 - val_accuracy: 0.8352
Epoch 85/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8163 - accuracy: 0.8360 - val_loss: 1.7784 - val_accuracy: 0.8352
Epoch 86/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8023 - accuracy: 0.8457 - val_loss: 1.7635 - val_accuracy: 0.8352
Epoch 87/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7814 - accuracy: 0.8481 - val_loss: 1.7489 - val_accuracy: 0.8352
Epoch 88/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7746 - accuracy: 0.8433 - val_loss: 1.7345 - val_accuracy: 0.8352
Epoch 89/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7760 - accuracy: 0.8469 - val_loss: 1.7202 - val_accuracy: 0.8352
Epoch 90/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7380 - accuracy: 0.8408 - val_loss: 1.7062 - val_accuracy: 0.8352
Epoch 91/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7409 - accuracy: 0.8433 - val_loss: 1.6923 - val_accuracy: 0.8352
Epoch 92/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6974 - accuracy: 0.8542 - val_loss: 1.6786 - val_accuracy: 0.8352
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7173 - accuracy: 0.8420 - val_loss: 1.6651 - val_accuracy: 0.8352
Epoch 94/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6990 - accuracy: 0.8554 - val_loss: 1.6518 - val_accuracy: 0.8352
Epoch 95/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6900 - accuracy: 0.8433 - val_loss: 1.6386 - val_accuracy: 0.8352
Epoch 96/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6675 - accuracy: 0.8530 - val_loss: 1.6256 - val_accuracy: 0.8352
Epoch 97/100
2/2 [==============================] - 0s 29ms/step - loss: 1.6539 - accuracy: 0.8530 - val_loss: 1.6127 - val_accuracy: 0.8352
Epoch 98/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6354 - accuracy: 0.8469 - val_loss: 1.6000 - val_accuracy: 0.8352
Epoch 99/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6167 - accuracy: 0.8457 - val_loss: 1.5875 - val_accuracy: 0.8352
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6111 - accuracy: 0.8481 - val_loss: 1.5751 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 5ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 234ms/step - loss: 3.2129 - accuracy: 0.2503 - val_loss: 3.0734 - val_accuracy: 0.2747
Epoch 2/100
2/2 [==============================] - 0s 41ms/step - loss: 3.1850 - accuracy: 0.2904 - val_loss: 3.0715 - val_accuracy: 0.2747
Epoch 3/100
2/2 [==============================] - 0s 41ms/step - loss: 3.1887 - accuracy: 0.2977 - val_loss: 3.0684 - val_accuracy: 0.2747
Epoch 4/100
2/2 [==============================] - 0s 39ms/step - loss: 3.1783 - accuracy: 0.3026 - val_loss: 3.0642 - val_accuracy: 0.2747
Epoch 5/100
2/2 [==============================] - 0s 39ms/step - loss: 3.1756 - accuracy: 0.2795 - val_loss: 3.0591 - val_accuracy: 0.2747
Epoch 6/100
2/2 [==============================] - 0s 37ms/step - loss: 3.1717 - accuracy: 0.2831 - val_loss: 3.0529 - val_accuracy: 0.2747
Epoch 7/100
2/2 [==============================] - 0s 43ms/step - loss: 3.1416 - accuracy: 0.2977 - val_loss: 3.0458 - val_accuracy: 0.2747
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 3.1896 - accuracy: 0.2880 - val_loss: 3.0377 - val_accuracy: 0.2747
Epoch 9/100
2/2 [==============================] - 0s 41ms/step - loss: 3.1554 - accuracy: 0.3013 - val_loss: 3.0286 - val_accuracy: 0.2857
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 3.1270 - accuracy: 0.3001 - val_loss: 3.0187 - val_accuracy: 0.2857
Epoch 11/100
2/2 [==============================] - 0s 40ms/step - loss: 3.1449 - accuracy: 0.3050 - val_loss: 3.0080 - val_accuracy: 0.2967
Epoch 12/100
2/2 [==============================] - 0s 40ms/step - loss: 3.1138 - accuracy: 0.3026 - val_loss: 2.9964 - val_accuracy: 0.2967
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 3.1311 - accuracy: 0.2880 - val_loss: 2.9840 - val_accuracy: 0.2967
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 3.0783 - accuracy: 0.2904 - val_loss: 2.9709 - val_accuracy: 0.2967
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 3.0853 - accuracy: 0.3111 - val_loss: 2.9570 - val_accuracy: 0.2967
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 3.0724 - accuracy: 0.3086 - val_loss: 2.9425 - val_accuracy: 0.2967
Epoch 17/100
2/2 [==============================] - 0s 45ms/step - loss: 3.0196 - accuracy: 0.3220 - val_loss: 2.9273 - val_accuracy: 0.3077
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 3.0515 - accuracy: 0.2868 - val_loss: 2.9115 - val_accuracy: 0.3077
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 2.9979 - accuracy: 0.3341 - val_loss: 2.8952 - val_accuracy: 0.3187
Epoch 20/100
2/2 [==============================] - 0s 40ms/step - loss: 2.9927 - accuracy: 0.3244 - val_loss: 2.8783 - val_accuracy: 0.3407
Epoch 21/100
2/2 [==============================] - 0s 35ms/step - loss: 2.9808 - accuracy: 0.3208 - val_loss: 2.8609 - val_accuracy: 0.3407
Epoch 22/100
2/2 [==============================] - 0s 34ms/step - loss: 2.9140 - accuracy: 0.3572 - val_loss: 2.8430 - val_accuracy: 0.3407
Epoch 23/100
2/2 [==============================] - 0s 40ms/step - loss: 2.9364 - accuracy: 0.3414 - val_loss: 2.8246 - val_accuracy: 0.3407
Epoch 24/100
2/2 [==============================] - 0s 38ms/step - loss: 2.9071 - accuracy: 0.3475 - val_loss: 2.8058 - val_accuracy: 0.3407
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8865 - accuracy: 0.3584 - val_loss: 2.7866 - val_accuracy: 0.3736
Epoch 26/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8850 - accuracy: 0.3451 - val_loss: 2.7671 - val_accuracy: 0.3956
Epoch 27/100
2/2 [==============================] - 0s 40ms/step - loss: 2.8415 - accuracy: 0.3706 - val_loss: 2.7472 - val_accuracy: 0.4176
Epoch 28/100
2/2 [==============================] - 0s 43ms/step - loss: 2.8372 - accuracy: 0.3755 - val_loss: 2.7271 - val_accuracy: 0.4176
Epoch 29/100
2/2 [==============================] - 0s 36ms/step - loss: 2.8169 - accuracy: 0.3961 - val_loss: 2.7067 - val_accuracy: 0.4286
Epoch 30/100
2/2 [==============================] - 0s 41ms/step - loss: 2.7602 - accuracy: 0.3973 - val_loss: 2.6861 - val_accuracy: 0.4286
Epoch 31/100
2/2 [==============================] - 0s 40ms/step - loss: 2.7481 - accuracy: 0.3937 - val_loss: 2.6653 - val_accuracy: 0.4505
Epoch 32/100
2/2 [==============================] - 0s 47ms/step - loss: 2.7619 - accuracy: 0.3937 - val_loss: 2.6443 - val_accuracy: 0.4505
Epoch 33/100
2/2 [==============================] - 0s 29ms/step - loss: 2.7304 - accuracy: 0.3852 - val_loss: 2.6232 - val_accuracy: 0.4615
Epoch 34/100
2/2 [==============================] - 0s 36ms/step - loss: 2.6812 - accuracy: 0.4386 - val_loss: 2.6020 - val_accuracy: 0.4835
Epoch 35/100
2/2 [==============================] - 0s 46ms/step - loss: 2.6659 - accuracy: 0.4350 - val_loss: 2.5806 - val_accuracy: 0.4945
Epoch 36/100
2/2 [==============================] - 0s 43ms/step - loss: 2.6322 - accuracy: 0.4496 - val_loss: 2.5593 - val_accuracy: 0.5055
Epoch 37/100
2/2 [==============================] - 0s 39ms/step - loss: 2.5952 - accuracy: 0.4642 - val_loss: 2.5378 - val_accuracy: 0.5604
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 2.5945 - accuracy: 0.4569 - val_loss: 2.5163 - val_accuracy: 0.5604
Epoch 39/100
2/2 [==============================] - 0s 37ms/step - loss: 2.5794 - accuracy: 0.4739 - val_loss: 2.4949 - val_accuracy: 0.5824
Epoch 40/100
2/2 [==============================] - 0s 39ms/step - loss: 2.5798 - accuracy: 0.4605 - val_loss: 2.4735 - val_accuracy: 0.6044
Epoch 41/100
2/2 [==============================] - 0s 38ms/step - loss: 2.5493 - accuracy: 0.4933 - val_loss: 2.4521 - val_accuracy: 0.6154
Epoch 42/100
2/2 [==============================] - 0s 41ms/step - loss: 2.5217 - accuracy: 0.4848 - val_loss: 2.4308 - val_accuracy: 0.6484
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 2.4725 - accuracy: 0.5164 - val_loss: 2.4095 - val_accuracy: 0.6593
Epoch 44/100
2/2 [==============================] - 0s 39ms/step - loss: 2.4477 - accuracy: 0.5358 - val_loss: 2.3884 - val_accuracy: 0.6593
Epoch 45/100
2/2 [==============================] - 0s 36ms/step - loss: 2.4254 - accuracy: 0.5371 - val_loss: 2.3675 - val_accuracy: 0.6484
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3944 - accuracy: 0.5443 - val_loss: 2.3467 - val_accuracy: 0.6593
Epoch 47/100
2/2 [==============================] - 0s 38ms/step - loss: 2.4107 - accuracy: 0.5626 - val_loss: 2.3260 - val_accuracy: 0.6703
Epoch 48/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3662 - accuracy: 0.5747 - val_loss: 2.3055 - val_accuracy: 0.6813
Epoch 49/100
2/2 [==============================] - 0s 44ms/step - loss: 2.3553 - accuracy: 0.5990 - val_loss: 2.2852 - val_accuracy: 0.7033
Epoch 50/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3256 - accuracy: 0.6087 - val_loss: 2.2651 - val_accuracy: 0.7033
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3172 - accuracy: 0.6039 - val_loss: 2.2452 - val_accuracy: 0.7363
Epoch 52/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2744 - accuracy: 0.6367 - val_loss: 2.2254 - val_accuracy: 0.7363
Epoch 53/100
2/2 [==============================] - 0s 38ms/step - loss: 2.2494 - accuracy: 0.6671 - val_loss: 2.2059 - val_accuracy: 0.7363
Epoch 54/100
2/2 [==============================] - 0s 39ms/step - loss: 2.2543 - accuracy: 0.6549 - val_loss: 2.1866 - val_accuracy: 0.7473
Epoch 55/100
2/2 [==============================] - 0s 36ms/step - loss: 2.2151 - accuracy: 0.6744 - val_loss: 2.1675 - val_accuracy: 0.7692
Epoch 56/100
2/2 [==============================] - 0s 38ms/step - loss: 2.2220 - accuracy: 0.6488 - val_loss: 2.1487 - val_accuracy: 0.7582
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1834 - accuracy: 0.6756 - val_loss: 2.1302 - val_accuracy: 0.7692
Epoch 58/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1726 - accuracy: 0.7060 - val_loss: 2.1119 - val_accuracy: 0.7802
Epoch 59/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1423 - accuracy: 0.7217 - val_loss: 2.0938 - val_accuracy: 0.7802
Epoch 60/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1256 - accuracy: 0.7412 - val_loss: 2.0760 - val_accuracy: 0.8022
Epoch 61/100
2/2 [==============================] - 0s 42ms/step - loss: 2.0975 - accuracy: 0.7618 - val_loss: 2.0584 - val_accuracy: 0.8132
Epoch 62/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0984 - accuracy: 0.7448 - val_loss: 2.0411 - val_accuracy: 0.8352
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0698 - accuracy: 0.7436 - val_loss: 2.0239 - val_accuracy: 0.8352
Epoch 64/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0458 - accuracy: 0.7728 - val_loss: 2.0071 - val_accuracy: 0.8462
Epoch 65/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0264 - accuracy: 0.7691 - val_loss: 1.9904 - val_accuracy: 0.8571
Epoch 66/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9992 - accuracy: 0.7825 - val_loss: 1.9739 - val_accuracy: 0.8462
Epoch 67/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9762 - accuracy: 0.7813 - val_loss: 1.9577 - val_accuracy: 0.8462
Epoch 68/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9673 - accuracy: 0.7922 - val_loss: 1.9417 - val_accuracy: 0.8571
Epoch 69/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9687 - accuracy: 0.7934 - val_loss: 1.9260 - val_accuracy: 0.8571
Epoch 70/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9464 - accuracy: 0.7983 - val_loss: 1.9105 - val_accuracy: 0.8681
Epoch 71/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9072 - accuracy: 0.8007 - val_loss: 1.8952 - val_accuracy: 0.8681
Epoch 72/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9015 - accuracy: 0.8141 - val_loss: 1.8802 - val_accuracy: 0.8681
Epoch 73/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9037 - accuracy: 0.8117 - val_loss: 1.8653 - val_accuracy: 0.8681
Epoch 74/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8777 - accuracy: 0.8092 - val_loss: 1.8507 - val_accuracy: 0.8681
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8493 - accuracy: 0.8287 - val_loss: 1.8362 - val_accuracy: 0.8681
Epoch 76/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8612 - accuracy: 0.8104 - val_loss: 1.8219 - val_accuracy: 0.8681
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8402 - accuracy: 0.8275 - val_loss: 1.8079 - val_accuracy: 0.8681
Epoch 78/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8175 - accuracy: 0.8420 - val_loss: 1.7940 - val_accuracy: 0.8681
Epoch 79/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8134 - accuracy: 0.8311 - val_loss: 1.7804 - val_accuracy: 0.8681
Epoch 80/100
2/2 [==============================] - 0s 45ms/step - loss: 1.8000 - accuracy: 0.8262 - val_loss: 1.7669 - val_accuracy: 0.8681
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7876 - accuracy: 0.8348 - val_loss: 1.7535 - val_accuracy: 0.8681
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7689 - accuracy: 0.8408 - val_loss: 1.7404 - val_accuracy: 0.8681
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7615 - accuracy: 0.8384 - val_loss: 1.7274 - val_accuracy: 0.8681
Epoch 84/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7432 - accuracy: 0.8457 - val_loss: 1.7146 - val_accuracy: 0.8681
Epoch 85/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7367 - accuracy: 0.8433 - val_loss: 1.7020 - val_accuracy: 0.8681
Epoch 86/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7115 - accuracy: 0.8396 - val_loss: 1.6895 - val_accuracy: 0.8681
Epoch 87/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6867 - accuracy: 0.8469 - val_loss: 1.6772 - val_accuracy: 0.8681
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6745 - accuracy: 0.8420 - val_loss: 1.6650 - val_accuracy: 0.8681
Epoch 89/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6817 - accuracy: 0.8445 - val_loss: 1.6530 - val_accuracy: 0.8681
Epoch 90/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6638 - accuracy: 0.8433 - val_loss: 1.6411 - val_accuracy: 0.8681
Epoch 91/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6443 - accuracy: 0.8530 - val_loss: 1.6294 - val_accuracy: 0.8681
Epoch 92/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6340 - accuracy: 0.8408 - val_loss: 1.6178 - val_accuracy: 0.8681
Epoch 93/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6358 - accuracy: 0.8372 - val_loss: 1.6064 - val_accuracy: 0.8681
Epoch 94/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6141 - accuracy: 0.8408 - val_loss: 1.5951 - val_accuracy: 0.8681
Epoch 95/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5999 - accuracy: 0.8445 - val_loss: 1.5839 - val_accuracy: 0.8681
Epoch 96/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5975 - accuracy: 0.8408 - val_loss: 1.5729 - val_accuracy: 0.8681
Epoch 97/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5701 - accuracy: 0.8420 - val_loss: 1.5620 - val_accuracy: 0.8681
Epoch 98/100
2/2 [==============================] - 0s 45ms/step - loss: 1.5700 - accuracy: 0.8469 - val_loss: 1.5512 - val_accuracy: 0.8681
Epoch 99/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5430 - accuracy: 0.8493 - val_loss: 1.5405 - val_accuracy: 0.8681
Epoch 100/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5443 - accuracy: 0.8445 - val_loss: 1.5300 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 238ms/step - loss: 3.0458 - accuracy: 0.3026 - val_loss: 2.9799 - val_accuracy: 0.2637
Epoch 2/100
2/2 [==============================] - 0s 45ms/step - loss: 3.0526 - accuracy: 0.3317 - val_loss: 2.9780 - val_accuracy: 0.2637
Epoch 3/100
2/2 [==============================] - 0s 45ms/step - loss: 3.0309 - accuracy: 0.3062 - val_loss: 2.9751 - val_accuracy: 0.2637
Epoch 4/100
2/2 [==============================] - 0s 42ms/step - loss: 3.0452 - accuracy: 0.3171 - val_loss: 2.9712 - val_accuracy: 0.2747
Epoch 5/100
2/2 [==============================] - 0s 38ms/step - loss: 3.0411 - accuracy: 0.3038 - val_loss: 2.9662 - val_accuracy: 0.2747
Epoch 6/100
2/2 [==============================] - 0s 45ms/step - loss: 3.0008 - accuracy: 0.3208 - val_loss: 2.9603 - val_accuracy: 0.2857
Epoch 7/100
2/2 [==============================] - 0s 38ms/step - loss: 2.9768 - accuracy: 0.3159 - val_loss: 2.9535 - val_accuracy: 0.3077
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 3.0248 - accuracy: 0.3111 - val_loss: 2.9458 - val_accuracy: 0.3077
Epoch 9/100
2/2 [==============================] - 0s 37ms/step - loss: 2.9882 - accuracy: 0.3475 - val_loss: 2.9372 - val_accuracy: 0.3077
Epoch 10/100
2/2 [==============================] - 0s 37ms/step - loss: 2.9799 - accuracy: 0.3499 - val_loss: 2.9278 - val_accuracy: 0.3077
Epoch 11/100
2/2 [==============================] - 0s 39ms/step - loss: 2.9653 - accuracy: 0.3560 - val_loss: 2.9176 - val_accuracy: 0.3407
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 2.9921 - accuracy: 0.3269 - val_loss: 2.9066 - val_accuracy: 0.3516
Epoch 13/100
2/2 [==============================] - 0s 35ms/step - loss: 2.9958 - accuracy: 0.3548 - val_loss: 2.8949 - val_accuracy: 0.3516
Epoch 14/100
2/2 [==============================] - 0s 46ms/step - loss: 2.9564 - accuracy: 0.3426 - val_loss: 2.8825 - val_accuracy: 0.3846
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 2.9305 - accuracy: 0.3779 - val_loss: 2.8694 - val_accuracy: 0.3846
Epoch 16/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8881 - accuracy: 0.3913 - val_loss: 2.8558 - val_accuracy: 0.4066
Epoch 17/100
2/2 [==============================] - 0s 39ms/step - loss: 2.9047 - accuracy: 0.3876 - val_loss: 2.8415 - val_accuracy: 0.4066
Epoch 18/100
2/2 [==============================] - 0s 44ms/step - loss: 2.8503 - accuracy: 0.4083 - val_loss: 2.8267 - val_accuracy: 0.4176
Epoch 19/100
2/2 [==============================] - 0s 27ms/step - loss: 2.8669 - accuracy: 0.4034 - val_loss: 2.8114 - val_accuracy: 0.4286
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8559 - accuracy: 0.4228 - val_loss: 2.7957 - val_accuracy: 0.4286
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 2.8129 - accuracy: 0.4362 - val_loss: 2.7794 - val_accuracy: 0.4286
Epoch 22/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8005 - accuracy: 0.4289 - val_loss: 2.7628 - val_accuracy: 0.4615
Epoch 23/100
2/2 [==============================] - 0s 37ms/step - loss: 2.7830 - accuracy: 0.4569 - val_loss: 2.7458 - val_accuracy: 0.4835
Epoch 24/100
2/2 [==============================] - 0s 37ms/step - loss: 2.7821 - accuracy: 0.4557 - val_loss: 2.7285 - val_accuracy: 0.5055
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 2.7528 - accuracy: 0.4544 - val_loss: 2.7108 - val_accuracy: 0.5275
Epoch 26/100
2/2 [==============================] - 0s 46ms/step - loss: 2.7219 - accuracy: 0.4727 - val_loss: 2.6928 - val_accuracy: 0.5604
Epoch 27/100
2/2 [==============================] - 0s 35ms/step - loss: 2.7413 - accuracy: 0.4775 - val_loss: 2.6746 - val_accuracy: 0.5604
Epoch 28/100
2/2 [==============================] - 0s 38ms/step - loss: 2.7228 - accuracy: 0.4763 - val_loss: 2.6561 - val_accuracy: 0.5824
Epoch 29/100
2/2 [==============================] - 0s 42ms/step - loss: 2.7118 - accuracy: 0.4812 - val_loss: 2.6374 - val_accuracy: 0.5934
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 2.6412 - accuracy: 0.5431 - val_loss: 2.6185 - val_accuracy: 0.5934
Epoch 31/100
2/2 [==============================] - 0s 37ms/step - loss: 2.6430 - accuracy: 0.5310 - val_loss: 2.5995 - val_accuracy: 0.5934
Epoch 32/100
2/2 [==============================] - 0s 31ms/step - loss: 2.6218 - accuracy: 0.5565 - val_loss: 2.5803 - val_accuracy: 0.6374
Epoch 33/100
2/2 [==============================] - 0s 40ms/step - loss: 2.5866 - accuracy: 0.5759 - val_loss: 2.5611 - val_accuracy: 0.6374
Epoch 34/100
2/2 [==============================] - 0s 46ms/step - loss: 2.5594 - accuracy: 0.5772 - val_loss: 2.5417 - val_accuracy: 0.6374
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 2.5539 - accuracy: 0.5589 - val_loss: 2.5223 - val_accuracy: 0.6374
Epoch 36/100
2/2 [==============================] - 0s 40ms/step - loss: 2.5246 - accuracy: 0.6173 - val_loss: 2.5028 - val_accuracy: 0.6593
Epoch 37/100
2/2 [==============================] - 0s 38ms/step - loss: 2.5121 - accuracy: 0.5942 - val_loss: 2.4834 - val_accuracy: 0.6593
Epoch 38/100
2/2 [==============================] - 0s 45ms/step - loss: 2.5025 - accuracy: 0.6160 - val_loss: 2.4639 - val_accuracy: 0.6923
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 2.4669 - accuracy: 0.6258 - val_loss: 2.4445 - val_accuracy: 0.6923
Epoch 40/100
2/2 [==============================] - 0s 37ms/step - loss: 2.4810 - accuracy: 0.6221 - val_loss: 2.4251 - val_accuracy: 0.6923
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 2.4451 - accuracy: 0.6343 - val_loss: 2.4057 - val_accuracy: 0.6923
Epoch 42/100
2/2 [==============================] - 0s 36ms/step - loss: 2.4319 - accuracy: 0.6391 - val_loss: 2.3864 - val_accuracy: 0.6923
Epoch 43/100
2/2 [==============================] - 0s 38ms/step - loss: 2.4020 - accuracy: 0.6549 - val_loss: 2.3672 - val_accuracy: 0.7033
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 2.3862 - accuracy: 0.6792 - val_loss: 2.3480 - val_accuracy: 0.7143
Epoch 45/100
2/2 [==============================] - 0s 43ms/step - loss: 2.3504 - accuracy: 0.6914 - val_loss: 2.3290 - val_accuracy: 0.7363
Epoch 46/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3293 - accuracy: 0.6731 - val_loss: 2.3101 - val_accuracy: 0.7473
Epoch 47/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3073 - accuracy: 0.7169 - val_loss: 2.2913 - val_accuracy: 0.7363
Epoch 48/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3020 - accuracy: 0.7108 - val_loss: 2.2726 - val_accuracy: 0.7582
Epoch 49/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2836 - accuracy: 0.7315 - val_loss: 2.2541 - val_accuracy: 0.7802
Epoch 50/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2480 - accuracy: 0.7339 - val_loss: 2.2357 - val_accuracy: 0.7912
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 2.2398 - accuracy: 0.7424 - val_loss: 2.2175 - val_accuracy: 0.8022
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 2.2289 - accuracy: 0.7217 - val_loss: 2.1994 - val_accuracy: 0.8132
Epoch 53/100
2/2 [==============================] - 0s 51ms/step - loss: 2.1985 - accuracy: 0.7533 - val_loss: 2.1815 - val_accuracy: 0.8132
Epoch 54/100
2/2 [==============================] - 0s 34ms/step - loss: 2.1828 - accuracy: 0.7606 - val_loss: 2.1638 - val_accuracy: 0.8132
Epoch 55/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1674 - accuracy: 0.7618 - val_loss: 2.1463 - val_accuracy: 0.8132
Epoch 56/100
2/2 [==============================] - 0s 46ms/step - loss: 2.1407 - accuracy: 0.7618 - val_loss: 2.1289 - val_accuracy: 0.8132
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1404 - accuracy: 0.7776 - val_loss: 2.1117 - val_accuracy: 0.8132
Epoch 58/100
2/2 [==============================] - 0s 42ms/step - loss: 2.1064 - accuracy: 0.7801 - val_loss: 2.0947 - val_accuracy: 0.8242
Epoch 59/100
2/2 [==============================] - 0s 48ms/step - loss: 2.1043 - accuracy: 0.7813 - val_loss: 2.0778 - val_accuracy: 0.8242
Epoch 60/100
2/2 [==============================] - 0s 42ms/step - loss: 2.0943 - accuracy: 0.7849 - val_loss: 2.0611 - val_accuracy: 0.8352
Epoch 61/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0707 - accuracy: 0.7825 - val_loss: 2.0445 - val_accuracy: 0.8352
Epoch 62/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0402 - accuracy: 0.8068 - val_loss: 2.0282 - val_accuracy: 0.8571
Epoch 63/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0347 - accuracy: 0.7934 - val_loss: 2.0120 - val_accuracy: 0.8571
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0107 - accuracy: 0.8080 - val_loss: 1.9960 - val_accuracy: 0.8571
Epoch 65/100
2/2 [==============================] - 0s 33ms/step - loss: 1.9845 - accuracy: 0.8104 - val_loss: 1.9802 - val_accuracy: 0.8571
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9892 - accuracy: 0.8068 - val_loss: 1.9646 - val_accuracy: 0.8681
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9723 - accuracy: 0.8056 - val_loss: 1.9491 - val_accuracy: 0.8681
Epoch 68/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9559 - accuracy: 0.8190 - val_loss: 1.9339 - val_accuracy: 0.8681
Epoch 69/100
2/2 [==============================] - 0s 35ms/step - loss: 1.9445 - accuracy: 0.8177 - val_loss: 1.9188 - val_accuracy: 0.8681
Epoch 70/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9265 - accuracy: 0.8202 - val_loss: 1.9038 - val_accuracy: 0.8681
Epoch 71/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9218 - accuracy: 0.8250 - val_loss: 1.8891 - val_accuracy: 0.8681
Epoch 72/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8931 - accuracy: 0.8360 - val_loss: 1.8745 - val_accuracy: 0.8681
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8840 - accuracy: 0.8299 - val_loss: 1.8601 - val_accuracy: 0.8791
Epoch 74/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8580 - accuracy: 0.8384 - val_loss: 1.8458 - val_accuracy: 0.8791
Epoch 75/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8591 - accuracy: 0.8348 - val_loss: 1.8317 - val_accuracy: 0.8791
Epoch 76/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8309 - accuracy: 0.8287 - val_loss: 1.8178 - val_accuracy: 0.8791
Epoch 77/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8302 - accuracy: 0.8384 - val_loss: 1.8040 - val_accuracy: 0.8791
Epoch 78/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8145 - accuracy: 0.8408 - val_loss: 1.7904 - val_accuracy: 0.9011
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8057 - accuracy: 0.8299 - val_loss: 1.7769 - val_accuracy: 0.9011
Epoch 80/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7843 - accuracy: 0.8348 - val_loss: 1.7636 - val_accuracy: 0.9011
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7647 - accuracy: 0.8469 - val_loss: 1.7504 - val_accuracy: 0.9011
Epoch 82/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7496 - accuracy: 0.8518 - val_loss: 1.7374 - val_accuracy: 0.9011
Epoch 83/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7537 - accuracy: 0.8469 - val_loss: 1.7244 - val_accuracy: 0.9011
Epoch 84/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7338 - accuracy: 0.8433 - val_loss: 1.7116 - val_accuracy: 0.9011
Epoch 85/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7439 - accuracy: 0.8420 - val_loss: 1.6990 - val_accuracy: 0.9011
Epoch 86/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7204 - accuracy: 0.8445 - val_loss: 1.6864 - val_accuracy: 0.9011
Epoch 87/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6983 - accuracy: 0.8481 - val_loss: 1.6740 - val_accuracy: 0.9011
Epoch 88/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7056 - accuracy: 0.8433 - val_loss: 1.6617 - val_accuracy: 0.9011
Epoch 89/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6797 - accuracy: 0.8433 - val_loss: 1.6496 - val_accuracy: 0.9011
Epoch 90/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6796 - accuracy: 0.8408 - val_loss: 1.6375 - val_accuracy: 0.9011
Epoch 91/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6636 - accuracy: 0.8457 - val_loss: 1.6256 - val_accuracy: 0.9011
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6411 - accuracy: 0.8433 - val_loss: 1.6138 - val_accuracy: 0.9011
Epoch 93/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6332 - accuracy: 0.8457 - val_loss: 1.6021 - val_accuracy: 0.9011
Epoch 94/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6129 - accuracy: 0.8481 - val_loss: 1.5906 - val_accuracy: 0.9011
Epoch 95/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6207 - accuracy: 0.8469 - val_loss: 1.5791 - val_accuracy: 0.9011
Epoch 96/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6041 - accuracy: 0.8433 - val_loss: 1.5677 - val_accuracy: 0.9011
Epoch 97/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5883 - accuracy: 0.8433 - val_loss: 1.5564 - val_accuracy: 0.9011
Epoch 98/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5871 - accuracy: 0.8433 - val_loss: 1.5452 - val_accuracy: 0.9011
Epoch 99/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5761 - accuracy: 0.8433 - val_loss: 1.5342 - val_accuracy: 0.9011
Epoch 100/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5508 - accuracy: 0.8433 - val_loss: 1.5232 - val_accuracy: 0.9011
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 229ms/step - loss: 3.7353 - accuracy: 0.1142 - val_loss: 3.5666 - val_accuracy: 0.0440
Epoch 2/100
2/2 [==============================] - 0s 29ms/step - loss: 3.7663 - accuracy: 0.0948 - val_loss: 3.5634 - val_accuracy: 0.0440
Epoch 3/100
2/2 [==============================] - 0s 39ms/step - loss: 3.7276 - accuracy: 0.1045 - val_loss: 3.5584 - val_accuracy: 0.0440
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 3.7163 - accuracy: 0.1106 - val_loss: 3.5518 - val_accuracy: 0.0440
Epoch 5/100
2/2 [==============================] - 0s 41ms/step - loss: 3.7215 - accuracy: 0.1069 - val_loss: 3.5434 - val_accuracy: 0.0440
Epoch 6/100
2/2 [==============================] - 0s 43ms/step - loss: 3.6592 - accuracy: 0.1154 - val_loss: 3.5335 - val_accuracy: 0.0440
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 3.6962 - accuracy: 0.1203 - val_loss: 3.5220 - val_accuracy: 0.0440
Epoch 8/100
2/2 [==============================] - 0s 39ms/step - loss: 3.6718 - accuracy: 0.1033 - val_loss: 3.5089 - val_accuracy: 0.0440
Epoch 9/100
2/2 [==============================] - 0s 37ms/step - loss: 3.6882 - accuracy: 0.1239 - val_loss: 3.4944 - val_accuracy: 0.0440
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 3.6558 - accuracy: 0.1191 - val_loss: 3.4785 - val_accuracy: 0.0549
Epoch 11/100
2/2 [==============================] - 0s 29ms/step - loss: 3.6335 - accuracy: 0.1154 - val_loss: 3.4613 - val_accuracy: 0.0549
Epoch 12/100
2/2 [==============================] - 0s 32ms/step - loss: 3.6234 - accuracy: 0.1239 - val_loss: 3.4427 - val_accuracy: 0.0769
Epoch 13/100
2/2 [==============================] - 0s 35ms/step - loss: 3.6032 - accuracy: 0.1118 - val_loss: 3.4230 - val_accuracy: 0.0769
Epoch 14/100
2/2 [==============================] - 0s 50ms/step - loss: 3.5817 - accuracy: 0.1276 - val_loss: 3.4020 - val_accuracy: 0.0769
Epoch 15/100
2/2 [==============================] - 0s 44ms/step - loss: 3.5307 - accuracy: 0.1507 - val_loss: 3.3800 - val_accuracy: 0.0879
Epoch 16/100
2/2 [==============================] - 0s 38ms/step - loss: 3.5582 - accuracy: 0.1507 - val_loss: 3.3569 - val_accuracy: 0.0879
Epoch 17/100
2/2 [==============================] - 0s 35ms/step - loss: 3.4923 - accuracy: 0.1349 - val_loss: 3.3329 - val_accuracy: 0.0879
Epoch 18/100
2/2 [==============================] - 0s 48ms/step - loss: 3.4603 - accuracy: 0.1434 - val_loss: 3.3079 - val_accuracy: 0.0879
Epoch 19/100
2/2 [==============================] - 0s 28ms/step - loss: 3.4700 - accuracy: 0.1495 - val_loss: 3.2821 - val_accuracy: 0.0879
Epoch 20/100
2/2 [==============================] - 0s 36ms/step - loss: 3.4367 - accuracy: 0.1555 - val_loss: 3.2555 - val_accuracy: 0.0879
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 3.4066 - accuracy: 0.1628 - val_loss: 3.2282 - val_accuracy: 0.0879
Epoch 22/100
2/2 [==============================] - 0s 39ms/step - loss: 3.3679 - accuracy: 0.1567 - val_loss: 3.2002 - val_accuracy: 0.0879
Epoch 23/100
2/2 [==============================] - 0s 29ms/step - loss: 3.3177 - accuracy: 0.1713 - val_loss: 3.1715 - val_accuracy: 0.0879
Epoch 24/100
2/2 [==============================] - 0s 36ms/step - loss: 3.2514 - accuracy: 0.1896 - val_loss: 3.1424 - val_accuracy: 0.0989
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 3.2745 - accuracy: 0.1835 - val_loss: 3.1129 - val_accuracy: 0.1429
Epoch 26/100
2/2 [==============================] - 0s 32ms/step - loss: 3.2666 - accuracy: 0.1896 - val_loss: 3.0829 - val_accuracy: 0.1538
Epoch 27/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1974 - accuracy: 0.2041 - val_loss: 3.0525 - val_accuracy: 0.1648
Epoch 28/100
2/2 [==============================] - 0s 35ms/step - loss: 3.1992 - accuracy: 0.2090 - val_loss: 3.0219 - val_accuracy: 0.1758
Epoch 29/100
2/2 [==============================] - 0s 40ms/step - loss: 3.1594 - accuracy: 0.2199 - val_loss: 2.9911 - val_accuracy: 0.1868
Epoch 30/100
2/2 [==============================] - 0s 40ms/step - loss: 3.0988 - accuracy: 0.2333 - val_loss: 2.9600 - val_accuracy: 0.2198
Epoch 31/100
2/2 [==============================] - 0s 31ms/step - loss: 3.0807 - accuracy: 0.2454 - val_loss: 2.9288 - val_accuracy: 0.2308
Epoch 32/100
2/2 [==============================] - 0s 42ms/step - loss: 3.0482 - accuracy: 0.2527 - val_loss: 2.8975 - val_accuracy: 0.2308
Epoch 33/100
2/2 [==============================] - 0s 42ms/step - loss: 3.0399 - accuracy: 0.2770 - val_loss: 2.8661 - val_accuracy: 0.2527
Epoch 34/100
2/2 [==============================] - 0s 46ms/step - loss: 2.9518 - accuracy: 0.2904 - val_loss: 2.8347 - val_accuracy: 0.2527
Epoch 35/100
2/2 [==============================] - 0s 30ms/step - loss: 2.9583 - accuracy: 0.2734 - val_loss: 2.8034 - val_accuracy: 0.2527
Epoch 36/100
2/2 [==============================] - 0s 34ms/step - loss: 2.9036 - accuracy: 0.2989 - val_loss: 2.7720 - val_accuracy: 0.2637
Epoch 37/100
2/2 [==============================] - 0s 54ms/step - loss: 2.8957 - accuracy: 0.2880 - val_loss: 2.7408 - val_accuracy: 0.2637
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8601 - accuracy: 0.3208 - val_loss: 2.7098 - val_accuracy: 0.2747
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8273 - accuracy: 0.3244 - val_loss: 2.6789 - val_accuracy: 0.2857
Epoch 40/100
2/2 [==============================] - 0s 26ms/step - loss: 2.7872 - accuracy: 0.3463 - val_loss: 2.6482 - val_accuracy: 0.2967
Epoch 41/100
2/2 [==============================] - 0s 39ms/step - loss: 2.7242 - accuracy: 0.3694 - val_loss: 2.6178 - val_accuracy: 0.3187
Epoch 42/100
2/2 [==============================] - 0s 38ms/step - loss: 2.7220 - accuracy: 0.3742 - val_loss: 2.5876 - val_accuracy: 0.3297
Epoch 43/100
2/2 [==============================] - 0s 46ms/step - loss: 2.6637 - accuracy: 0.3791 - val_loss: 2.5577 - val_accuracy: 0.3516
Epoch 44/100
2/2 [==============================] - 0s 41ms/step - loss: 2.6524 - accuracy: 0.3925 - val_loss: 2.5281 - val_accuracy: 0.3626
Epoch 45/100
2/2 [==============================] - 0s 38ms/step - loss: 2.6078 - accuracy: 0.4131 - val_loss: 2.4988 - val_accuracy: 0.3956
Epoch 46/100
2/2 [==============================] - 0s 48ms/step - loss: 2.5890 - accuracy: 0.4131 - val_loss: 2.4699 - val_accuracy: 0.4176
Epoch 47/100
2/2 [==============================] - 0s 40ms/step - loss: 2.5461 - accuracy: 0.4459 - val_loss: 2.4413 - val_accuracy: 0.4286
Epoch 48/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5217 - accuracy: 0.4423 - val_loss: 2.4131 - val_accuracy: 0.4615
Epoch 49/100
2/2 [==============================] - 0s 38ms/step - loss: 2.5045 - accuracy: 0.4654 - val_loss: 2.3853 - val_accuracy: 0.4945
Epoch 50/100
2/2 [==============================] - 0s 42ms/step - loss: 2.4503 - accuracy: 0.5079 - val_loss: 2.3579 - val_accuracy: 0.4945
Epoch 51/100
2/2 [==============================] - 0s 56ms/step - loss: 2.4262 - accuracy: 0.5006 - val_loss: 2.3310 - val_accuracy: 0.5165
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 2.4134 - accuracy: 0.5018 - val_loss: 2.3045 - val_accuracy: 0.5275
Epoch 53/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3749 - accuracy: 0.5103 - val_loss: 2.2784 - val_accuracy: 0.5495
Epoch 54/100
2/2 [==============================] - 0s 43ms/step - loss: 2.3640 - accuracy: 0.5358 - val_loss: 2.2528 - val_accuracy: 0.5714
Epoch 55/100
2/2 [==============================] - 0s 34ms/step - loss: 2.3314 - accuracy: 0.5541 - val_loss: 2.2275 - val_accuracy: 0.6374
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 2.2916 - accuracy: 0.5832 - val_loss: 2.2027 - val_accuracy: 0.6703
Epoch 57/100
2/2 [==============================] - 0s 53ms/step - loss: 2.2652 - accuracy: 0.5881 - val_loss: 2.1783 - val_accuracy: 0.6923
Epoch 58/100
2/2 [==============================] - 0s 48ms/step - loss: 2.2441 - accuracy: 0.6015 - val_loss: 2.1543 - val_accuracy: 0.7143
Epoch 59/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2176 - accuracy: 0.6330 - val_loss: 2.1308 - val_accuracy: 0.7253
Epoch 60/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1843 - accuracy: 0.6258 - val_loss: 2.1077 - val_accuracy: 0.7143
Epoch 61/100
2/2 [==============================] - 0s 46ms/step - loss: 2.1761 - accuracy: 0.6525 - val_loss: 2.0851 - val_accuracy: 0.7143
Epoch 62/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1455 - accuracy: 0.6501 - val_loss: 2.0628 - val_accuracy: 0.7363
Epoch 63/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1298 - accuracy: 0.6804 - val_loss: 2.0410 - val_accuracy: 0.7473
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0824 - accuracy: 0.6999 - val_loss: 2.0196 - val_accuracy: 0.7692
Epoch 65/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0867 - accuracy: 0.6914 - val_loss: 1.9986 - val_accuracy: 0.7692
Epoch 66/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0622 - accuracy: 0.6974 - val_loss: 1.9780 - val_accuracy: 0.7802
Epoch 67/100
2/2 [==============================] - 0s 32ms/step - loss: 2.0206 - accuracy: 0.7315 - val_loss: 1.9578 - val_accuracy: 0.8022
Epoch 68/100
2/2 [==============================] - 0s 51ms/step - loss: 2.0139 - accuracy: 0.7412 - val_loss: 1.9379 - val_accuracy: 0.8132
Epoch 69/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9878 - accuracy: 0.7497 - val_loss: 1.9185 - val_accuracy: 0.8132
Epoch 70/100
2/2 [==============================] - 0s 28ms/step - loss: 1.9540 - accuracy: 0.7643 - val_loss: 1.8995 - val_accuracy: 0.8242
Epoch 71/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9445 - accuracy: 0.7728 - val_loss: 1.8808 - val_accuracy: 0.8242
Epoch 72/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9255 - accuracy: 0.7849 - val_loss: 1.8624 - val_accuracy: 0.8462
Epoch 73/100
2/2 [==============================] - 0s 52ms/step - loss: 1.9234 - accuracy: 0.7691 - val_loss: 1.8445 - val_accuracy: 0.8462
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8945 - accuracy: 0.7849 - val_loss: 1.8269 - val_accuracy: 0.8462
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8776 - accuracy: 0.7995 - val_loss: 1.8096 - val_accuracy: 0.8462
Epoch 76/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8555 - accuracy: 0.7947 - val_loss: 1.7927 - val_accuracy: 0.8462
Epoch 77/100
2/2 [==============================] - 0s 50ms/step - loss: 1.8404 - accuracy: 0.8044 - val_loss: 1.7761 - val_accuracy: 0.8462
Epoch 78/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8099 - accuracy: 0.8190 - val_loss: 1.7598 - val_accuracy: 0.8571
Epoch 79/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8026 - accuracy: 0.8141 - val_loss: 1.7437 - val_accuracy: 0.8571
Epoch 80/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7956 - accuracy: 0.8190 - val_loss: 1.7280 - val_accuracy: 0.8571
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7725 - accuracy: 0.8335 - val_loss: 1.7125 - val_accuracy: 0.8571
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7454 - accuracy: 0.8262 - val_loss: 1.6974 - val_accuracy: 0.8571
Epoch 83/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7412 - accuracy: 0.8348 - val_loss: 1.6825 - val_accuracy: 0.8571
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7198 - accuracy: 0.8287 - val_loss: 1.6679 - val_accuracy: 0.8571
Epoch 85/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7040 - accuracy: 0.8348 - val_loss: 1.6535 - val_accuracy: 0.8571
Epoch 86/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7015 - accuracy: 0.8384 - val_loss: 1.6394 - val_accuracy: 0.8571
Epoch 87/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6907 - accuracy: 0.8335 - val_loss: 1.6255 - val_accuracy: 0.8571
Epoch 88/100
2/2 [==============================] - 0s 48ms/step - loss: 1.6536 - accuracy: 0.8396 - val_loss: 1.6118 - val_accuracy: 0.8571
Epoch 89/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6429 - accuracy: 0.8433 - val_loss: 1.5984 - val_accuracy: 0.8571
Epoch 90/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6399 - accuracy: 0.8360 - val_loss: 1.5853 - val_accuracy: 0.8571
Epoch 91/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6248 - accuracy: 0.8408 - val_loss: 1.5723 - val_accuracy: 0.8681
Epoch 92/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6021 - accuracy: 0.8457 - val_loss: 1.5595 - val_accuracy: 0.8681
Epoch 93/100
2/2 [==============================] - 0s 50ms/step - loss: 1.5859 - accuracy: 0.8433 - val_loss: 1.5470 - val_accuracy: 0.8681
Epoch 94/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5756 - accuracy: 0.8384 - val_loss: 1.5347 - val_accuracy: 0.8681
Epoch 95/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5627 - accuracy: 0.8396 - val_loss: 1.5225 - val_accuracy: 0.8681
Epoch 96/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5588 - accuracy: 0.8408 - val_loss: 1.5105 - val_accuracy: 0.8681
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5307 - accuracy: 0.8408 - val_loss: 1.4987 - val_accuracy: 0.8681
Epoch 98/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5424 - accuracy: 0.8420 - val_loss: 1.4871 - val_accuracy: 0.8681
Epoch 99/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5240 - accuracy: 0.8420 - val_loss: 1.4757 - val_accuracy: 0.8681
Epoch 100/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5135 - accuracy: 0.8420 - val_loss: 1.4644 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 218ms/step - loss: 2.8590 - accuracy: 0.3852 - val_loss: 2.9394 - val_accuracy: 0.2637
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8166 - accuracy: 0.4119 - val_loss: 2.9378 - val_accuracy: 0.2637
Epoch 3/100
2/2 [==============================] - 0s 49ms/step - loss: 2.8337 - accuracy: 0.3852 - val_loss: 2.9352 - val_accuracy: 0.2637
Epoch 4/100
2/2 [==============================] - 0s 45ms/step - loss: 2.8503 - accuracy: 0.3888 - val_loss: 2.9317 - val_accuracy: 0.2637
Epoch 5/100
2/2 [==============================] - 0s 42ms/step - loss: 2.8470 - accuracy: 0.3937 - val_loss: 2.9274 - val_accuracy: 0.2637
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 2.8177 - accuracy: 0.3998 - val_loss: 2.9221 - val_accuracy: 0.2637
Epoch 7/100
2/2 [==============================] - 0s 37ms/step - loss: 2.8240 - accuracy: 0.4083 - val_loss: 2.9161 - val_accuracy: 0.2637
Epoch 8/100
2/2 [==============================] - 0s 42ms/step - loss: 2.8288 - accuracy: 0.3779 - val_loss: 2.9092 - val_accuracy: 0.2637
Epoch 9/100
2/2 [==============================] - 0s 33ms/step - loss: 2.8287 - accuracy: 0.3791 - val_loss: 2.9015 - val_accuracy: 0.2637
Epoch 10/100
2/2 [==============================] - 0s 37ms/step - loss: 2.8114 - accuracy: 0.4095 - val_loss: 2.8931 - val_accuracy: 0.2637
Epoch 11/100
2/2 [==============================] - 0s 32ms/step - loss: 2.7772 - accuracy: 0.4326 - val_loss: 2.8840 - val_accuracy: 0.2637
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 2.7963 - accuracy: 0.4119 - val_loss: 2.8741 - val_accuracy: 0.2637
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 2.7808 - accuracy: 0.4350 - val_loss: 2.8636 - val_accuracy: 0.2747
Epoch 14/100
2/2 [==============================] - 0s 46ms/step - loss: 2.7763 - accuracy: 0.4168 - val_loss: 2.8524 - val_accuracy: 0.3077
Epoch 15/100
2/2 [==============================] - 0s 42ms/step - loss: 2.7539 - accuracy: 0.4301 - val_loss: 2.8406 - val_accuracy: 0.3077
Epoch 16/100
2/2 [==============================] - 0s 31ms/step - loss: 2.7586 - accuracy: 0.4338 - val_loss: 2.8282 - val_accuracy: 0.2967
Epoch 17/100
2/2 [==============================] - 0s 35ms/step - loss: 2.7459 - accuracy: 0.4411 - val_loss: 2.8153 - val_accuracy: 0.2967
Epoch 18/100
2/2 [==============================] - 0s 38ms/step - loss: 2.7315 - accuracy: 0.4338 - val_loss: 2.8018 - val_accuracy: 0.2967
Epoch 19/100
2/2 [==============================] - 0s 49ms/step - loss: 2.7049 - accuracy: 0.4605 - val_loss: 2.7877 - val_accuracy: 0.3077
Epoch 20/100
2/2 [==============================] - 0s 47ms/step - loss: 2.6983 - accuracy: 0.4739 - val_loss: 2.7732 - val_accuracy: 0.3077
Epoch 21/100
2/2 [==============================] - 0s 32ms/step - loss: 2.6889 - accuracy: 0.4714 - val_loss: 2.7583 - val_accuracy: 0.3297
Epoch 22/100
2/2 [==============================] - 0s 37ms/step - loss: 2.6634 - accuracy: 0.4812 - val_loss: 2.7429 - val_accuracy: 0.3297
Epoch 23/100
2/2 [==============================] - 0s 49ms/step - loss: 2.6609 - accuracy: 0.4787 - val_loss: 2.7272 - val_accuracy: 0.3297
Epoch 24/100
2/2 [==============================] - 0s 49ms/step - loss: 2.6331 - accuracy: 0.5018 - val_loss: 2.7110 - val_accuracy: 0.3297
Epoch 25/100
2/2 [==============================] - 0s 49ms/step - loss: 2.6169 - accuracy: 0.5152 - val_loss: 2.6945 - val_accuracy: 0.3626
Epoch 26/100
2/2 [==============================] - 0s 42ms/step - loss: 2.6396 - accuracy: 0.5067 - val_loss: 2.6777 - val_accuracy: 0.3956
Epoch 27/100
2/2 [==============================] - 0s 32ms/step - loss: 2.5948 - accuracy: 0.5188 - val_loss: 2.6606 - val_accuracy: 0.4066
Epoch 28/100
2/2 [==============================] - 0s 51ms/step - loss: 2.6053 - accuracy: 0.5286 - val_loss: 2.6431 - val_accuracy: 0.4505
Epoch 29/100
2/2 [==============================] - 0s 40ms/step - loss: 2.5780 - accuracy: 0.5261 - val_loss: 2.6255 - val_accuracy: 0.4505
Epoch 30/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5456 - accuracy: 0.5541 - val_loss: 2.6076 - val_accuracy: 0.4725
Epoch 31/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5510 - accuracy: 0.5492 - val_loss: 2.5895 - val_accuracy: 0.4945
Epoch 32/100
2/2 [==============================] - 0s 50ms/step - loss: 2.5328 - accuracy: 0.5553 - val_loss: 2.5711 - val_accuracy: 0.5165
Epoch 33/100
2/2 [==============================] - 0s 48ms/step - loss: 2.4890 - accuracy: 0.5759 - val_loss: 2.5526 - val_accuracy: 0.5165
Epoch 34/100
2/2 [==============================] - 0s 35ms/step - loss: 2.5120 - accuracy: 0.5844 - val_loss: 2.5340 - val_accuracy: 0.5275
Epoch 35/100
2/2 [==============================] - 0s 37ms/step - loss: 2.4884 - accuracy: 0.5772 - val_loss: 2.5153 - val_accuracy: 0.5604
Epoch 36/100
2/2 [==============================] - 0s 36ms/step - loss: 2.4600 - accuracy: 0.5930 - val_loss: 2.4965 - val_accuracy: 0.5604
Epoch 37/100
2/2 [==============================] - 0s 48ms/step - loss: 2.4398 - accuracy: 0.5930 - val_loss: 2.4776 - val_accuracy: 0.5714
Epoch 38/100
2/2 [==============================] - 0s 51ms/step - loss: 2.4280 - accuracy: 0.6112 - val_loss: 2.4586 - val_accuracy: 0.5714
Epoch 39/100
2/2 [==============================] - 0s 34ms/step - loss: 2.4249 - accuracy: 0.6148 - val_loss: 2.4397 - val_accuracy: 0.5824
Epoch 40/100
2/2 [==============================] - 0s 42ms/step - loss: 2.4087 - accuracy: 0.6173 - val_loss: 2.4206 - val_accuracy: 0.6044
Epoch 41/100
2/2 [==============================] - 0s 37ms/step - loss: 2.3853 - accuracy: 0.6282 - val_loss: 2.4016 - val_accuracy: 0.6154
Epoch 42/100
2/2 [==============================] - 0s 48ms/step - loss: 2.3521 - accuracy: 0.6646 - val_loss: 2.3826 - val_accuracy: 0.6154
Epoch 43/100
2/2 [==============================] - 0s 33ms/step - loss: 2.3281 - accuracy: 0.6598 - val_loss: 2.3636 - val_accuracy: 0.6374
Epoch 44/100
2/2 [==============================] - 0s 32ms/step - loss: 2.3381 - accuracy: 0.6610 - val_loss: 2.3447 - val_accuracy: 0.6484
Epoch 45/100
2/2 [==============================] - 0s 35ms/step - loss: 2.3058 - accuracy: 0.6695 - val_loss: 2.3258 - val_accuracy: 0.6484
Epoch 46/100
2/2 [==============================] - 0s 49ms/step - loss: 2.3150 - accuracy: 0.6744 - val_loss: 2.3070 - val_accuracy: 0.6484
Epoch 47/100
2/2 [==============================] - 0s 29ms/step - loss: 2.2636 - accuracy: 0.6999 - val_loss: 2.2882 - val_accuracy: 0.6593
Epoch 48/100
2/2 [==============================] - 0s 34ms/step - loss: 2.2617 - accuracy: 0.6926 - val_loss: 2.2696 - val_accuracy: 0.6813
Epoch 49/100
2/2 [==============================] - 0s 49ms/step - loss: 2.2325 - accuracy: 0.7181 - val_loss: 2.2510 - val_accuracy: 0.7363
Epoch 50/100
2/2 [==============================] - 0s 30ms/step - loss: 2.2325 - accuracy: 0.7205 - val_loss: 2.2326 - val_accuracy: 0.7582
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 2.2236 - accuracy: 0.7132 - val_loss: 2.2143 - val_accuracy: 0.7473
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1886 - accuracy: 0.7327 - val_loss: 2.1961 - val_accuracy: 0.7692
Epoch 53/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1764 - accuracy: 0.7230 - val_loss: 2.1780 - val_accuracy: 0.7912
Epoch 54/100
2/2 [==============================] - 0s 48ms/step - loss: 2.1677 - accuracy: 0.7533 - val_loss: 2.1600 - val_accuracy: 0.8022
Epoch 55/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1524 - accuracy: 0.7546 - val_loss: 2.1421 - val_accuracy: 0.8022
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 2.1101 - accuracy: 0.7971 - val_loss: 2.1245 - val_accuracy: 0.8022
Epoch 57/100
2/2 [==============================] - 0s 50ms/step - loss: 2.1291 - accuracy: 0.7618 - val_loss: 2.1069 - val_accuracy: 0.8242
Epoch 58/100
2/2 [==============================] - 0s 45ms/step - loss: 2.0911 - accuracy: 0.7776 - val_loss: 2.0896 - val_accuracy: 0.8242
Epoch 59/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0889 - accuracy: 0.7837 - val_loss: 2.0725 - val_accuracy: 0.8352
Epoch 60/100
2/2 [==============================] - 0s 44ms/step - loss: 2.0499 - accuracy: 0.7934 - val_loss: 2.0555 - val_accuracy: 0.8462
Epoch 61/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0562 - accuracy: 0.7752 - val_loss: 2.0386 - val_accuracy: 0.8571
Epoch 62/100
2/2 [==============================] - 0s 50ms/step - loss: 2.0351 - accuracy: 0.7947 - val_loss: 2.0220 - val_accuracy: 0.8571
Epoch 63/100
2/2 [==============================] - 0s 31ms/step - loss: 2.0123 - accuracy: 0.8019 - val_loss: 2.0055 - val_accuracy: 0.8571
Epoch 64/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0181 - accuracy: 0.7959 - val_loss: 1.9892 - val_accuracy: 0.8791
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9884 - accuracy: 0.8080 - val_loss: 1.9730 - val_accuracy: 0.8791
Epoch 66/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9821 - accuracy: 0.7898 - val_loss: 1.9570 - val_accuracy: 0.8791
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9664 - accuracy: 0.8080 - val_loss: 1.9412 - val_accuracy: 0.8791
Epoch 68/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9529 - accuracy: 0.8214 - val_loss: 1.9256 - val_accuracy: 0.8791
Epoch 69/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9319 - accuracy: 0.8250 - val_loss: 1.9101 - val_accuracy: 0.8791
Epoch 70/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9113 - accuracy: 0.8262 - val_loss: 1.8948 - val_accuracy: 0.8791
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9103 - accuracy: 0.8275 - val_loss: 1.8797 - val_accuracy: 0.8791
Epoch 72/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8791 - accuracy: 0.8323 - val_loss: 1.8648 - val_accuracy: 0.8791
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8822 - accuracy: 0.8396 - val_loss: 1.8500 - val_accuracy: 0.8791
Epoch 74/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8718 - accuracy: 0.8226 - val_loss: 1.8354 - val_accuracy: 0.8791
Epoch 75/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8624 - accuracy: 0.8202 - val_loss: 1.8210 - val_accuracy: 0.8791
Epoch 76/100
2/2 [==============================] - 0s 48ms/step - loss: 1.8263 - accuracy: 0.8457 - val_loss: 1.8067 - val_accuracy: 0.8791
Epoch 77/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8327 - accuracy: 0.8250 - val_loss: 1.7926 - val_accuracy: 0.8791
Epoch 78/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8325 - accuracy: 0.8250 - val_loss: 1.7787 - val_accuracy: 0.8791
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8089 - accuracy: 0.8323 - val_loss: 1.7650 - val_accuracy: 0.8791
Epoch 80/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7977 - accuracy: 0.8335 - val_loss: 1.7514 - val_accuracy: 0.8791
Epoch 81/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7865 - accuracy: 0.8335 - val_loss: 1.7380 - val_accuracy: 0.8791
Epoch 82/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7795 - accuracy: 0.8311 - val_loss: 1.7247 - val_accuracy: 0.8791
Epoch 83/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7658 - accuracy: 0.8275 - val_loss: 1.7116 - val_accuracy: 0.8791
Epoch 84/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7166 - accuracy: 0.8420 - val_loss: 1.6986 - val_accuracy: 0.8791
Epoch 85/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7326 - accuracy: 0.8287 - val_loss: 1.6858 - val_accuracy: 0.8791
Epoch 86/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7220 - accuracy: 0.8335 - val_loss: 1.6731 - val_accuracy: 0.8901
Epoch 87/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7031 - accuracy: 0.8420 - val_loss: 1.6605 - val_accuracy: 0.8791
Epoch 88/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7152 - accuracy: 0.8372 - val_loss: 1.6482 - val_accuracy: 0.8791
Epoch 89/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6737 - accuracy: 0.8360 - val_loss: 1.6359 - val_accuracy: 0.8901
Epoch 90/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6745 - accuracy: 0.8408 - val_loss: 1.6238 - val_accuracy: 0.8901
Epoch 91/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6666 - accuracy: 0.8372 - val_loss: 1.6119 - val_accuracy: 0.8901
Epoch 92/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6422 - accuracy: 0.8554 - val_loss: 1.6000 - val_accuracy: 0.8901
Epoch 93/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6215 - accuracy: 0.8433 - val_loss: 1.5883 - val_accuracy: 0.8901
Epoch 94/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6183 - accuracy: 0.8420 - val_loss: 1.5767 - val_accuracy: 0.8901
Epoch 95/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6124 - accuracy: 0.8372 - val_loss: 1.5652 - val_accuracy: 0.8901
Epoch 96/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5903 - accuracy: 0.8408 - val_loss: 1.5538 - val_accuracy: 0.8901
Epoch 97/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5926 - accuracy: 0.8469 - val_loss: 1.5425 - val_accuracy: 0.8901
Epoch 98/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5771 - accuracy: 0.8469 - val_loss: 1.5314 - val_accuracy: 0.8901
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5828 - accuracy: 0.8408 - val_loss: 1.5204 - val_accuracy: 0.8901
Epoch 100/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5580 - accuracy: 0.8481 - val_loss: 1.5094 - val_accuracy: 0.8901
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 237ms/step - loss: 3.1996 - accuracy: 0.1531 - val_loss: 3.1158 - val_accuracy: 0.1319
Epoch 2/100
2/2 [==============================] - 0s 33ms/step - loss: 3.2319 - accuracy: 0.1470 - val_loss: 3.1137 - val_accuracy: 0.1319
Epoch 3/100
2/2 [==============================] - 0s 52ms/step - loss: 3.1791 - accuracy: 0.1628 - val_loss: 3.1105 - val_accuracy: 0.1319
Epoch 4/100
2/2 [==============================] - 0s 43ms/step - loss: 3.2128 - accuracy: 0.1519 - val_loss: 3.1061 - val_accuracy: 0.1319
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 3.1877 - accuracy: 0.1628 - val_loss: 3.1007 - val_accuracy: 0.1319
Epoch 6/100
2/2 [==============================] - 0s 35ms/step - loss: 3.1929 - accuracy: 0.1592 - val_loss: 3.0942 - val_accuracy: 0.1319
Epoch 7/100
2/2 [==============================] - 0s 42ms/step - loss: 3.1929 - accuracy: 0.1519 - val_loss: 3.0866 - val_accuracy: 0.1429
Epoch 8/100
2/2 [==============================] - 0s 37ms/step - loss: 3.1810 - accuracy: 0.1555 - val_loss: 3.0781 - val_accuracy: 0.1429
Epoch 9/100
2/2 [==============================] - 0s 45ms/step - loss: 3.1547 - accuracy: 0.1665 - val_loss: 3.0686 - val_accuracy: 0.1429
Epoch 10/100
2/2 [==============================] - 0s 33ms/step - loss: 3.1717 - accuracy: 0.1640 - val_loss: 3.0581 - val_accuracy: 0.1429
Epoch 11/100
2/2 [==============================] - 0s 34ms/step - loss: 3.1470 - accuracy: 0.1701 - val_loss: 3.0467 - val_accuracy: 0.1538
Epoch 12/100
2/2 [==============================] - 0s 35ms/step - loss: 3.1236 - accuracy: 0.1689 - val_loss: 3.0345 - val_accuracy: 0.1429
Epoch 13/100
2/2 [==============================] - 0s 34ms/step - loss: 3.1314 - accuracy: 0.1774 - val_loss: 3.0215 - val_accuracy: 0.1429
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 3.1069 - accuracy: 0.1713 - val_loss: 3.0076 - val_accuracy: 0.1429
Epoch 15/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1104 - accuracy: 0.1689 - val_loss: 2.9930 - val_accuracy: 0.1538
Epoch 16/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0849 - accuracy: 0.1786 - val_loss: 2.9777 - val_accuracy: 0.1758
Epoch 17/100
2/2 [==============================] - 0s 34ms/step - loss: 3.0524 - accuracy: 0.1871 - val_loss: 2.9617 - val_accuracy: 0.1868
Epoch 18/100
2/2 [==============================] - 0s 36ms/step - loss: 3.0584 - accuracy: 0.2017 - val_loss: 2.9451 - val_accuracy: 0.1868
Epoch 19/100
2/2 [==============================] - 0s 46ms/step - loss: 3.0404 - accuracy: 0.1859 - val_loss: 2.9278 - val_accuracy: 0.1868
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 3.0136 - accuracy: 0.2041 - val_loss: 2.9100 - val_accuracy: 0.1978
Epoch 21/100
2/2 [==============================] - 0s 31ms/step - loss: 2.9764 - accuracy: 0.1981 - val_loss: 2.8916 - val_accuracy: 0.2198
Epoch 22/100
2/2 [==============================] - 0s 37ms/step - loss: 2.9617 - accuracy: 0.2175 - val_loss: 2.8728 - val_accuracy: 0.2198
Epoch 23/100
2/2 [==============================] - 0s 46ms/step - loss: 2.9769 - accuracy: 0.1920 - val_loss: 2.8535 - val_accuracy: 0.2308
Epoch 24/100
2/2 [==============================] - 0s 37ms/step - loss: 2.9392 - accuracy: 0.2114 - val_loss: 2.8338 - val_accuracy: 0.2308
Epoch 25/100
2/2 [==============================] - 0s 34ms/step - loss: 2.9038 - accuracy: 0.2187 - val_loss: 2.8137 - val_accuracy: 0.2418
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 2.8901 - accuracy: 0.2345 - val_loss: 2.7933 - val_accuracy: 0.2418
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8740 - accuracy: 0.2321 - val_loss: 2.7725 - val_accuracy: 0.2418
Epoch 28/100
2/2 [==============================] - 0s 38ms/step - loss: 2.8365 - accuracy: 0.2564 - val_loss: 2.7515 - val_accuracy: 0.2418
Epoch 29/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8285 - accuracy: 0.2685 - val_loss: 2.7301 - val_accuracy: 0.2418
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 2.8056 - accuracy: 0.2734 - val_loss: 2.7086 - val_accuracy: 0.2637
Epoch 31/100
2/2 [==============================] - 0s 34ms/step - loss: 2.7948 - accuracy: 0.2612 - val_loss: 2.6869 - val_accuracy: 0.2637
Epoch 32/100
2/2 [==============================] - 0s 49ms/step - loss: 2.7542 - accuracy: 0.3013 - val_loss: 2.6651 - val_accuracy: 0.2857
Epoch 33/100
2/2 [==============================] - 0s 38ms/step - loss: 2.7385 - accuracy: 0.3062 - val_loss: 2.6430 - val_accuracy: 0.2967
Epoch 34/100
2/2 [==============================] - 0s 34ms/step - loss: 2.7251 - accuracy: 0.3013 - val_loss: 2.6209 - val_accuracy: 0.3187
Epoch 35/100
2/2 [==============================] - 0s 49ms/step - loss: 2.6835 - accuracy: 0.3305 - val_loss: 2.5986 - val_accuracy: 0.3297
Epoch 36/100
2/2 [==============================] - 0s 41ms/step - loss: 2.6711 - accuracy: 0.3293 - val_loss: 2.5764 - val_accuracy: 0.3626
Epoch 37/100
2/2 [==============================] - 0s 36ms/step - loss: 2.6506 - accuracy: 0.3426 - val_loss: 2.5540 - val_accuracy: 0.3626
Epoch 38/100
2/2 [==============================] - 0s 71ms/step - loss: 2.6255 - accuracy: 0.3524 - val_loss: 2.5317 - val_accuracy: 0.3736
Epoch 39/100
2/2 [==============================] - 0s 43ms/step - loss: 2.5803 - accuracy: 0.3767 - val_loss: 2.5094 - val_accuracy: 0.4066
Epoch 40/100
2/2 [==============================] - 0s 33ms/step - loss: 2.5586 - accuracy: 0.4119 - val_loss: 2.4872 - val_accuracy: 0.4396
Epoch 41/100
2/2 [==============================] - 0s 48ms/step - loss: 2.5515 - accuracy: 0.3913 - val_loss: 2.4650 - val_accuracy: 0.4505
Epoch 42/100
2/2 [==============================] - 0s 34ms/step - loss: 2.5190 - accuracy: 0.4216 - val_loss: 2.4428 - val_accuracy: 0.4505
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 2.4833 - accuracy: 0.4350 - val_loss: 2.4208 - val_accuracy: 0.4835
Epoch 44/100
2/2 [==============================] - 0s 54ms/step - loss: 2.4900 - accuracy: 0.4313 - val_loss: 2.3989 - val_accuracy: 0.5055
Epoch 45/100
2/2 [==============================] - 0s 44ms/step - loss: 2.4396 - accuracy: 0.4739 - val_loss: 2.3772 - val_accuracy: 0.5495
Epoch 46/100
2/2 [==============================] - 0s 40ms/step - loss: 2.4140 - accuracy: 0.5043 - val_loss: 2.3555 - val_accuracy: 0.5824
Epoch 47/100
2/2 [==============================] - 0s 34ms/step - loss: 2.4066 - accuracy: 0.4945 - val_loss: 2.3341 - val_accuracy: 0.6044
Epoch 48/100
2/2 [==============================] - 0s 40ms/step - loss: 2.3725 - accuracy: 0.5067 - val_loss: 2.3129 - val_accuracy: 0.6264
Epoch 49/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3600 - accuracy: 0.5176 - val_loss: 2.2918 - val_accuracy: 0.6374
Epoch 50/100
2/2 [==============================] - 0s 46ms/step - loss: 2.3475 - accuracy: 0.5322 - val_loss: 2.2709 - val_accuracy: 0.6374
Epoch 51/100
2/2 [==============================] - 0s 36ms/step - loss: 2.3311 - accuracy: 0.5286 - val_loss: 2.2503 - val_accuracy: 0.6484
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 2.3044 - accuracy: 0.5553 - val_loss: 2.2298 - val_accuracy: 0.6703
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2841 - accuracy: 0.5990 - val_loss: 2.2096 - val_accuracy: 0.6703
Epoch 54/100
2/2 [==============================] - 0s 47ms/step - loss: 2.2451 - accuracy: 0.6075 - val_loss: 2.1896 - val_accuracy: 0.7033
Epoch 55/100
2/2 [==============================] - 0s 43ms/step - loss: 2.2171 - accuracy: 0.6403 - val_loss: 2.1699 - val_accuracy: 0.7363
Epoch 56/100
2/2 [==============================] - 0s 40ms/step - loss: 2.2116 - accuracy: 0.6476 - val_loss: 2.1504 - val_accuracy: 0.7692
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1940 - accuracy: 0.6391 - val_loss: 2.1312 - val_accuracy: 0.7692
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1641 - accuracy: 0.6731 - val_loss: 2.1123 - val_accuracy: 0.7692
Epoch 59/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1576 - accuracy: 0.6731 - val_loss: 2.0935 - val_accuracy: 0.7802
Epoch 60/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1401 - accuracy: 0.6853 - val_loss: 2.0751 - val_accuracy: 0.8022
Epoch 61/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1222 - accuracy: 0.7023 - val_loss: 2.0569 - val_accuracy: 0.8022
Epoch 62/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0931 - accuracy: 0.7290 - val_loss: 2.0389 - val_accuracy: 0.8022
Epoch 63/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0622 - accuracy: 0.7436 - val_loss: 2.0212 - val_accuracy: 0.8132
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0380 - accuracy: 0.7570 - val_loss: 2.0038 - val_accuracy: 0.8022
Epoch 65/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0551 - accuracy: 0.7412 - val_loss: 1.9866 - val_accuracy: 0.8242
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 2.0378 - accuracy: 0.7618 - val_loss: 1.9696 - val_accuracy: 0.8352
Epoch 67/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9836 - accuracy: 0.7728 - val_loss: 1.9529 - val_accuracy: 0.8352
Epoch 68/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9865 - accuracy: 0.7874 - val_loss: 1.9364 - val_accuracy: 0.8242
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9536 - accuracy: 0.8044 - val_loss: 1.9202 - val_accuracy: 0.8242
Epoch 70/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9550 - accuracy: 0.8080 - val_loss: 1.9042 - val_accuracy: 0.8242
Epoch 71/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9298 - accuracy: 0.8141 - val_loss: 1.8884 - val_accuracy: 0.8242
Epoch 72/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9151 - accuracy: 0.8007 - val_loss: 1.8729 - val_accuracy: 0.8242
Epoch 73/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8956 - accuracy: 0.8238 - val_loss: 1.8576 - val_accuracy: 0.8242
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8875 - accuracy: 0.8262 - val_loss: 1.8426 - val_accuracy: 0.8242
Epoch 75/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8659 - accuracy: 0.8238 - val_loss: 1.8278 - val_accuracy: 0.8242
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8412 - accuracy: 0.8311 - val_loss: 1.8132 - val_accuracy: 0.8242
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8320 - accuracy: 0.8384 - val_loss: 1.7988 - val_accuracy: 0.8352
Epoch 78/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8220 - accuracy: 0.8408 - val_loss: 1.7846 - val_accuracy: 0.8352
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8104 - accuracy: 0.8323 - val_loss: 1.7706 - val_accuracy: 0.8352
Epoch 80/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7826 - accuracy: 0.8445 - val_loss: 1.7569 - val_accuracy: 0.8352
Epoch 81/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7666 - accuracy: 0.8420 - val_loss: 1.7433 - val_accuracy: 0.8352
Epoch 82/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7517 - accuracy: 0.8457 - val_loss: 1.7299 - val_accuracy: 0.8352
Epoch 83/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7478 - accuracy: 0.8433 - val_loss: 1.7168 - val_accuracy: 0.8352
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7305 - accuracy: 0.8445 - val_loss: 1.7038 - val_accuracy: 0.8352
Epoch 85/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7191 - accuracy: 0.8445 - val_loss: 1.6910 - val_accuracy: 0.8352
Epoch 86/100
2/2 [==============================] - 0s 50ms/step - loss: 1.7012 - accuracy: 0.8420 - val_loss: 1.6784 - val_accuracy: 0.8352
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6853 - accuracy: 0.8493 - val_loss: 1.6659 - val_accuracy: 0.8352
Epoch 88/100
2/2 [==============================] - 0s 49ms/step - loss: 1.6662 - accuracy: 0.8469 - val_loss: 1.6536 - val_accuracy: 0.8352
Epoch 89/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6709 - accuracy: 0.8457 - val_loss: 1.6415 - val_accuracy: 0.8352
Epoch 90/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6611 - accuracy: 0.8530 - val_loss: 1.6296 - val_accuracy: 0.8352
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6426 - accuracy: 0.8481 - val_loss: 1.6177 - val_accuracy: 0.8352
Epoch 92/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6214 - accuracy: 0.8530 - val_loss: 1.6061 - val_accuracy: 0.8352
Epoch 93/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6132 - accuracy: 0.8505 - val_loss: 1.5946 - val_accuracy: 0.8352
Epoch 94/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6169 - accuracy: 0.8469 - val_loss: 1.5832 - val_accuracy: 0.8352
Epoch 95/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5910 - accuracy: 0.8530 - val_loss: 1.5720 - val_accuracy: 0.8352
Epoch 96/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5779 - accuracy: 0.8518 - val_loss: 1.5610 - val_accuracy: 0.8352
Epoch 97/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5644 - accuracy: 0.8505 - val_loss: 1.5500 - val_accuracy: 0.8352
Epoch 98/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5541 - accuracy: 0.8505 - val_loss: 1.5392 - val_accuracy: 0.8352
Epoch 99/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5447 - accuracy: 0.8505 - val_loss: 1.5286 - val_accuracy: 0.8352
Epoch 100/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5363 - accuracy: 0.8481 - val_loss: 1.5180 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Experiment number: 6
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 255ms/step - loss: 5.8661 - accuracy: 0.2445 - val_loss: 5.2138 - val_accuracy: 0.4891
Epoch 2/100
2/2 [==============================] - 0s 37ms/step - loss: 5.8595 - accuracy: 0.2445 - val_loss: 5.2164 - val_accuracy: 0.4674
Epoch 3/100
2/2 [==============================] - 0s 33ms/step - loss: 5.8660 - accuracy: 0.2397 - val_loss: 5.2182 - val_accuracy: 0.4674
Epoch 4/100
2/2 [==============================] - 0s 43ms/step - loss: 5.8450 - accuracy: 0.2409 - val_loss: 5.2195 - val_accuracy: 0.4565
Epoch 5/100
2/2 [==============================] - 0s 39ms/step - loss: 5.8336 - accuracy: 0.2372 - val_loss: 5.2201 - val_accuracy: 0.4457
Epoch 6/100
2/2 [==============================] - 0s 38ms/step - loss: 5.8450 - accuracy: 0.2421 - val_loss: 5.2203 - val_accuracy: 0.4348
Epoch 7/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8280 - accuracy: 0.2397 - val_loss: 5.2202 - val_accuracy: 0.4348
Epoch 8/100
2/2 [==============================] - 0s 39ms/step - loss: 5.8111 - accuracy: 0.2543 - val_loss: 5.2198 - val_accuracy: 0.4348
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8316 - accuracy: 0.2384 - val_loss: 5.2192 - val_accuracy: 0.4239
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 5.8176 - accuracy: 0.2433 - val_loss: 5.2184 - val_accuracy: 0.4239
Epoch 11/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7894 - accuracy: 0.2457 - val_loss: 5.2175 - val_accuracy: 0.4022
Epoch 12/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7939 - accuracy: 0.2457 - val_loss: 5.2164 - val_accuracy: 0.3804
Epoch 13/100
2/2 [==============================] - 0s 39ms/step - loss: 5.8004 - accuracy: 0.2397 - val_loss: 5.2153 - val_accuracy: 0.3804
Epoch 14/100
2/2 [==============================] - 0s 42ms/step - loss: 5.7905 - accuracy: 0.2397 - val_loss: 5.2141 - val_accuracy: 0.3804
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7705 - accuracy: 0.2579 - val_loss: 5.2128 - val_accuracy: 0.3696
Epoch 16/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7786 - accuracy: 0.2433 - val_loss: 5.2115 - val_accuracy: 0.3696
Epoch 17/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7798 - accuracy: 0.2445 - val_loss: 5.2101 - val_accuracy: 0.3696
Epoch 18/100
2/2 [==============================] - 0s 37ms/step - loss: 5.7418 - accuracy: 0.2530 - val_loss: 5.2087 - val_accuracy: 0.3696
Epoch 19/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7621 - accuracy: 0.2299 - val_loss: 5.2070 - val_accuracy: 0.3696
Epoch 20/100
2/2 [==============================] - 0s 41ms/step - loss: 5.7222 - accuracy: 0.2336 - val_loss: 5.2054 - val_accuracy: 0.3587
Epoch 21/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7376 - accuracy: 0.2567 - val_loss: 5.2038 - val_accuracy: 0.3587
Epoch 22/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7220 - accuracy: 0.2433 - val_loss: 5.2021 - val_accuracy: 0.3587
Epoch 23/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7308 - accuracy: 0.2689 - val_loss: 5.2005 - val_accuracy: 0.3587
Epoch 24/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7179 - accuracy: 0.2518 - val_loss: 5.1987 - val_accuracy: 0.3587
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7033 - accuracy: 0.2457 - val_loss: 5.1969 - val_accuracy: 0.3587
Epoch 26/100
2/2 [==============================] - 0s 40ms/step - loss: 5.6808 - accuracy: 0.2518 - val_loss: 5.1951 - val_accuracy: 0.3587
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6752 - accuracy: 0.2616 - val_loss: 5.1933 - val_accuracy: 0.3478
Epoch 28/100
2/2 [==============================] - 0s 43ms/step - loss: 5.6657 - accuracy: 0.2543 - val_loss: 5.1915 - val_accuracy: 0.3478
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6590 - accuracy: 0.2616 - val_loss: 5.1896 - val_accuracy: 0.3478
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 5.6287 - accuracy: 0.2616 - val_loss: 5.1878 - val_accuracy: 0.3478
Epoch 31/100
2/2 [==============================] - 0s 48ms/step - loss: 5.6681 - accuracy: 0.2384 - val_loss: 5.1859 - val_accuracy: 0.3478
Epoch 32/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6560 - accuracy: 0.2616 - val_loss: 5.1839 - val_accuracy: 0.3478
Epoch 33/100
2/2 [==============================] - 0s 39ms/step - loss: 5.6428 - accuracy: 0.2555 - val_loss: 5.1818 - val_accuracy: 0.3370
Epoch 34/100
2/2 [==============================] - 0s 40ms/step - loss: 5.6318 - accuracy: 0.2567 - val_loss: 5.1798 - val_accuracy: 0.3370
Epoch 35/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6158 - accuracy: 0.2640 - val_loss: 5.1777 - val_accuracy: 0.3370
Epoch 36/100
2/2 [==============================] - 0s 40ms/step - loss: 5.6156 - accuracy: 0.2640 - val_loss: 5.1756 - val_accuracy: 0.3370
Epoch 37/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5620 - accuracy: 0.2725 - val_loss: 5.1735 - val_accuracy: 0.3370
Epoch 38/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5651 - accuracy: 0.2652 - val_loss: 5.1713 - val_accuracy: 0.3370
Epoch 39/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5782 - accuracy: 0.2689 - val_loss: 5.1690 - val_accuracy: 0.3370
Epoch 40/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5541 - accuracy: 0.2689 - val_loss: 5.1667 - val_accuracy: 0.3370
Epoch 41/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5862 - accuracy: 0.2433 - val_loss: 5.1644 - val_accuracy: 0.3370
Epoch 42/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5550 - accuracy: 0.2640 - val_loss: 5.1620 - val_accuracy: 0.3370
Epoch 43/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5628 - accuracy: 0.2628 - val_loss: 5.1597 - val_accuracy: 0.3370
Epoch 44/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5375 - accuracy: 0.2652 - val_loss: 5.1574 - val_accuracy: 0.3370
Epoch 45/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5012 - accuracy: 0.2664 - val_loss: 5.1549 - val_accuracy: 0.3370
Epoch 46/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5350 - accuracy: 0.2591 - val_loss: 5.1525 - val_accuracy: 0.3370
Epoch 47/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5150 - accuracy: 0.2701 - val_loss: 5.1499 - val_accuracy: 0.3370
Epoch 48/100
2/2 [==============================] - 0s 40ms/step - loss: 5.5051 - accuracy: 0.2506 - val_loss: 5.1474 - val_accuracy: 0.3370
Epoch 49/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4874 - accuracy: 0.2603 - val_loss: 5.1448 - val_accuracy: 0.3370
Epoch 50/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4901 - accuracy: 0.2713 - val_loss: 5.1422 - val_accuracy: 0.3370
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4726 - accuracy: 0.2871 - val_loss: 5.1395 - val_accuracy: 0.3370
Epoch 52/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4855 - accuracy: 0.2737 - val_loss: 5.1369 - val_accuracy: 0.3370
Epoch 53/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4764 - accuracy: 0.2835 - val_loss: 5.1344 - val_accuracy: 0.3370
Epoch 54/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4553 - accuracy: 0.2701 - val_loss: 5.1315 - val_accuracy: 0.3370
Epoch 55/100
2/2 [==============================] - 0s 44ms/step - loss: 5.4420 - accuracy: 0.2810 - val_loss: 5.1287 - val_accuracy: 0.3370
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4296 - accuracy: 0.2774 - val_loss: 5.1260 - val_accuracy: 0.3370
Epoch 57/100
2/2 [==============================] - 0s 42ms/step - loss: 5.4062 - accuracy: 0.2859 - val_loss: 5.1232 - val_accuracy: 0.3370
Epoch 58/100
2/2 [==============================] - 0s 42ms/step - loss: 5.4128 - accuracy: 0.2689 - val_loss: 5.1205 - val_accuracy: 0.3370
Epoch 59/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4318 - accuracy: 0.2786 - val_loss: 5.1176 - val_accuracy: 0.3370
Epoch 60/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3897 - accuracy: 0.2981 - val_loss: 5.1146 - val_accuracy: 0.3370
Epoch 61/100
2/2 [==============================] - 0s 40ms/step - loss: 5.4150 - accuracy: 0.2676 - val_loss: 5.1117 - val_accuracy: 0.3370
Epoch 62/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4045 - accuracy: 0.2762 - val_loss: 5.1087 - val_accuracy: 0.3370
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3660 - accuracy: 0.2908 - val_loss: 5.1057 - val_accuracy: 0.3370
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 5.3817 - accuracy: 0.2713 - val_loss: 5.1025 - val_accuracy: 0.3370
Epoch 65/100
2/2 [==============================] - 0s 47ms/step - loss: 5.3768 - accuracy: 0.2883 - val_loss: 5.0993 - val_accuracy: 0.3370
Epoch 66/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3471 - accuracy: 0.2944 - val_loss: 5.0962 - val_accuracy: 0.3370
Epoch 67/100
2/2 [==============================] - 0s 30ms/step - loss: 5.3545 - accuracy: 0.2822 - val_loss: 5.0931 - val_accuracy: 0.3370
Epoch 68/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3505 - accuracy: 0.2920 - val_loss: 5.0898 - val_accuracy: 0.3370
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3419 - accuracy: 0.2822 - val_loss: 5.0865 - val_accuracy: 0.3370
Epoch 70/100
2/2 [==============================] - 0s 54ms/step - loss: 5.3100 - accuracy: 0.2920 - val_loss: 5.0832 - val_accuracy: 0.3370
Epoch 71/100
2/2 [==============================] - 0s 40ms/step - loss: 5.3018 - accuracy: 0.2944 - val_loss: 5.0798 - val_accuracy: 0.3370
Epoch 72/100
2/2 [==============================] - 0s 36ms/step - loss: 5.3212 - accuracy: 0.2920 - val_loss: 5.0763 - val_accuracy: 0.3370
Epoch 73/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3032 - accuracy: 0.2968 - val_loss: 5.0729 - val_accuracy: 0.3370
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 5.2999 - accuracy: 0.2981 - val_loss: 5.0695 - val_accuracy: 0.3370
Epoch 75/100
2/2 [==============================] - 0s 36ms/step - loss: 5.2602 - accuracy: 0.2956 - val_loss: 5.0661 - val_accuracy: 0.3370
Epoch 76/100
2/2 [==============================] - 0s 40ms/step - loss: 5.2865 - accuracy: 0.3017 - val_loss: 5.0626 - val_accuracy: 0.3370
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 5.3252 - accuracy: 0.2847 - val_loss: 5.0590 - val_accuracy: 0.3370
Epoch 78/100
2/2 [==============================] - 0s 36ms/step - loss: 5.2609 - accuracy: 0.2847 - val_loss: 5.0555 - val_accuracy: 0.3370
Epoch 79/100
2/2 [==============================] - 0s 40ms/step - loss: 5.2415 - accuracy: 0.2993 - val_loss: 5.0520 - val_accuracy: 0.3370
Epoch 80/100
2/2 [==============================] - 0s 41ms/step - loss: 5.2952 - accuracy: 0.2883 - val_loss: 5.0484 - val_accuracy: 0.3370
Epoch 81/100
2/2 [==============================] - 0s 36ms/step - loss: 5.2493 - accuracy: 0.2932 - val_loss: 5.0447 - val_accuracy: 0.3370
Epoch 82/100
2/2 [==============================] - 0s 39ms/step - loss: 5.2228 - accuracy: 0.3078 - val_loss: 5.0410 - val_accuracy: 0.3370
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 5.1964 - accuracy: 0.3102 - val_loss: 5.0372 - val_accuracy: 0.3370
Epoch 84/100
2/2 [==============================] - 0s 37ms/step - loss: 5.2125 - accuracy: 0.3066 - val_loss: 5.0334 - val_accuracy: 0.3370
Epoch 85/100
2/2 [==============================] - 0s 36ms/step - loss: 5.2050 - accuracy: 0.2932 - val_loss: 5.0297 - val_accuracy: 0.3370
Epoch 86/100
2/2 [==============================] - 0s 29ms/step - loss: 5.2067 - accuracy: 0.2895 - val_loss: 5.0258 - val_accuracy: 0.3370
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 5.2209 - accuracy: 0.3066 - val_loss: 5.0220 - val_accuracy: 0.3261
Epoch 88/100
2/2 [==============================] - 0s 48ms/step - loss: 5.1645 - accuracy: 0.2956 - val_loss: 5.0181 - val_accuracy: 0.3261
Epoch 89/100
2/2 [==============================] - 0s 51ms/step - loss: 5.1822 - accuracy: 0.2993 - val_loss: 5.0142 - val_accuracy: 0.3261
Epoch 90/100
2/2 [==============================] - 0s 43ms/step - loss: 5.1530 - accuracy: 0.3029 - val_loss: 5.0103 - val_accuracy: 0.3261
Epoch 91/100
2/2 [==============================] - 0s 25ms/step - loss: 5.1459 - accuracy: 0.3102 - val_loss: 5.0064 - val_accuracy: 0.3261
Epoch 92/100
2/2 [==============================] - 0s 28ms/step - loss: 5.1523 - accuracy: 0.3139 - val_loss: 5.0023 - val_accuracy: 0.3261
Epoch 93/100
2/2 [==============================] - 0s 38ms/step - loss: 5.1670 - accuracy: 0.3151 - val_loss: 4.9983 - val_accuracy: 0.3261
Epoch 94/100
2/2 [==============================] - 0s 37ms/step - loss: 5.1608 - accuracy: 0.2786 - val_loss: 4.9942 - val_accuracy: 0.3261
Epoch 95/100
2/2 [==============================] - 0s 32ms/step - loss: 5.1298 - accuracy: 0.3090 - val_loss: 4.9901 - val_accuracy: 0.3261
Epoch 96/100
2/2 [==============================] - 0s 30ms/step - loss: 5.1186 - accuracy: 0.3248 - val_loss: 4.9861 - val_accuracy: 0.3261
Epoch 97/100
2/2 [==============================] - 0s 34ms/step - loss: 5.1562 - accuracy: 0.3187 - val_loss: 4.9820 - val_accuracy: 0.3261
Epoch 98/100
2/2 [==============================] - 0s 48ms/step - loss: 5.1274 - accuracy: 0.3163 - val_loss: 4.9778 - val_accuracy: 0.3261
Epoch 99/100
2/2 [==============================] - 0s 45ms/step - loss: 5.1215 - accuracy: 0.3236 - val_loss: 4.9737 - val_accuracy: 0.3261
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 5.1075 - accuracy: 0.3127 - val_loss: 4.9694 - val_accuracy: 0.3261
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 234ms/step - loss: 5.9552 - accuracy: 0.3650 - val_loss: 5.4981 - val_accuracy: 0.4130
Epoch 2/100
2/2 [==============================] - 0s 37ms/step - loss: 5.9185 - accuracy: 0.3869 - val_loss: 5.4970 - val_accuracy: 0.4130
Epoch 3/100
2/2 [==============================] - 0s 34ms/step - loss: 5.9057 - accuracy: 0.3504 - val_loss: 5.4950 - val_accuracy: 0.4130
Epoch 4/100
2/2 [==============================] - 0s 29ms/step - loss: 5.8818 - accuracy: 0.3759 - val_loss: 5.4925 - val_accuracy: 0.4130
Epoch 5/100
2/2 [==============================] - 0s 34ms/step - loss: 5.9329 - accuracy: 0.3601 - val_loss: 5.4894 - val_accuracy: 0.4130
Epoch 6/100
2/2 [==============================] - 0s 52ms/step - loss: 5.9019 - accuracy: 0.3540 - val_loss: 5.4859 - val_accuracy: 0.4130
Epoch 7/100
2/2 [==============================] - 0s 48ms/step - loss: 5.8834 - accuracy: 0.3637 - val_loss: 5.4820 - val_accuracy: 0.4130
Epoch 8/100
2/2 [==============================] - 0s 44ms/step - loss: 5.8960 - accuracy: 0.3735 - val_loss: 5.4779 - val_accuracy: 0.4130
Epoch 9/100
2/2 [==============================] - 0s 36ms/step - loss: 5.8906 - accuracy: 0.3710 - val_loss: 5.4734 - val_accuracy: 0.4130
Epoch 10/100
2/2 [==============================] - 0s 42ms/step - loss: 5.8739 - accuracy: 0.3735 - val_loss: 5.4690 - val_accuracy: 0.4130
Epoch 11/100
2/2 [==============================] - 0s 33ms/step - loss: 5.9133 - accuracy: 0.3564 - val_loss: 5.4643 - val_accuracy: 0.4130
Epoch 12/100
2/2 [==============================] - 0s 37ms/step - loss: 5.8929 - accuracy: 0.3759 - val_loss: 5.4594 - val_accuracy: 0.4130
Epoch 13/100
2/2 [==============================] - 0s 46ms/step - loss: 5.8404 - accuracy: 0.3954 - val_loss: 5.4545 - val_accuracy: 0.4239
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8363 - accuracy: 0.3832 - val_loss: 5.4494 - val_accuracy: 0.4239
Epoch 15/100
2/2 [==============================] - 0s 41ms/step - loss: 5.8422 - accuracy: 0.3747 - val_loss: 5.4445 - val_accuracy: 0.4239
Epoch 16/100
2/2 [==============================] - 0s 39ms/step - loss: 5.8615 - accuracy: 0.3710 - val_loss: 5.4396 - val_accuracy: 0.4348
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8268 - accuracy: 0.3759 - val_loss: 5.4344 - val_accuracy: 0.4348
Epoch 18/100
2/2 [==============================] - 0s 42ms/step - loss: 5.7889 - accuracy: 0.4002 - val_loss: 5.4293 - val_accuracy: 0.4348
Epoch 19/100
2/2 [==============================] - 0s 51ms/step - loss: 5.8571 - accuracy: 0.3783 - val_loss: 5.4241 - val_accuracy: 0.4348
Epoch 20/100
2/2 [==============================] - 0s 49ms/step - loss: 5.8205 - accuracy: 0.3808 - val_loss: 5.4189 - val_accuracy: 0.4348
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 5.7636 - accuracy: 0.3978 - val_loss: 5.4137 - val_accuracy: 0.4348
Epoch 22/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7959 - accuracy: 0.3796 - val_loss: 5.4084 - val_accuracy: 0.4348
Epoch 23/100
2/2 [==============================] - 0s 47ms/step - loss: 5.8011 - accuracy: 0.3747 - val_loss: 5.4030 - val_accuracy: 0.4348
Epoch 24/100
2/2 [==============================] - 0s 49ms/step - loss: 5.8042 - accuracy: 0.3783 - val_loss: 5.3978 - val_accuracy: 0.4565
Epoch 25/100
2/2 [==============================] - 0s 44ms/step - loss: 5.7543 - accuracy: 0.3820 - val_loss: 5.3927 - val_accuracy: 0.4565
Epoch 26/100
2/2 [==============================] - 0s 43ms/step - loss: 5.7806 - accuracy: 0.3808 - val_loss: 5.3874 - val_accuracy: 0.4674
Epoch 27/100
2/2 [==============================] - 0s 42ms/step - loss: 5.7647 - accuracy: 0.4161 - val_loss: 5.3821 - val_accuracy: 0.4674
Epoch 28/100
2/2 [==============================] - 0s 44ms/step - loss: 5.7989 - accuracy: 0.3710 - val_loss: 5.3767 - val_accuracy: 0.4674
Epoch 29/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7556 - accuracy: 0.3844 - val_loss: 5.3714 - val_accuracy: 0.4674
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7573 - accuracy: 0.3808 - val_loss: 5.3663 - val_accuracy: 0.4674
Epoch 31/100
2/2 [==============================] - 0s 32ms/step - loss: 5.7613 - accuracy: 0.3917 - val_loss: 5.3611 - val_accuracy: 0.4674
Epoch 32/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7412 - accuracy: 0.3893 - val_loss: 5.3558 - val_accuracy: 0.4674
Epoch 33/100
2/2 [==============================] - 0s 31ms/step - loss: 5.7383 - accuracy: 0.4027 - val_loss: 5.3506 - val_accuracy: 0.4674
Epoch 34/100
2/2 [==============================] - 0s 50ms/step - loss: 5.6996 - accuracy: 0.3917 - val_loss: 5.3454 - val_accuracy: 0.4674
Epoch 35/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6993 - accuracy: 0.3820 - val_loss: 5.3400 - val_accuracy: 0.4674
Epoch 36/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6930 - accuracy: 0.3844 - val_loss: 5.3347 - val_accuracy: 0.4674
Epoch 37/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6905 - accuracy: 0.3856 - val_loss: 5.3295 - val_accuracy: 0.4674
Epoch 38/100
2/2 [==============================] - 0s 37ms/step - loss: 5.7088 - accuracy: 0.3942 - val_loss: 5.3242 - val_accuracy: 0.4783
Epoch 39/100
2/2 [==============================] - 0s 48ms/step - loss: 5.6509 - accuracy: 0.3990 - val_loss: 5.3191 - val_accuracy: 0.4783
Epoch 40/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6896 - accuracy: 0.3929 - val_loss: 5.3139 - val_accuracy: 0.4783
Epoch 41/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6858 - accuracy: 0.3881 - val_loss: 5.3088 - val_accuracy: 0.4891
Epoch 42/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6585 - accuracy: 0.3893 - val_loss: 5.3037 - val_accuracy: 0.4891
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6769 - accuracy: 0.3929 - val_loss: 5.2986 - val_accuracy: 0.4891
Epoch 44/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6461 - accuracy: 0.4136 - val_loss: 5.2935 - val_accuracy: 0.4891
Epoch 45/100
2/2 [==============================] - 0s 51ms/step - loss: 5.6285 - accuracy: 0.3990 - val_loss: 5.2884 - val_accuracy: 0.5000
Epoch 46/100
2/2 [==============================] - 0s 49ms/step - loss: 5.6269 - accuracy: 0.4185 - val_loss: 5.2835 - val_accuracy: 0.5000
Epoch 47/100
2/2 [==============================] - 0s 40ms/step - loss: 5.6344 - accuracy: 0.4100 - val_loss: 5.2783 - val_accuracy: 0.5000
Epoch 48/100
2/2 [==============================] - 0s 47ms/step - loss: 5.6305 - accuracy: 0.3966 - val_loss: 5.2733 - val_accuracy: 0.5000
Epoch 49/100
2/2 [==============================] - 0s 33ms/step - loss: 5.5949 - accuracy: 0.4173 - val_loss: 5.2681 - val_accuracy: 0.5000
Epoch 50/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6089 - accuracy: 0.3978 - val_loss: 5.2631 - val_accuracy: 0.5000
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5696 - accuracy: 0.4173 - val_loss: 5.2578 - val_accuracy: 0.5000
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6199 - accuracy: 0.4063 - val_loss: 5.2525 - val_accuracy: 0.5109
Epoch 53/100
2/2 [==============================] - 0s 40ms/step - loss: 5.5937 - accuracy: 0.3966 - val_loss: 5.2474 - val_accuracy: 0.5109
Epoch 54/100
2/2 [==============================] - 0s 41ms/step - loss: 5.5760 - accuracy: 0.4136 - val_loss: 5.2423 - val_accuracy: 0.5109
Epoch 55/100
2/2 [==============================] - 0s 33ms/step - loss: 5.5350 - accuracy: 0.4221 - val_loss: 5.2372 - val_accuracy: 0.5109
Epoch 56/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5691 - accuracy: 0.4234 - val_loss: 5.2323 - val_accuracy: 0.5109
Epoch 57/100
2/2 [==============================] - 0s 41ms/step - loss: 5.5738 - accuracy: 0.4124 - val_loss: 5.2271 - val_accuracy: 0.5109
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5731 - accuracy: 0.4015 - val_loss: 5.2221 - val_accuracy: 0.5109
Epoch 59/100
2/2 [==============================] - 0s 32ms/step - loss: 5.5566 - accuracy: 0.4039 - val_loss: 5.2167 - val_accuracy: 0.5109
Epoch 60/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5367 - accuracy: 0.4221 - val_loss: 5.2115 - val_accuracy: 0.5109
Epoch 61/100
2/2 [==============================] - 0s 49ms/step - loss: 5.5268 - accuracy: 0.4161 - val_loss: 5.2063 - val_accuracy: 0.5109
Epoch 62/100
2/2 [==============================] - 0s 44ms/step - loss: 5.5411 - accuracy: 0.4221 - val_loss: 5.2012 - val_accuracy: 0.5109
Epoch 63/100
2/2 [==============================] - 0s 48ms/step - loss: 5.5562 - accuracy: 0.4161 - val_loss: 5.1960 - val_accuracy: 0.5109
Epoch 64/100
2/2 [==============================] - 0s 52ms/step - loss: 5.5013 - accuracy: 0.4136 - val_loss: 5.1908 - val_accuracy: 0.5109
Epoch 65/100
2/2 [==============================] - 0s 50ms/step - loss: 5.5040 - accuracy: 0.4282 - val_loss: 5.1856 - val_accuracy: 0.5109
Epoch 66/100
2/2 [==============================] - 0s 31ms/step - loss: 5.5323 - accuracy: 0.4148 - val_loss: 5.1803 - val_accuracy: 0.5109
Epoch 67/100
2/2 [==============================] - 0s 40ms/step - loss: 5.4879 - accuracy: 0.4416 - val_loss: 5.1752 - val_accuracy: 0.5109
Epoch 68/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4778 - accuracy: 0.4221 - val_loss: 5.1700 - val_accuracy: 0.5109
Epoch 69/100
2/2 [==============================] - 0s 44ms/step - loss: 5.5106 - accuracy: 0.4234 - val_loss: 5.1651 - val_accuracy: 0.5109
Epoch 70/100
2/2 [==============================] - 0s 51ms/step - loss: 5.4778 - accuracy: 0.4270 - val_loss: 5.1599 - val_accuracy: 0.5109
Epoch 71/100
2/2 [==============================] - 0s 47ms/step - loss: 5.4538 - accuracy: 0.4294 - val_loss: 5.1548 - val_accuracy: 0.5109
Epoch 72/100
2/2 [==============================] - 0s 29ms/step - loss: 5.4428 - accuracy: 0.4453 - val_loss: 5.1497 - val_accuracy: 0.5109
Epoch 73/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4593 - accuracy: 0.4319 - val_loss: 5.1444 - val_accuracy: 0.5109
Epoch 74/100
2/2 [==============================] - 0s 41ms/step - loss: 5.4436 - accuracy: 0.4392 - val_loss: 5.1394 - val_accuracy: 0.5109
Epoch 75/100
2/2 [==============================] - 0s 33ms/step - loss: 5.4399 - accuracy: 0.4343 - val_loss: 5.1342 - val_accuracy: 0.5109
Epoch 76/100
2/2 [==============================] - 0s 51ms/step - loss: 5.4509 - accuracy: 0.4282 - val_loss: 5.1291 - val_accuracy: 0.5109
Epoch 77/100
2/2 [==============================] - 0s 46ms/step - loss: 5.4199 - accuracy: 0.4404 - val_loss: 5.1239 - val_accuracy: 0.5217
Epoch 78/100
2/2 [==============================] - 0s 44ms/step - loss: 5.4262 - accuracy: 0.4380 - val_loss: 5.1187 - val_accuracy: 0.5217
Epoch 79/100
2/2 [==============================] - 0s 40ms/step - loss: 5.4033 - accuracy: 0.4416 - val_loss: 5.1135 - val_accuracy: 0.5217
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4479 - accuracy: 0.4428 - val_loss: 5.1085 - val_accuracy: 0.5217
Epoch 81/100
2/2 [==============================] - 0s 48ms/step - loss: 5.4252 - accuracy: 0.4319 - val_loss: 5.1034 - val_accuracy: 0.5217
Epoch 82/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4237 - accuracy: 0.4173 - val_loss: 5.0983 - val_accuracy: 0.5217
Epoch 83/100
2/2 [==============================] - 0s 32ms/step - loss: 5.3831 - accuracy: 0.4416 - val_loss: 5.0932 - val_accuracy: 0.5217
Epoch 84/100
2/2 [==============================] - 0s 50ms/step - loss: 5.3678 - accuracy: 0.4586 - val_loss: 5.0880 - val_accuracy: 0.5217
Epoch 85/100
2/2 [==============================] - 0s 46ms/step - loss: 5.3699 - accuracy: 0.4234 - val_loss: 5.0829 - val_accuracy: 0.5217
Epoch 86/100
2/2 [==============================] - 0s 28ms/step - loss: 5.3607 - accuracy: 0.4623 - val_loss: 5.0778 - val_accuracy: 0.5217
Epoch 87/100
2/2 [==============================] - 0s 35ms/step - loss: 5.3591 - accuracy: 0.4428 - val_loss: 5.0725 - val_accuracy: 0.5217
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3626 - accuracy: 0.4501 - val_loss: 5.0674 - val_accuracy: 0.5217
Epoch 89/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3465 - accuracy: 0.4611 - val_loss: 5.0622 - val_accuracy: 0.5326
Epoch 90/100
2/2 [==============================] - 0s 42ms/step - loss: 5.3367 - accuracy: 0.4477 - val_loss: 5.0571 - val_accuracy: 0.5326
Epoch 91/100
2/2 [==============================] - 0s 34ms/step - loss: 5.3169 - accuracy: 0.4538 - val_loss: 5.0520 - val_accuracy: 0.5326
Epoch 92/100
2/2 [==============================] - 0s 36ms/step - loss: 5.3488 - accuracy: 0.4659 - val_loss: 5.0469 - val_accuracy: 0.5326
Epoch 93/100
2/2 [==============================] - 0s 48ms/step - loss: 5.3219 - accuracy: 0.4489 - val_loss: 5.0417 - val_accuracy: 0.5326
Epoch 94/100
2/2 [==============================] - 0s 41ms/step - loss: 5.3226 - accuracy: 0.4319 - val_loss: 5.0366 - val_accuracy: 0.5326
Epoch 95/100
2/2 [==============================] - 0s 34ms/step - loss: 5.3163 - accuracy: 0.4647 - val_loss: 5.0315 - val_accuracy: 0.5326
Epoch 96/100
2/2 [==============================] - 0s 35ms/step - loss: 5.3107 - accuracy: 0.4599 - val_loss: 5.0264 - val_accuracy: 0.5326
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 5.2996 - accuracy: 0.4647 - val_loss: 5.0211 - val_accuracy: 0.5326
Epoch 98/100
2/2 [==============================] - 0s 30ms/step - loss: 5.2835 - accuracy: 0.4684 - val_loss: 5.0160 - val_accuracy: 0.5326
Epoch 99/100
2/2 [==============================] - 0s 32ms/step - loss: 5.2996 - accuracy: 0.4501 - val_loss: 5.0108 - val_accuracy: 0.5326
Epoch 100/100
2/2 [==============================] - 0s 28ms/step - loss: 5.3058 - accuracy: 0.4647 - val_loss: 5.0057 - val_accuracy: 0.5326
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 241ms/step - loss: 5.4402 - accuracy: 0.3504 - val_loss: 4.9060 - val_accuracy: 0.6413
Epoch 2/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4572 - accuracy: 0.3479 - val_loss: 4.9078 - val_accuracy: 0.6413
Epoch 3/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4509 - accuracy: 0.3370 - val_loss: 4.9091 - val_accuracy: 0.6413
Epoch 4/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4482 - accuracy: 0.3491 - val_loss: 4.9096 - val_accuracy: 0.6304
Epoch 5/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4362 - accuracy: 0.3650 - val_loss: 4.9098 - val_accuracy: 0.6304
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 5.4125 - accuracy: 0.3564 - val_loss: 4.9097 - val_accuracy: 0.6304
Epoch 7/100
2/2 [==============================] - 0s 39ms/step - loss: 5.4407 - accuracy: 0.3504 - val_loss: 4.9093 - val_accuracy: 0.6304
Epoch 8/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4089 - accuracy: 0.3625 - val_loss: 4.9085 - val_accuracy: 0.6304
Epoch 9/100
2/2 [==============================] - 0s 47ms/step - loss: 5.4292 - accuracy: 0.3516 - val_loss: 4.9076 - val_accuracy: 0.6196
Epoch 10/100
2/2 [==============================] - 0s 34ms/step - loss: 5.4135 - accuracy: 0.3577 - val_loss: 4.9067 - val_accuracy: 0.6196
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 5.3885 - accuracy: 0.3504 - val_loss: 4.9056 - val_accuracy: 0.6304
Epoch 12/100
2/2 [==============================] - 0s 45ms/step - loss: 5.4262 - accuracy: 0.3345 - val_loss: 4.9043 - val_accuracy: 0.6304
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4005 - accuracy: 0.3455 - val_loss: 4.9029 - val_accuracy: 0.6304
Epoch 14/100
2/2 [==============================] - 0s 29ms/step - loss: 5.3753 - accuracy: 0.3625 - val_loss: 4.9015 - val_accuracy: 0.6304
Epoch 15/100
2/2 [==============================] - 0s 44ms/step - loss: 5.3516 - accuracy: 0.3528 - val_loss: 4.9000 - val_accuracy: 0.6304
Epoch 16/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3871 - accuracy: 0.3771 - val_loss: 4.8985 - val_accuracy: 0.6304
Epoch 17/100
2/2 [==============================] - 0s 36ms/step - loss: 5.3785 - accuracy: 0.3625 - val_loss: 4.8969 - val_accuracy: 0.6196
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3384 - accuracy: 0.3869 - val_loss: 4.8955 - val_accuracy: 0.6196
Epoch 19/100
2/2 [==============================] - 0s 41ms/step - loss: 5.3456 - accuracy: 0.3650 - val_loss: 4.8940 - val_accuracy: 0.5978
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3599 - accuracy: 0.3710 - val_loss: 4.8925 - val_accuracy: 0.5978
Epoch 21/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3378 - accuracy: 0.3601 - val_loss: 4.8908 - val_accuracy: 0.5978
Epoch 22/100
2/2 [==============================] - 0s 42ms/step - loss: 5.3458 - accuracy: 0.3504 - val_loss: 4.8892 - val_accuracy: 0.5870
Epoch 23/100
2/2 [==============================] - 0s 42ms/step - loss: 5.3289 - accuracy: 0.3637 - val_loss: 4.8874 - val_accuracy: 0.5652
Epoch 24/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3293 - accuracy: 0.3528 - val_loss: 4.8856 - val_accuracy: 0.5652
Epoch 25/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3373 - accuracy: 0.3613 - val_loss: 4.8840 - val_accuracy: 0.5652
Epoch 26/100
2/2 [==============================] - 0s 41ms/step - loss: 5.2840 - accuracy: 0.3820 - val_loss: 4.8822 - val_accuracy: 0.5652
Epoch 27/100
2/2 [==============================] - 0s 42ms/step - loss: 5.3103 - accuracy: 0.3771 - val_loss: 4.8805 - val_accuracy: 0.5543
Epoch 28/100
2/2 [==============================] - 0s 39ms/step - loss: 5.2899 - accuracy: 0.3637 - val_loss: 4.8787 - val_accuracy: 0.5435
Epoch 29/100
2/2 [==============================] - 0s 40ms/step - loss: 5.2763 - accuracy: 0.3613 - val_loss: 4.8769 - val_accuracy: 0.5435
Epoch 30/100
2/2 [==============================] - 0s 40ms/step - loss: 5.3111 - accuracy: 0.3528 - val_loss: 4.8750 - val_accuracy: 0.5435
Epoch 31/100
2/2 [==============================] - 0s 41ms/step - loss: 5.2768 - accuracy: 0.3783 - val_loss: 4.8732 - val_accuracy: 0.5326
Epoch 32/100
2/2 [==============================] - 0s 37ms/step - loss: 5.2876 - accuracy: 0.3674 - val_loss: 4.8714 - val_accuracy: 0.5326
Epoch 33/100
2/2 [==============================] - 0s 40ms/step - loss: 5.2423 - accuracy: 0.3674 - val_loss: 4.8696 - val_accuracy: 0.5326
Epoch 34/100
2/2 [==============================] - 0s 35ms/step - loss: 5.2242 - accuracy: 0.3832 - val_loss: 4.8678 - val_accuracy: 0.5217
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 5.2602 - accuracy: 0.3686 - val_loss: 4.8658 - val_accuracy: 0.5217
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 5.2381 - accuracy: 0.3735 - val_loss: 4.8640 - val_accuracy: 0.5217
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 5.2523 - accuracy: 0.3735 - val_loss: 4.8622 - val_accuracy: 0.5000
Epoch 38/100
2/2 [==============================] - 0s 37ms/step - loss: 5.2164 - accuracy: 0.3808 - val_loss: 4.8603 - val_accuracy: 0.5000
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 5.2383 - accuracy: 0.3516 - val_loss: 4.8584 - val_accuracy: 0.5000
Epoch 40/100
2/2 [==============================] - 0s 30ms/step - loss: 5.2197 - accuracy: 0.3650 - val_loss: 4.8565 - val_accuracy: 0.4891
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 5.2208 - accuracy: 0.3686 - val_loss: 4.8545 - val_accuracy: 0.4783
Epoch 42/100
2/2 [==============================] - 0s 40ms/step - loss: 5.2048 - accuracy: 0.3856 - val_loss: 4.8525 - val_accuracy: 0.4783
Epoch 43/100
2/2 [==============================] - 0s 44ms/step - loss: 5.1759 - accuracy: 0.3942 - val_loss: 4.8505 - val_accuracy: 0.4783
Epoch 44/100
2/2 [==============================] - 0s 38ms/step - loss: 5.2032 - accuracy: 0.3735 - val_loss: 4.8485 - val_accuracy: 0.4783
Epoch 45/100
2/2 [==============================] - 0s 39ms/step - loss: 5.1778 - accuracy: 0.3832 - val_loss: 4.8464 - val_accuracy: 0.4783
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 5.1849 - accuracy: 0.3881 - val_loss: 4.8443 - val_accuracy: 0.4783
Epoch 47/100
2/2 [==============================] - 0s 30ms/step - loss: 5.1520 - accuracy: 0.4051 - val_loss: 4.8422 - val_accuracy: 0.4674
Epoch 48/100
2/2 [==============================] - 0s 41ms/step - loss: 5.1342 - accuracy: 0.4027 - val_loss: 4.8401 - val_accuracy: 0.4565
Epoch 49/100
2/2 [==============================] - 0s 36ms/step - loss: 5.1684 - accuracy: 0.3844 - val_loss: 4.8381 - val_accuracy: 0.4348
Epoch 50/100
2/2 [==============================] - 0s 37ms/step - loss: 5.1560 - accuracy: 0.3905 - val_loss: 4.8360 - val_accuracy: 0.4130
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 5.1166 - accuracy: 0.3856 - val_loss: 4.8339 - val_accuracy: 0.4130
Epoch 52/100
2/2 [==============================] - 0s 40ms/step - loss: 5.1444 - accuracy: 0.3893 - val_loss: 4.8318 - val_accuracy: 0.4130
Epoch 53/100
2/2 [==============================] - 0s 39ms/step - loss: 5.1224 - accuracy: 0.3978 - val_loss: 4.8297 - val_accuracy: 0.4130
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 5.1110 - accuracy: 0.3942 - val_loss: 4.8274 - val_accuracy: 0.4130
Epoch 55/100
2/2 [==============================] - 0s 38ms/step - loss: 5.1339 - accuracy: 0.3942 - val_loss: 4.8252 - val_accuracy: 0.4130
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 5.1077 - accuracy: 0.3905 - val_loss: 4.8228 - val_accuracy: 0.4130
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 5.0869 - accuracy: 0.4124 - val_loss: 4.8206 - val_accuracy: 0.4130
Epoch 58/100
2/2 [==============================] - 0s 42ms/step - loss: 5.1377 - accuracy: 0.3759 - val_loss: 4.8183 - val_accuracy: 0.4130
Epoch 59/100
2/2 [==============================] - 0s 37ms/step - loss: 5.0894 - accuracy: 0.4002 - val_loss: 4.8160 - val_accuracy: 0.4022
Epoch 60/100
2/2 [==============================] - 0s 44ms/step - loss: 5.0938 - accuracy: 0.3783 - val_loss: 4.8137 - val_accuracy: 0.4022
Epoch 61/100
2/2 [==============================] - 0s 32ms/step - loss: 5.0646 - accuracy: 0.3978 - val_loss: 4.8113 - val_accuracy: 0.4022
Epoch 62/100
2/2 [==============================] - 0s 34ms/step - loss: 5.1000 - accuracy: 0.3856 - val_loss: 4.8090 - val_accuracy: 0.4022
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 5.0765 - accuracy: 0.3844 - val_loss: 4.8066 - val_accuracy: 0.4022
Epoch 64/100
2/2 [==============================] - 0s 47ms/step - loss: 5.0513 - accuracy: 0.4002 - val_loss: 4.8041 - val_accuracy: 0.4022
Epoch 65/100
2/2 [==============================] - 0s 49ms/step - loss: 5.0541 - accuracy: 0.3990 - val_loss: 4.8017 - val_accuracy: 0.4022
Epoch 66/100
2/2 [==============================] - 0s 38ms/step - loss: 5.0438 - accuracy: 0.4063 - val_loss: 4.7990 - val_accuracy: 0.4022
Epoch 67/100
2/2 [==============================] - 0s 31ms/step - loss: 5.0434 - accuracy: 0.4075 - val_loss: 4.7965 - val_accuracy: 0.4022
Epoch 68/100
2/2 [==============================] - 0s 36ms/step - loss: 5.0307 - accuracy: 0.4088 - val_loss: 4.7940 - val_accuracy: 0.4022
Epoch 69/100
2/2 [==============================] - 0s 33ms/step - loss: 5.0256 - accuracy: 0.3929 - val_loss: 4.7916 - val_accuracy: 0.4022
Epoch 70/100
2/2 [==============================] - 0s 34ms/step - loss: 5.0257 - accuracy: 0.4075 - val_loss: 4.7890 - val_accuracy: 0.4022
Epoch 71/100
2/2 [==============================] - 0s 36ms/step - loss: 5.0135 - accuracy: 0.4051 - val_loss: 4.7864 - val_accuracy: 0.4022
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 5.0321 - accuracy: 0.3942 - val_loss: 4.7839 - val_accuracy: 0.4022
Epoch 73/100
2/2 [==============================] - 0s 42ms/step - loss: 5.0324 - accuracy: 0.3844 - val_loss: 4.7813 - val_accuracy: 0.4022
Epoch 74/100
2/2 [==============================] - 0s 37ms/step - loss: 4.9859 - accuracy: 0.4100 - val_loss: 4.7786 - val_accuracy: 0.4022
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 4.9755 - accuracy: 0.4234 - val_loss: 4.7758 - val_accuracy: 0.4022
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 4.9965 - accuracy: 0.4002 - val_loss: 4.7730 - val_accuracy: 0.4022
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 4.9757 - accuracy: 0.4002 - val_loss: 4.7703 - val_accuracy: 0.4022
Epoch 78/100
2/2 [==============================] - 0s 40ms/step - loss: 4.9959 - accuracy: 0.4063 - val_loss: 4.7677 - val_accuracy: 0.4022
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 4.9739 - accuracy: 0.4002 - val_loss: 4.7649 - val_accuracy: 0.4022
Epoch 80/100
2/2 [==============================] - 0s 43ms/step - loss: 4.9440 - accuracy: 0.4051 - val_loss: 4.7622 - val_accuracy: 0.4022
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 4.9776 - accuracy: 0.4051 - val_loss: 4.7593 - val_accuracy: 0.4022
Epoch 82/100
2/2 [==============================] - 0s 41ms/step - loss: 4.9446 - accuracy: 0.4088 - val_loss: 4.7565 - val_accuracy: 0.3913
Epoch 83/100
2/2 [==============================] - 0s 40ms/step - loss: 4.9414 - accuracy: 0.4234 - val_loss: 4.7537 - val_accuracy: 0.3804
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 4.9181 - accuracy: 0.4331 - val_loss: 4.7507 - val_accuracy: 0.3913
Epoch 85/100
2/2 [==============================] - 0s 41ms/step - loss: 4.9316 - accuracy: 0.4404 - val_loss: 4.7478 - val_accuracy: 0.3913
Epoch 86/100
2/2 [==============================] - 0s 38ms/step - loss: 4.9155 - accuracy: 0.4112 - val_loss: 4.7448 - val_accuracy: 0.3913
Epoch 87/100
2/2 [==============================] - 0s 32ms/step - loss: 4.9192 - accuracy: 0.3978 - val_loss: 4.7419 - val_accuracy: 0.3913
Epoch 88/100
2/2 [==============================] - 0s 75ms/step - loss: 4.9087 - accuracy: 0.4270 - val_loss: 4.7390 - val_accuracy: 0.3913
Epoch 89/100
2/2 [==============================] - 0s 35ms/step - loss: 4.9211 - accuracy: 0.4136 - val_loss: 4.7359 - val_accuracy: 0.3913
Epoch 90/100
2/2 [==============================] - 0s 40ms/step - loss: 4.9389 - accuracy: 0.4136 - val_loss: 4.7330 - val_accuracy: 0.3913
Epoch 91/100
2/2 [==============================] - 0s 38ms/step - loss: 4.8830 - accuracy: 0.4209 - val_loss: 4.7301 - val_accuracy: 0.3913
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 4.9169 - accuracy: 0.4112 - val_loss: 4.7271 - val_accuracy: 0.3913
Epoch 93/100
2/2 [==============================] - 0s 28ms/step - loss: 4.8988 - accuracy: 0.4136 - val_loss: 4.7240 - val_accuracy: 0.3913
Epoch 94/100
2/2 [==============================] - 0s 34ms/step - loss: 4.8929 - accuracy: 0.4234 - val_loss: 4.7209 - val_accuracy: 0.3913
Epoch 95/100
2/2 [==============================] - 0s 36ms/step - loss: 4.8797 - accuracy: 0.4234 - val_loss: 4.7178 - val_accuracy: 0.3913
Epoch 96/100
2/2 [==============================] - 0s 34ms/step - loss: 4.8731 - accuracy: 0.4246 - val_loss: 4.7148 - val_accuracy: 0.4022
Epoch 97/100
2/2 [==============================] - 0s 36ms/step - loss: 4.9043 - accuracy: 0.4234 - val_loss: 4.7118 - val_accuracy: 0.4022
Epoch 98/100
2/2 [==============================] - 0s 38ms/step - loss: 4.8782 - accuracy: 0.4343 - val_loss: 4.7088 - val_accuracy: 0.4130
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 4.8653 - accuracy: 0.4258 - val_loss: 4.7056 - val_accuracy: 0.4130
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 4.8585 - accuracy: 0.4465 - val_loss: 4.7024 - val_accuracy: 0.4130
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 809us/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 244ms/step - loss: 5.7576 - accuracy: 0.3698 - val_loss: 5.5784 - val_accuracy: 0.3261
Epoch 2/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7681 - accuracy: 0.3796 - val_loss: 5.5758 - val_accuracy: 0.3261
Epoch 3/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7492 - accuracy: 0.3905 - val_loss: 5.5725 - val_accuracy: 0.3370
Epoch 4/100
2/2 [==============================] - 0s 33ms/step - loss: 5.7583 - accuracy: 0.3747 - val_loss: 5.5684 - val_accuracy: 0.3370
Epoch 5/100
2/2 [==============================] - 0s 41ms/step - loss: 5.7680 - accuracy: 0.3869 - val_loss: 5.5635 - val_accuracy: 0.3370
Epoch 6/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7880 - accuracy: 0.3844 - val_loss: 5.5583 - val_accuracy: 0.3370
Epoch 7/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7543 - accuracy: 0.3844 - val_loss: 5.5528 - val_accuracy: 0.3370
Epoch 8/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7503 - accuracy: 0.4075 - val_loss: 5.5470 - val_accuracy: 0.3370
Epoch 9/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7552 - accuracy: 0.3832 - val_loss: 5.5408 - val_accuracy: 0.3370
Epoch 10/100
2/2 [==============================] - 0s 43ms/step - loss: 5.7236 - accuracy: 0.3796 - val_loss: 5.5345 - val_accuracy: 0.3370
Epoch 11/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7702 - accuracy: 0.3650 - val_loss: 5.5282 - val_accuracy: 0.3370
Epoch 12/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6870 - accuracy: 0.3978 - val_loss: 5.5219 - val_accuracy: 0.3370
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7055 - accuracy: 0.3893 - val_loss: 5.5156 - val_accuracy: 0.3370
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7056 - accuracy: 0.4063 - val_loss: 5.5090 - val_accuracy: 0.3370
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6972 - accuracy: 0.3917 - val_loss: 5.5025 - val_accuracy: 0.3370
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7073 - accuracy: 0.3905 - val_loss: 5.4960 - val_accuracy: 0.3478
Epoch 17/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7018 - accuracy: 0.3954 - val_loss: 5.4892 - val_accuracy: 0.3478
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 5.6588 - accuracy: 0.4051 - val_loss: 5.4825 - val_accuracy: 0.3478
Epoch 19/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6783 - accuracy: 0.3954 - val_loss: 5.4759 - val_accuracy: 0.3478
Epoch 20/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6192 - accuracy: 0.3978 - val_loss: 5.4690 - val_accuracy: 0.3478
Epoch 21/100
2/2 [==============================] - 0s 39ms/step - loss: 5.6695 - accuracy: 0.3978 - val_loss: 5.4621 - val_accuracy: 0.3478
Epoch 22/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6331 - accuracy: 0.3966 - val_loss: 5.4552 - val_accuracy: 0.3478
Epoch 23/100
2/2 [==============================] - 0s 41ms/step - loss: 5.6401 - accuracy: 0.3942 - val_loss: 5.4486 - val_accuracy: 0.3478
Epoch 24/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6275 - accuracy: 0.4209 - val_loss: 5.4421 - val_accuracy: 0.3370
Epoch 25/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6166 - accuracy: 0.4015 - val_loss: 5.4357 - val_accuracy: 0.3478
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 5.6385 - accuracy: 0.3978 - val_loss: 5.4291 - val_accuracy: 0.3478
Epoch 27/100
2/2 [==============================] - 0s 47ms/step - loss: 5.5597 - accuracy: 0.4161 - val_loss: 5.4224 - val_accuracy: 0.3478
Epoch 28/100
2/2 [==============================] - 0s 33ms/step - loss: 5.5765 - accuracy: 0.4136 - val_loss: 5.4157 - val_accuracy: 0.3478
Epoch 29/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5750 - accuracy: 0.4161 - val_loss: 5.4093 - val_accuracy: 0.3478
Epoch 30/100
2/2 [==============================] - 0s 41ms/step - loss: 5.5569 - accuracy: 0.4039 - val_loss: 5.4027 - val_accuracy: 0.3478
Epoch 31/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5717 - accuracy: 0.4088 - val_loss: 5.3962 - val_accuracy: 0.3478
Epoch 32/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5621 - accuracy: 0.3990 - val_loss: 5.3897 - val_accuracy: 0.3478
Epoch 33/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5755 - accuracy: 0.4148 - val_loss: 5.3833 - val_accuracy: 0.3478
Epoch 34/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5650 - accuracy: 0.4075 - val_loss: 5.3767 - val_accuracy: 0.3478
Epoch 35/100
2/2 [==============================] - 0s 45ms/step - loss: 5.5506 - accuracy: 0.4112 - val_loss: 5.3702 - val_accuracy: 0.3478
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5523 - accuracy: 0.4209 - val_loss: 5.3638 - val_accuracy: 0.3587
Epoch 37/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5445 - accuracy: 0.4161 - val_loss: 5.3574 - val_accuracy: 0.3587
Epoch 38/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5193 - accuracy: 0.4100 - val_loss: 5.3508 - val_accuracy: 0.3587
Epoch 39/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5348 - accuracy: 0.3917 - val_loss: 5.3445 - val_accuracy: 0.3587
Epoch 40/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5321 - accuracy: 0.4331 - val_loss: 5.3381 - val_accuracy: 0.3696
Epoch 41/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5095 - accuracy: 0.4063 - val_loss: 5.3318 - val_accuracy: 0.3696
Epoch 42/100
2/2 [==============================] - 0s 25ms/step - loss: 5.5030 - accuracy: 0.4002 - val_loss: 5.3255 - val_accuracy: 0.3696
Epoch 43/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4575 - accuracy: 0.4416 - val_loss: 5.3192 - val_accuracy: 0.3696
Epoch 44/100
2/2 [==============================] - 0s 39ms/step - loss: 5.4760 - accuracy: 0.4185 - val_loss: 5.3129 - val_accuracy: 0.3913
Epoch 45/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4815 - accuracy: 0.4282 - val_loss: 5.3065 - val_accuracy: 0.4022
Epoch 46/100
2/2 [==============================] - 0s 49ms/step - loss: 5.4723 - accuracy: 0.4380 - val_loss: 5.3002 - val_accuracy: 0.4130
Epoch 47/100
2/2 [==============================] - 0s 49ms/step - loss: 5.4989 - accuracy: 0.4063 - val_loss: 5.2940 - val_accuracy: 0.4239
Epoch 48/100
2/2 [==============================] - 0s 50ms/step - loss: 5.4545 - accuracy: 0.4258 - val_loss: 5.2877 - val_accuracy: 0.4239
Epoch 49/100
2/2 [==============================] - 0s 49ms/step - loss: 5.4400 - accuracy: 0.4355 - val_loss: 5.2814 - val_accuracy: 0.4239
Epoch 50/100
2/2 [==============================] - 0s 49ms/step - loss: 5.4471 - accuracy: 0.4465 - val_loss: 5.2751 - val_accuracy: 0.4348
Epoch 51/100
2/2 [==============================] - 0s 47ms/step - loss: 5.4473 - accuracy: 0.4380 - val_loss: 5.2689 - val_accuracy: 0.4348
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4153 - accuracy: 0.4465 - val_loss: 5.2625 - val_accuracy: 0.4348
Epoch 53/100
2/2 [==============================] - 0s 33ms/step - loss: 5.4485 - accuracy: 0.4258 - val_loss: 5.2563 - val_accuracy: 0.4348
Epoch 54/100
2/2 [==============================] - 0s 35ms/step - loss: 5.3799 - accuracy: 0.4562 - val_loss: 5.2500 - val_accuracy: 0.4348
Epoch 55/100
2/2 [==============================] - 0s 34ms/step - loss: 5.4425 - accuracy: 0.4392 - val_loss: 5.2437 - val_accuracy: 0.4348
Epoch 56/100
2/2 [==============================] - 0s 47ms/step - loss: 5.3833 - accuracy: 0.4380 - val_loss: 5.2376 - val_accuracy: 0.4348
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4096 - accuracy: 0.4355 - val_loss: 5.2314 - val_accuracy: 0.4348
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4223 - accuracy: 0.4209 - val_loss: 5.2250 - val_accuracy: 0.4348
Epoch 59/100
2/2 [==============================] - 0s 37ms/step - loss: 5.3845 - accuracy: 0.4416 - val_loss: 5.2189 - val_accuracy: 0.4348
Epoch 60/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3817 - accuracy: 0.4307 - val_loss: 5.2127 - val_accuracy: 0.4348
Epoch 61/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3846 - accuracy: 0.4440 - val_loss: 5.2066 - val_accuracy: 0.4348
Epoch 62/100
2/2 [==============================] - 0s 34ms/step - loss: 5.4110 - accuracy: 0.4209 - val_loss: 5.2005 - val_accuracy: 0.4457
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 5.3632 - accuracy: 0.4282 - val_loss: 5.1945 - val_accuracy: 0.4565
Epoch 64/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3519 - accuracy: 0.4574 - val_loss: 5.1886 - val_accuracy: 0.4565
Epoch 65/100
2/2 [==============================] - 0s 34ms/step - loss: 5.3388 - accuracy: 0.4307 - val_loss: 5.1825 - val_accuracy: 0.4565
Epoch 66/100
2/2 [==============================] - 0s 33ms/step - loss: 5.3287 - accuracy: 0.4501 - val_loss: 5.1765 - val_accuracy: 0.4565
Epoch 67/100
2/2 [==============================] - 0s 36ms/step - loss: 5.3179 - accuracy: 0.4611 - val_loss: 5.1704 - val_accuracy: 0.4565
Epoch 68/100
2/2 [==============================] - 0s 35ms/step - loss: 5.3328 - accuracy: 0.4440 - val_loss: 5.1647 - val_accuracy: 0.4565
Epoch 69/100
2/2 [==============================] - 0s 52ms/step - loss: 5.2993 - accuracy: 0.4550 - val_loss: 5.1587 - val_accuracy: 0.4565
Epoch 70/100
2/2 [==============================] - 0s 46ms/step - loss: 5.3034 - accuracy: 0.4416 - val_loss: 5.1526 - val_accuracy: 0.4565
Epoch 71/100
2/2 [==============================] - 0s 41ms/step - loss: 5.2911 - accuracy: 0.4526 - val_loss: 5.1467 - val_accuracy: 0.4565
Epoch 72/100
2/2 [==============================] - 0s 33ms/step - loss: 5.3242 - accuracy: 0.4331 - val_loss: 5.1406 - val_accuracy: 0.4565
Epoch 73/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3167 - accuracy: 0.4307 - val_loss: 5.1348 - val_accuracy: 0.4565
Epoch 74/100
2/2 [==============================] - 0s 37ms/step - loss: 5.2645 - accuracy: 0.4453 - val_loss: 5.1290 - val_accuracy: 0.4565
Epoch 75/100
2/2 [==============================] - 0s 40ms/step - loss: 5.3048 - accuracy: 0.4477 - val_loss: 5.1232 - val_accuracy: 0.4565
Epoch 76/100
2/2 [==============================] - 0s 39ms/step - loss: 5.2807 - accuracy: 0.4416 - val_loss: 5.1175 - val_accuracy: 0.4565
Epoch 77/100
2/2 [==============================] - 0s 39ms/step - loss: 5.2626 - accuracy: 0.4562 - val_loss: 5.1117 - val_accuracy: 0.4565
Epoch 78/100
2/2 [==============================] - 0s 29ms/step - loss: 5.2603 - accuracy: 0.4720 - val_loss: 5.1057 - val_accuracy: 0.4565
Epoch 79/100
2/2 [==============================] - 0s 37ms/step - loss: 5.2621 - accuracy: 0.4659 - val_loss: 5.0999 - val_accuracy: 0.4565
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 5.2079 - accuracy: 0.4526 - val_loss: 5.0941 - val_accuracy: 0.4565
Epoch 81/100
2/2 [==============================] - 0s 34ms/step - loss: 5.2500 - accuracy: 0.4392 - val_loss: 5.0881 - val_accuracy: 0.4674
Epoch 82/100
2/2 [==============================] - 0s 37ms/step - loss: 5.2442 - accuracy: 0.4513 - val_loss: 5.0823 - val_accuracy: 0.4674
Epoch 83/100
2/2 [==============================] - 0s 40ms/step - loss: 5.2359 - accuracy: 0.4732 - val_loss: 5.0766 - val_accuracy: 0.4674
Epoch 84/100
2/2 [==============================] - 0s 37ms/step - loss: 5.2308 - accuracy: 0.4440 - val_loss: 5.0708 - val_accuracy: 0.4674
Epoch 85/100
2/2 [==============================] - 0s 46ms/step - loss: 5.2001 - accuracy: 0.4574 - val_loss: 5.0649 - val_accuracy: 0.4674
Epoch 86/100
2/2 [==============================] - 0s 38ms/step - loss: 5.1592 - accuracy: 0.4708 - val_loss: 5.0590 - val_accuracy: 0.4674
Epoch 87/100
2/2 [==============================] - 0s 32ms/step - loss: 5.1895 - accuracy: 0.4769 - val_loss: 5.0533 - val_accuracy: 0.4674
Epoch 88/100
2/2 [==============================] - 0s 29ms/step - loss: 5.1842 - accuracy: 0.4745 - val_loss: 5.0474 - val_accuracy: 0.4674
Epoch 89/100
2/2 [==============================] - 0s 37ms/step - loss: 5.2152 - accuracy: 0.4501 - val_loss: 5.0415 - val_accuracy: 0.4674
Epoch 90/100
2/2 [==============================] - 0s 48ms/step - loss: 5.1844 - accuracy: 0.4635 - val_loss: 5.0358 - val_accuracy: 0.4674
Epoch 91/100
2/2 [==============================] - 0s 42ms/step - loss: 5.1771 - accuracy: 0.4599 - val_loss: 5.0300 - val_accuracy: 0.4674
Epoch 92/100
2/2 [==============================] - 0s 41ms/step - loss: 5.1338 - accuracy: 0.4672 - val_loss: 5.0244 - val_accuracy: 0.4674
Epoch 93/100
2/2 [==============================] - 0s 36ms/step - loss: 5.1531 - accuracy: 0.4927 - val_loss: 5.0186 - val_accuracy: 0.4674
Epoch 94/100
2/2 [==============================] - 0s 46ms/step - loss: 5.1456 - accuracy: 0.4781 - val_loss: 5.0128 - val_accuracy: 0.4783
Epoch 95/100
2/2 [==============================] - 0s 41ms/step - loss: 5.1288 - accuracy: 0.4951 - val_loss: 5.0070 - val_accuracy: 0.4891
Epoch 96/100
2/2 [==============================] - 0s 42ms/step - loss: 5.1303 - accuracy: 0.4623 - val_loss: 5.0013 - val_accuracy: 0.4891
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 5.1309 - accuracy: 0.4830 - val_loss: 4.9955 - val_accuracy: 0.4891
Epoch 98/100
2/2 [==============================] - 0s 37ms/step - loss: 5.1496 - accuracy: 0.4830 - val_loss: 4.9897 - val_accuracy: 0.5000
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 5.1199 - accuracy: 0.4866 - val_loss: 4.9839 - val_accuracy: 0.5000
Epoch 100/100
2/2 [==============================] - 0s 44ms/step - loss: 5.1058 - accuracy: 0.4951 - val_loss: 4.9782 - val_accuracy: 0.5000
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 810us/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 2s 249ms/step - loss: 6.0125 - accuracy: 0.4678 - val_loss: 6.1630 - val_accuracy: 0.0769
Epoch 2/100
2/2 [==============================] - 0s 41ms/step - loss: 5.9790 - accuracy: 0.4787 - val_loss: 6.1559 - val_accuracy: 0.0769
Epoch 3/100
2/2 [==============================] - 0s 35ms/step - loss: 6.0574 - accuracy: 0.4569 - val_loss: 6.1476 - val_accuracy: 0.0989
Epoch 4/100
2/2 [==============================] - 0s 35ms/step - loss: 5.9995 - accuracy: 0.4617 - val_loss: 6.1385 - val_accuracy: 0.1099
Epoch 5/100
2/2 [==============================] - 0s 35ms/step - loss: 5.9572 - accuracy: 0.4824 - val_loss: 6.1289 - val_accuracy: 0.1099
Epoch 6/100
2/2 [==============================] - 0s 33ms/step - loss: 6.0463 - accuracy: 0.4544 - val_loss: 6.1188 - val_accuracy: 0.1209
Epoch 7/100
2/2 [==============================] - 0s 36ms/step - loss: 6.0121 - accuracy: 0.4714 - val_loss: 6.1083 - val_accuracy: 0.1209
Epoch 8/100
2/2 [==============================] - 0s 49ms/step - loss: 5.9906 - accuracy: 0.4690 - val_loss: 6.0975 - val_accuracy: 0.1209
Epoch 9/100
2/2 [==============================] - 0s 34ms/step - loss: 6.0093 - accuracy: 0.4763 - val_loss: 6.0865 - val_accuracy: 0.1319
Epoch 10/100
2/2 [==============================] - 0s 33ms/step - loss: 5.9666 - accuracy: 0.4800 - val_loss: 6.0754 - val_accuracy: 0.1319
Epoch 11/100
2/2 [==============================] - 0s 35ms/step - loss: 5.9918 - accuracy: 0.4593 - val_loss: 6.0641 - val_accuracy: 0.1429
Epoch 12/100
2/2 [==============================] - 0s 35ms/step - loss: 5.9352 - accuracy: 0.4812 - val_loss: 6.0529 - val_accuracy: 0.1429
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 5.9623 - accuracy: 0.4557 - val_loss: 6.0415 - val_accuracy: 0.1538
Epoch 14/100
2/2 [==============================] - 0s 32ms/step - loss: 5.9674 - accuracy: 0.4605 - val_loss: 6.0299 - val_accuracy: 0.1758
Epoch 15/100
2/2 [==============================] - 0s 32ms/step - loss: 5.9221 - accuracy: 0.4787 - val_loss: 6.0184 - val_accuracy: 0.1868
Epoch 16/100
2/2 [==============================] - 0s 50ms/step - loss: 5.9561 - accuracy: 0.4569 - val_loss: 6.0070 - val_accuracy: 0.1868
Epoch 17/100
2/2 [==============================] - 0s 33ms/step - loss: 5.8930 - accuracy: 0.4751 - val_loss: 5.9955 - val_accuracy: 0.1978
Epoch 18/100
2/2 [==============================] - 0s 33ms/step - loss: 5.9941 - accuracy: 0.4447 - val_loss: 5.9842 - val_accuracy: 0.1978
Epoch 19/100
2/2 [==============================] - 0s 38ms/step - loss: 5.8733 - accuracy: 0.4787 - val_loss: 5.9729 - val_accuracy: 0.1978
Epoch 20/100
2/2 [==============================] - 0s 36ms/step - loss: 5.8800 - accuracy: 0.4605 - val_loss: 5.9616 - val_accuracy: 0.1978
Epoch 21/100
2/2 [==============================] - 0s 35ms/step - loss: 5.9507 - accuracy: 0.4714 - val_loss: 5.9503 - val_accuracy: 0.1978
Epoch 22/100
2/2 [==============================] - 0s 49ms/step - loss: 5.8935 - accuracy: 0.4678 - val_loss: 5.9393 - val_accuracy: 0.2088
Epoch 23/100
2/2 [==============================] - 0s 44ms/step - loss: 5.9018 - accuracy: 0.4654 - val_loss: 5.9281 - val_accuracy: 0.2198
Epoch 24/100
2/2 [==============================] - 0s 47ms/step - loss: 5.9095 - accuracy: 0.4678 - val_loss: 5.9171 - val_accuracy: 0.2308
Epoch 25/100
2/2 [==============================] - 0s 35ms/step - loss: 5.8741 - accuracy: 0.4569 - val_loss: 5.9062 - val_accuracy: 0.2418
Epoch 26/100
2/2 [==============================] - 0s 34ms/step - loss: 5.8626 - accuracy: 0.4860 - val_loss: 5.8952 - val_accuracy: 0.2637
Epoch 27/100
2/2 [==============================] - 0s 36ms/step - loss: 5.8769 - accuracy: 0.4751 - val_loss: 5.8845 - val_accuracy: 0.2637
Epoch 28/100
2/2 [==============================] - 0s 34ms/step - loss: 5.8737 - accuracy: 0.4666 - val_loss: 5.8739 - val_accuracy: 0.2857
Epoch 29/100
2/2 [==============================] - 0s 32ms/step - loss: 5.8332 - accuracy: 0.4909 - val_loss: 5.8631 - val_accuracy: 0.2857
Epoch 30/100
2/2 [==============================] - 0s 53ms/step - loss: 5.8678 - accuracy: 0.4654 - val_loss: 5.8524 - val_accuracy: 0.2857
Epoch 31/100
2/2 [==============================] - 0s 52ms/step - loss: 5.8022 - accuracy: 0.4970 - val_loss: 5.8417 - val_accuracy: 0.2857
Epoch 32/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8413 - accuracy: 0.4860 - val_loss: 5.8313 - val_accuracy: 0.2857
Epoch 33/100
2/2 [==============================] - 0s 49ms/step - loss: 5.7967 - accuracy: 0.5006 - val_loss: 5.8210 - val_accuracy: 0.2857
Epoch 34/100
2/2 [==============================] - 0s 50ms/step - loss: 5.8297 - accuracy: 0.4714 - val_loss: 5.8107 - val_accuracy: 0.2857
Epoch 35/100
2/2 [==============================] - 0s 50ms/step - loss: 5.7708 - accuracy: 0.4885 - val_loss: 5.8004 - val_accuracy: 0.2967
Epoch 36/100
2/2 [==============================] - 0s 46ms/step - loss: 5.7987 - accuracy: 0.4957 - val_loss: 5.7905 - val_accuracy: 0.2967
Epoch 37/100
2/2 [==============================] - 0s 35ms/step - loss: 5.7728 - accuracy: 0.4945 - val_loss: 5.7806 - val_accuracy: 0.3077
Epoch 38/100
2/2 [==============================] - 0s 33ms/step - loss: 5.7643 - accuracy: 0.4921 - val_loss: 5.7706 - val_accuracy: 0.3187
Epoch 39/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7307 - accuracy: 0.5067 - val_loss: 5.7607 - val_accuracy: 0.3187
Epoch 40/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7907 - accuracy: 0.5043 - val_loss: 5.7510 - val_accuracy: 0.3297
Epoch 41/100
2/2 [==============================] - 0s 51ms/step - loss: 5.7799 - accuracy: 0.4933 - val_loss: 5.7413 - val_accuracy: 0.3297
Epoch 42/100
2/2 [==============================] - 0s 49ms/step - loss: 5.7622 - accuracy: 0.5103 - val_loss: 5.7317 - val_accuracy: 0.3297
Epoch 43/100
2/2 [==============================] - 0s 49ms/step - loss: 5.7658 - accuracy: 0.5018 - val_loss: 5.7219 - val_accuracy: 0.3297
Epoch 44/100
2/2 [==============================] - 0s 47ms/step - loss: 5.7350 - accuracy: 0.5067 - val_loss: 5.7119 - val_accuracy: 0.3407
Epoch 45/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6780 - accuracy: 0.5176 - val_loss: 5.7022 - val_accuracy: 0.3407
Epoch 46/100
2/2 [==============================] - 0s 33ms/step - loss: 5.7464 - accuracy: 0.5091 - val_loss: 5.6926 - val_accuracy: 0.3516
Epoch 47/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7116 - accuracy: 0.5176 - val_loss: 5.6831 - val_accuracy: 0.3626
Epoch 48/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6582 - accuracy: 0.5261 - val_loss: 5.6738 - val_accuracy: 0.3626
Epoch 49/100
2/2 [==============================] - 0s 41ms/step - loss: 5.7355 - accuracy: 0.4872 - val_loss: 5.6644 - val_accuracy: 0.3736
Epoch 50/100
2/2 [==============================] - 0s 49ms/step - loss: 5.7192 - accuracy: 0.4872 - val_loss: 5.6551 - val_accuracy: 0.3956
Epoch 51/100
2/2 [==============================] - 0s 47ms/step - loss: 5.6956 - accuracy: 0.5273 - val_loss: 5.6458 - val_accuracy: 0.4066
Epoch 52/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6680 - accuracy: 0.4982 - val_loss: 5.6365 - val_accuracy: 0.4066
Epoch 53/100
2/2 [==============================] - 0s 43ms/step - loss: 5.6805 - accuracy: 0.5200 - val_loss: 5.6273 - val_accuracy: 0.4286
Epoch 54/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6773 - accuracy: 0.5164 - val_loss: 5.6184 - val_accuracy: 0.4505
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6664 - accuracy: 0.5200 - val_loss: 5.6092 - val_accuracy: 0.4615
Epoch 56/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6338 - accuracy: 0.5383 - val_loss: 5.6000 - val_accuracy: 0.4725
Epoch 57/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6521 - accuracy: 0.5115 - val_loss: 5.5908 - val_accuracy: 0.4945
Epoch 58/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6549 - accuracy: 0.5164 - val_loss: 5.5821 - val_accuracy: 0.4945
Epoch 59/100
2/2 [==============================] - 0s 33ms/step - loss: 5.5988 - accuracy: 0.5213 - val_loss: 5.5733 - val_accuracy: 0.4945
Epoch 60/100
2/2 [==============================] - 0s 40ms/step - loss: 5.6232 - accuracy: 0.5152 - val_loss: 5.5645 - val_accuracy: 0.5055
Epoch 61/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6142 - accuracy: 0.5103 - val_loss: 5.5557 - val_accuracy: 0.5165
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5934 - accuracy: 0.5468 - val_loss: 5.5470 - val_accuracy: 0.5275
Epoch 63/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5790 - accuracy: 0.5456 - val_loss: 5.5382 - val_accuracy: 0.5275
Epoch 64/100
2/2 [==============================] - 0s 34ms/step - loss: 5.5860 - accuracy: 0.5140 - val_loss: 5.5297 - val_accuracy: 0.5275
Epoch 65/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5662 - accuracy: 0.5371 - val_loss: 5.5211 - val_accuracy: 0.5275
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5732 - accuracy: 0.5115 - val_loss: 5.5128 - val_accuracy: 0.5385
Epoch 67/100
2/2 [==============================] - 0s 49ms/step - loss: 5.5532 - accuracy: 0.5322 - val_loss: 5.5042 - val_accuracy: 0.5385
Epoch 68/100
2/2 [==============================] - 0s 80ms/step - loss: 5.5730 - accuracy: 0.5115 - val_loss: 5.4959 - val_accuracy: 0.5385
Epoch 69/100
2/2 [==============================] - 0s 30ms/step - loss: 5.5478 - accuracy: 0.5128 - val_loss: 5.4874 - val_accuracy: 0.5385
Epoch 70/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5474 - accuracy: 0.5334 - val_loss: 5.4792 - val_accuracy: 0.5385
Epoch 71/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5190 - accuracy: 0.5492 - val_loss: 5.4711 - val_accuracy: 0.5385
Epoch 72/100
2/2 [==============================] - 0s 42ms/step - loss: 5.5250 - accuracy: 0.5225 - val_loss: 5.4629 - val_accuracy: 0.5385
Epoch 73/100
2/2 [==============================] - 0s 28ms/step - loss: 5.5325 - accuracy: 0.5358 - val_loss: 5.4548 - val_accuracy: 0.5495
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5095 - accuracy: 0.5419 - val_loss: 5.4467 - val_accuracy: 0.5495
Epoch 75/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4959 - accuracy: 0.5456 - val_loss: 5.4387 - val_accuracy: 0.5495
Epoch 76/100
2/2 [==============================] - 0s 34ms/step - loss: 5.5436 - accuracy: 0.5407 - val_loss: 5.4309 - val_accuracy: 0.5495
Epoch 77/100
2/2 [==============================] - 0s 49ms/step - loss: 5.5339 - accuracy: 0.5589 - val_loss: 5.4230 - val_accuracy: 0.5714
Epoch 78/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5476 - accuracy: 0.5443 - val_loss: 5.4151 - val_accuracy: 0.5714
Epoch 79/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4309 - accuracy: 0.5650 - val_loss: 5.4074 - val_accuracy: 0.5714
Epoch 80/100
2/2 [==============================] - 0s 39ms/step - loss: 5.4804 - accuracy: 0.5711 - val_loss: 5.3995 - val_accuracy: 0.5714
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 5.4789 - accuracy: 0.5565 - val_loss: 5.3917 - val_accuracy: 0.5714
Epoch 82/100
2/2 [==============================] - 0s 46ms/step - loss: 5.4408 - accuracy: 0.5662 - val_loss: 5.3839 - val_accuracy: 0.5714
Epoch 83/100
2/2 [==============================] - 0s 50ms/step - loss: 5.4908 - accuracy: 0.5395 - val_loss: 5.3762 - val_accuracy: 0.5714
Epoch 84/100
2/2 [==============================] - 0s 47ms/step - loss: 5.4781 - accuracy: 0.5456 - val_loss: 5.3684 - val_accuracy: 0.5714
Epoch 85/100
2/2 [==============================] - 0s 34ms/step - loss: 5.4549 - accuracy: 0.5504 - val_loss: 5.3608 - val_accuracy: 0.5714
Epoch 86/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4685 - accuracy: 0.5443 - val_loss: 5.3532 - val_accuracy: 0.5714
Epoch 87/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4360 - accuracy: 0.5601 - val_loss: 5.3457 - val_accuracy: 0.5934
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4410 - accuracy: 0.5431 - val_loss: 5.3382 - val_accuracy: 0.5934
Epoch 89/100
2/2 [==============================] - 0s 39ms/step - loss: 5.4411 - accuracy: 0.5529 - val_loss: 5.3307 - val_accuracy: 0.5934
Epoch 90/100
2/2 [==============================] - 0s 30ms/step - loss: 5.4610 - accuracy: 0.5529 - val_loss: 5.3232 - val_accuracy: 0.5934
Epoch 91/100
2/2 [==============================] - 0s 25ms/step - loss: 5.3953 - accuracy: 0.5601 - val_loss: 5.3157 - val_accuracy: 0.6044
Epoch 92/100
2/2 [==============================] - 0s 33ms/step - loss: 5.4230 - accuracy: 0.5747 - val_loss: 5.3081 - val_accuracy: 0.6044
Epoch 93/100
2/2 [==============================] - 0s 36ms/step - loss: 5.3889 - accuracy: 0.5553 - val_loss: 5.3007 - val_accuracy: 0.6044
Epoch 94/100
2/2 [==============================] - 0s 29ms/step - loss: 5.4093 - accuracy: 0.5614 - val_loss: 5.2933 - val_accuracy: 0.6044
Epoch 95/100
2/2 [==============================] - 0s 32ms/step - loss: 5.4136 - accuracy: 0.5699 - val_loss: 5.2859 - val_accuracy: 0.6154
Epoch 96/100
2/2 [==============================] - 0s 36ms/step - loss: 5.3596 - accuracy: 0.5504 - val_loss: 5.2787 - val_accuracy: 0.6154
Epoch 97/100
2/2 [==============================] - 0s 24ms/step - loss: 5.3823 - accuracy: 0.5601 - val_loss: 5.2713 - val_accuracy: 0.6154
Epoch 98/100
2/2 [==============================] - 0s 29ms/step - loss: 5.3586 - accuracy: 0.5614 - val_loss: 5.2638 - val_accuracy: 0.6154
Epoch 99/100
2/2 [==============================] - 0s 34ms/step - loss: 5.3597 - accuracy: 0.5808 - val_loss: 5.2566 - val_accuracy: 0.6154
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3684 - accuracy: 0.5492 - val_loss: 5.2495 - val_accuracy: 0.6374
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 7ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 250ms/step - loss: 5.9386 - accuracy: 0.3609 - val_loss: 5.8519 - val_accuracy: 0.1868
Epoch 2/100
2/2 [==============================] - 0s 36ms/step - loss: 5.8558 - accuracy: 0.3694 - val_loss: 5.8456 - val_accuracy: 0.1868
Epoch 3/100
2/2 [==============================] - 0s 37ms/step - loss: 5.8639 - accuracy: 0.4010 - val_loss: 5.8384 - val_accuracy: 0.1758
Epoch 4/100
2/2 [==============================] - 0s 50ms/step - loss: 5.9202 - accuracy: 0.3694 - val_loss: 5.8304 - val_accuracy: 0.1758
Epoch 5/100
2/2 [==============================] - 0s 48ms/step - loss: 5.8737 - accuracy: 0.3803 - val_loss: 5.8219 - val_accuracy: 0.1758
Epoch 6/100
2/2 [==============================] - 0s 48ms/step - loss: 5.9413 - accuracy: 0.3597 - val_loss: 5.8128 - val_accuracy: 0.1758
Epoch 7/100
2/2 [==============================] - 0s 44ms/step - loss: 5.9117 - accuracy: 0.3609 - val_loss: 5.8035 - val_accuracy: 0.1868
Epoch 8/100
2/2 [==============================] - 0s 33ms/step - loss: 5.8769 - accuracy: 0.3803 - val_loss: 5.7940 - val_accuracy: 0.1868
Epoch 9/100
2/2 [==============================] - 0s 34ms/step - loss: 5.8564 - accuracy: 0.3864 - val_loss: 5.7839 - val_accuracy: 0.1868
Epoch 10/100
2/2 [==============================] - 0s 50ms/step - loss: 5.8715 - accuracy: 0.3876 - val_loss: 5.7737 - val_accuracy: 0.1868
Epoch 11/100
2/2 [==============================] - 0s 43ms/step - loss: 5.8498 - accuracy: 0.3827 - val_loss: 5.7636 - val_accuracy: 0.1978
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 5.8667 - accuracy: 0.3730 - val_loss: 5.7535 - val_accuracy: 0.1978
Epoch 13/100
2/2 [==============================] - 0s 34ms/step - loss: 5.8479 - accuracy: 0.4083 - val_loss: 5.7432 - val_accuracy: 0.1978
Epoch 14/100
2/2 [==============================] - 0s 34ms/step - loss: 5.8335 - accuracy: 0.3973 - val_loss: 5.7329 - val_accuracy: 0.2088
Epoch 15/100
2/2 [==============================] - 0s 35ms/step - loss: 5.8503 - accuracy: 0.3913 - val_loss: 5.7227 - val_accuracy: 0.2088
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7961 - accuracy: 0.4168 - val_loss: 5.7124 - val_accuracy: 0.2088
Epoch 17/100
2/2 [==============================] - 0s 48ms/step - loss: 5.8009 - accuracy: 0.3803 - val_loss: 5.7021 - val_accuracy: 0.2088
Epoch 18/100
2/2 [==============================] - 0s 47ms/step - loss: 5.7830 - accuracy: 0.4095 - val_loss: 5.6919 - val_accuracy: 0.2198
Epoch 19/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7904 - accuracy: 0.4156 - val_loss: 5.6817 - val_accuracy: 0.2198
Epoch 20/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7551 - accuracy: 0.4070 - val_loss: 5.6716 - val_accuracy: 0.2308
Epoch 21/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7587 - accuracy: 0.4131 - val_loss: 5.6614 - val_accuracy: 0.2418
Epoch 22/100
2/2 [==============================] - 0s 49ms/step - loss: 5.7646 - accuracy: 0.3913 - val_loss: 5.6515 - val_accuracy: 0.2527
Epoch 23/100
2/2 [==============================] - 0s 72ms/step - loss: 5.7545 - accuracy: 0.4265 - val_loss: 5.6415 - val_accuracy: 0.2637
Epoch 24/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7880 - accuracy: 0.3998 - val_loss: 5.6313 - val_accuracy: 0.2637
Epoch 25/100
2/2 [==============================] - 0s 35ms/step - loss: 5.7237 - accuracy: 0.4180 - val_loss: 5.6214 - val_accuracy: 0.2747
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 5.7512 - accuracy: 0.3973 - val_loss: 5.6113 - val_accuracy: 0.2747
Epoch 27/100
2/2 [==============================] - 0s 35ms/step - loss: 5.7186 - accuracy: 0.4204 - val_loss: 5.6014 - val_accuracy: 0.2857
Epoch 28/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7496 - accuracy: 0.3840 - val_loss: 5.5916 - val_accuracy: 0.2857
Epoch 29/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7062 - accuracy: 0.4204 - val_loss: 5.5820 - val_accuracy: 0.2967
Epoch 30/100
2/2 [==============================] - 0s 48ms/step - loss: 5.7042 - accuracy: 0.4095 - val_loss: 5.5724 - val_accuracy: 0.2967
Epoch 31/100
2/2 [==============================] - 0s 52ms/step - loss: 5.6863 - accuracy: 0.4046 - val_loss: 5.5628 - val_accuracy: 0.2967
Epoch 32/100
2/2 [==============================] - 0s 27ms/step - loss: 5.6698 - accuracy: 0.4216 - val_loss: 5.5533 - val_accuracy: 0.3187
Epoch 33/100
2/2 [==============================] - 0s 50ms/step - loss: 5.6477 - accuracy: 0.4228 - val_loss: 5.5438 - val_accuracy: 0.3297
Epoch 34/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6893 - accuracy: 0.4180 - val_loss: 5.5343 - val_accuracy: 0.3407
Epoch 35/100
2/2 [==============================] - 0s 49ms/step - loss: 5.6729 - accuracy: 0.4423 - val_loss: 5.5247 - val_accuracy: 0.3516
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6605 - accuracy: 0.4192 - val_loss: 5.5154 - val_accuracy: 0.3516
Epoch 37/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6177 - accuracy: 0.4156 - val_loss: 5.5061 - val_accuracy: 0.3516
Epoch 38/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6341 - accuracy: 0.4180 - val_loss: 5.4970 - val_accuracy: 0.3516
Epoch 39/100
2/2 [==============================] - 0s 52ms/step - loss: 5.6498 - accuracy: 0.4423 - val_loss: 5.4877 - val_accuracy: 0.3516
Epoch 40/100
2/2 [==============================] - 0s 35ms/step - loss: 5.6221 - accuracy: 0.4143 - val_loss: 5.4786 - val_accuracy: 0.3516
Epoch 41/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6367 - accuracy: 0.4143 - val_loss: 5.4695 - val_accuracy: 0.3516
Epoch 42/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6219 - accuracy: 0.4216 - val_loss: 5.4608 - val_accuracy: 0.3516
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6005 - accuracy: 0.4459 - val_loss: 5.4519 - val_accuracy: 0.3516
Epoch 44/100
2/2 [==============================] - 0s 49ms/step - loss: 5.5963 - accuracy: 0.4338 - val_loss: 5.4428 - val_accuracy: 0.3516
Epoch 45/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5704 - accuracy: 0.4253 - val_loss: 5.4340 - val_accuracy: 0.3516
Epoch 46/100
2/2 [==============================] - 0s 34ms/step - loss: 5.5899 - accuracy: 0.4447 - val_loss: 5.4254 - val_accuracy: 0.3626
Epoch 47/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5642 - accuracy: 0.4459 - val_loss: 5.4167 - val_accuracy: 0.3846
Epoch 48/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5654 - accuracy: 0.4435 - val_loss: 5.4079 - val_accuracy: 0.3956
Epoch 49/100
2/2 [==============================] - 0s 46ms/step - loss: 5.5278 - accuracy: 0.4508 - val_loss: 5.3994 - val_accuracy: 0.4066
Epoch 50/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5704 - accuracy: 0.4532 - val_loss: 5.3911 - val_accuracy: 0.4066
Epoch 51/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5850 - accuracy: 0.4423 - val_loss: 5.3826 - val_accuracy: 0.4176
Epoch 52/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5440 - accuracy: 0.4435 - val_loss: 5.3742 - val_accuracy: 0.4176
Epoch 53/100
2/2 [==============================] - 0s 46ms/step - loss: 5.5461 - accuracy: 0.4411 - val_loss: 5.3658 - val_accuracy: 0.4176
Epoch 54/100
2/2 [==============================] - 0s 41ms/step - loss: 5.5252 - accuracy: 0.4581 - val_loss: 5.3575 - val_accuracy: 0.4396
Epoch 55/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5166 - accuracy: 0.4411 - val_loss: 5.3491 - val_accuracy: 0.4505
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5086 - accuracy: 0.4471 - val_loss: 5.3409 - val_accuracy: 0.4615
Epoch 57/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5420 - accuracy: 0.4435 - val_loss: 5.3326 - val_accuracy: 0.4725
Epoch 58/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4778 - accuracy: 0.4411 - val_loss: 5.3241 - val_accuracy: 0.4725
Epoch 59/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5029 - accuracy: 0.4459 - val_loss: 5.3159 - val_accuracy: 0.4725
Epoch 60/100
2/2 [==============================] - 0s 34ms/step - loss: 5.4928 - accuracy: 0.4532 - val_loss: 5.3076 - val_accuracy: 0.4725
Epoch 61/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4495 - accuracy: 0.4787 - val_loss: 5.2996 - val_accuracy: 0.4725
Epoch 62/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4613 - accuracy: 0.4666 - val_loss: 5.2915 - val_accuracy: 0.4725
Epoch 63/100
2/2 [==============================] - 0s 27ms/step - loss: 5.4327 - accuracy: 0.4775 - val_loss: 5.2835 - val_accuracy: 0.4725
Epoch 64/100
2/2 [==============================] - 0s 33ms/step - loss: 5.4765 - accuracy: 0.4459 - val_loss: 5.2753 - val_accuracy: 0.4725
Epoch 65/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4973 - accuracy: 0.4423 - val_loss: 5.2673 - val_accuracy: 0.4725
Epoch 66/100
2/2 [==============================] - 0s 31ms/step - loss: 5.4630 - accuracy: 0.4532 - val_loss: 5.2594 - val_accuracy: 0.4725
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4262 - accuracy: 0.4544 - val_loss: 5.2514 - val_accuracy: 0.4725
Epoch 68/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4025 - accuracy: 0.4727 - val_loss: 5.2436 - val_accuracy: 0.4615
Epoch 69/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4549 - accuracy: 0.4508 - val_loss: 5.2356 - val_accuracy: 0.4615
Epoch 70/100
2/2 [==============================] - 0s 45ms/step - loss: 5.4007 - accuracy: 0.4702 - val_loss: 5.2279 - val_accuracy: 0.4615
Epoch 71/100
2/2 [==============================] - 0s 32ms/step - loss: 5.3767 - accuracy: 0.4800 - val_loss: 5.2203 - val_accuracy: 0.4615
Epoch 72/100
2/2 [==============================] - 0s 33ms/step - loss: 5.3693 - accuracy: 0.4860 - val_loss: 5.2126 - val_accuracy: 0.4615
Epoch 73/100
2/2 [==============================] - 0s 51ms/step - loss: 5.4023 - accuracy: 0.4727 - val_loss: 5.2049 - val_accuracy: 0.4615
Epoch 74/100
2/2 [==============================] - 0s 32ms/step - loss: 5.4006 - accuracy: 0.4666 - val_loss: 5.1974 - val_accuracy: 0.4725
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3765 - accuracy: 0.4763 - val_loss: 5.1898 - val_accuracy: 0.4725
Epoch 76/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3422 - accuracy: 0.4897 - val_loss: 5.1822 - val_accuracy: 0.4725
Epoch 77/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3526 - accuracy: 0.4666 - val_loss: 5.1747 - val_accuracy: 0.4725
Epoch 78/100
2/2 [==============================] - 0s 49ms/step - loss: 5.3562 - accuracy: 0.4812 - val_loss: 5.1672 - val_accuracy: 0.4835
Epoch 79/100
2/2 [==============================] - 0s 50ms/step - loss: 5.3785 - accuracy: 0.4739 - val_loss: 5.1598 - val_accuracy: 0.4835
Epoch 80/100
2/2 [==============================] - 0s 45ms/step - loss: 5.3919 - accuracy: 0.4824 - val_loss: 5.1523 - val_accuracy: 0.4835
Epoch 81/100
2/2 [==============================] - 0s 47ms/step - loss: 5.3284 - accuracy: 0.4848 - val_loss: 5.1448 - val_accuracy: 0.4835
Epoch 82/100
2/2 [==============================] - 0s 32ms/step - loss: 5.3015 - accuracy: 0.4848 - val_loss: 5.1372 - val_accuracy: 0.4945
Epoch 83/100
2/2 [==============================] - 0s 33ms/step - loss: 5.3263 - accuracy: 0.5006 - val_loss: 5.1300 - val_accuracy: 0.4945
Epoch 84/100
2/2 [==============================] - 0s 35ms/step - loss: 5.3298 - accuracy: 0.4836 - val_loss: 5.1224 - val_accuracy: 0.4945
Epoch 85/100
2/2 [==============================] - 0s 30ms/step - loss: 5.2617 - accuracy: 0.5128 - val_loss: 5.1150 - val_accuracy: 0.5055
Epoch 86/100
2/2 [==============================] - 0s 36ms/step - loss: 5.3228 - accuracy: 0.4897 - val_loss: 5.1080 - val_accuracy: 0.5055
Epoch 87/100
2/2 [==============================] - 0s 47ms/step - loss: 5.3089 - accuracy: 0.4933 - val_loss: 5.1006 - val_accuracy: 0.5055
Epoch 88/100
2/2 [==============================] - 0s 34ms/step - loss: 5.2785 - accuracy: 0.4970 - val_loss: 5.0935 - val_accuracy: 0.5055
Epoch 89/100
2/2 [==============================] - 0s 36ms/step - loss: 5.2744 - accuracy: 0.4945 - val_loss: 5.0863 - val_accuracy: 0.5055
Epoch 90/100
2/2 [==============================] - 0s 33ms/step - loss: 5.2362 - accuracy: 0.5091 - val_loss: 5.0792 - val_accuracy: 0.5055
Epoch 91/100
2/2 [==============================] - 0s 34ms/step - loss: 5.3034 - accuracy: 0.4775 - val_loss: 5.0719 - val_accuracy: 0.5055
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 5.2532 - accuracy: 0.4933 - val_loss: 5.0647 - val_accuracy: 0.5055
Epoch 93/100
2/2 [==============================] - 0s 35ms/step - loss: 5.2747 - accuracy: 0.5043 - val_loss: 5.0575 - val_accuracy: 0.5055
Epoch 94/100
2/2 [==============================] - 0s 36ms/step - loss: 5.2817 - accuracy: 0.5164 - val_loss: 5.0505 - val_accuracy: 0.5165
Epoch 95/100
2/2 [==============================] - 0s 32ms/step - loss: 5.2198 - accuracy: 0.5006 - val_loss: 5.0434 - val_accuracy: 0.5275
Epoch 96/100
2/2 [==============================] - 0s 49ms/step - loss: 5.2501 - accuracy: 0.4994 - val_loss: 5.0361 - val_accuracy: 0.5385
Epoch 97/100
2/2 [==============================] - 0s 66ms/step - loss: 5.2404 - accuracy: 0.4909 - val_loss: 5.0291 - val_accuracy: 0.5385
Epoch 98/100
2/2 [==============================] - 0s 66ms/step - loss: 5.2272 - accuracy: 0.5055 - val_loss: 5.0221 - val_accuracy: 0.5385
Epoch 99/100
2/2 [==============================] - 0s 39ms/step - loss: 5.2343 - accuracy: 0.5164 - val_loss: 5.0151 - val_accuracy: 0.5385
Epoch 100/100
2/2 [==============================] - 0s 42ms/step - loss: 5.2383 - accuracy: 0.4994 - val_loss: 5.0082 - val_accuracy: 0.5385
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 7ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 249ms/step - loss: 6.3536 - accuracy: 0.2697 - val_loss: 5.0395 - val_accuracy: 0.6813
Epoch 2/100
2/2 [==============================] - 0s 36ms/step - loss: 6.3442 - accuracy: 0.2697 - val_loss: 5.0449 - val_accuracy: 0.6703
Epoch 3/100
2/2 [==============================] - 0s 35ms/step - loss: 6.3234 - accuracy: 0.2880 - val_loss: 5.0497 - val_accuracy: 0.6593
Epoch 4/100
2/2 [==============================] - 0s 52ms/step - loss: 6.3295 - accuracy: 0.2722 - val_loss: 5.0538 - val_accuracy: 0.6374
Epoch 5/100
2/2 [==============================] - 0s 49ms/step - loss: 6.3477 - accuracy: 0.2625 - val_loss: 5.0574 - val_accuracy: 0.6374
Epoch 6/100
2/2 [==============================] - 0s 47ms/step - loss: 6.3152 - accuracy: 0.2722 - val_loss: 5.0605 - val_accuracy: 0.6374
Epoch 7/100
2/2 [==============================] - 0s 35ms/step - loss: 6.2859 - accuracy: 0.2734 - val_loss: 5.0633 - val_accuracy: 0.6374
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 6.3065 - accuracy: 0.2904 - val_loss: 5.0661 - val_accuracy: 0.6374
Epoch 9/100
2/2 [==============================] - 0s 36ms/step - loss: 6.3118 - accuracy: 0.2625 - val_loss: 5.0684 - val_accuracy: 0.6374
Epoch 10/100
2/2 [==============================] - 0s 36ms/step - loss: 6.2724 - accuracy: 0.2843 - val_loss: 5.0705 - val_accuracy: 0.6374
Epoch 11/100
2/2 [==============================] - 0s 38ms/step - loss: 6.2850 - accuracy: 0.2746 - val_loss: 5.0725 - val_accuracy: 0.6264
Epoch 12/100
2/2 [==============================] - 0s 49ms/step - loss: 6.2754 - accuracy: 0.2661 - val_loss: 5.0743 - val_accuracy: 0.6374
Epoch 13/100
2/2 [==============================] - 0s 49ms/step - loss: 6.2828 - accuracy: 0.2783 - val_loss: 5.0760 - val_accuracy: 0.6374
Epoch 14/100
2/2 [==============================] - 0s 46ms/step - loss: 6.2442 - accuracy: 0.2831 - val_loss: 5.0774 - val_accuracy: 0.6374
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 6.2307 - accuracy: 0.2831 - val_loss: 5.0787 - val_accuracy: 0.6374
Epoch 16/100
2/2 [==============================] - 0s 28ms/step - loss: 6.2254 - accuracy: 0.2710 - val_loss: 5.0801 - val_accuracy: 0.6374
Epoch 17/100
2/2 [==============================] - 0s 33ms/step - loss: 6.2292 - accuracy: 0.2807 - val_loss: 5.0812 - val_accuracy: 0.6264
Epoch 18/100
2/2 [==============================] - 0s 34ms/step - loss: 6.2327 - accuracy: 0.2758 - val_loss: 5.0825 - val_accuracy: 0.6264
Epoch 19/100
2/2 [==============================] - 0s 36ms/step - loss: 6.1698 - accuracy: 0.2783 - val_loss: 5.0837 - val_accuracy: 0.6154
Epoch 20/100
2/2 [==============================] - 0s 50ms/step - loss: 6.1823 - accuracy: 0.2892 - val_loss: 5.0846 - val_accuracy: 0.6154
Epoch 21/100
2/2 [==============================] - 0s 50ms/step - loss: 6.2132 - accuracy: 0.2746 - val_loss: 5.0856 - val_accuracy: 0.6044
Epoch 22/100
2/2 [==============================] - 0s 35ms/step - loss: 6.1621 - accuracy: 0.2928 - val_loss: 5.0866 - val_accuracy: 0.6044
Epoch 23/100
2/2 [==============================] - 0s 34ms/step - loss: 6.1676 - accuracy: 0.2831 - val_loss: 5.0876 - val_accuracy: 0.5934
Epoch 24/100
2/2 [==============================] - 0s 48ms/step - loss: 6.1526 - accuracy: 0.2904 - val_loss: 5.0884 - val_accuracy: 0.5934
Epoch 25/100
2/2 [==============================] - 0s 34ms/step - loss: 6.1341 - accuracy: 0.2940 - val_loss: 5.0891 - val_accuracy: 0.5934
Epoch 26/100
2/2 [==============================] - 0s 33ms/step - loss: 6.1179 - accuracy: 0.2770 - val_loss: 5.0897 - val_accuracy: 0.5934
Epoch 27/100
2/2 [==============================] - 0s 48ms/step - loss: 6.1692 - accuracy: 0.2940 - val_loss: 5.0902 - val_accuracy: 0.5934
Epoch 28/100
2/2 [==============================] - 0s 47ms/step - loss: 6.1061 - accuracy: 0.2819 - val_loss: 5.0907 - val_accuracy: 0.5934
Epoch 29/100
2/2 [==============================] - 0s 33ms/step - loss: 6.1278 - accuracy: 0.2989 - val_loss: 5.0912 - val_accuracy: 0.5934
Epoch 30/100
2/2 [==============================] - 0s 45ms/step - loss: 6.1187 - accuracy: 0.2795 - val_loss: 5.0916 - val_accuracy: 0.5824
Epoch 31/100
2/2 [==============================] - 0s 33ms/step - loss: 6.1033 - accuracy: 0.2904 - val_loss: 5.0920 - val_accuracy: 0.5714
Epoch 32/100
2/2 [==============================] - 0s 34ms/step - loss: 6.0713 - accuracy: 0.2868 - val_loss: 5.0922 - val_accuracy: 0.5714
Epoch 33/100
2/2 [==============================] - 0s 33ms/step - loss: 6.1179 - accuracy: 0.2770 - val_loss: 5.0922 - val_accuracy: 0.5714
Epoch 34/100
2/2 [==============================] - 0s 31ms/step - loss: 6.0978 - accuracy: 0.2673 - val_loss: 5.0925 - val_accuracy: 0.5604
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 6.0825 - accuracy: 0.2697 - val_loss: 5.0923 - val_accuracy: 0.5604
Epoch 36/100
2/2 [==============================] - 0s 46ms/step - loss: 6.0408 - accuracy: 0.3026 - val_loss: 5.0923 - val_accuracy: 0.5495
Epoch 37/100
2/2 [==============================] - 0s 50ms/step - loss: 6.0522 - accuracy: 0.2928 - val_loss: 5.0921 - val_accuracy: 0.5495
Epoch 38/100
2/2 [==============================] - 0s 48ms/step - loss: 5.9660 - accuracy: 0.3159 - val_loss: 5.0920 - val_accuracy: 0.5495
Epoch 39/100
2/2 [==============================] - 0s 36ms/step - loss: 6.0097 - accuracy: 0.2977 - val_loss: 5.0920 - val_accuracy: 0.5495
Epoch 40/100
2/2 [==============================] - 0s 41ms/step - loss: 6.0306 - accuracy: 0.2843 - val_loss: 5.0916 - val_accuracy: 0.5385
Epoch 41/100
2/2 [==============================] - 0s 33ms/step - loss: 5.9772 - accuracy: 0.3111 - val_loss: 5.0913 - val_accuracy: 0.5385
Epoch 42/100
2/2 [==============================] - 0s 35ms/step - loss: 5.9689 - accuracy: 0.3026 - val_loss: 5.0908 - val_accuracy: 0.5385
Epoch 43/100
2/2 [==============================] - 0s 36ms/step - loss: 5.9934 - accuracy: 0.2953 - val_loss: 5.0904 - val_accuracy: 0.5385
Epoch 44/100
2/2 [==============================] - 0s 49ms/step - loss: 5.9547 - accuracy: 0.2989 - val_loss: 5.0898 - val_accuracy: 0.5385
Epoch 45/100
2/2 [==============================] - 0s 52ms/step - loss: 5.9484 - accuracy: 0.3171 - val_loss: 5.0893 - val_accuracy: 0.5385
Epoch 46/100
2/2 [==============================] - 0s 41ms/step - loss: 5.9408 - accuracy: 0.3013 - val_loss: 5.0887 - val_accuracy: 0.5385
Epoch 47/100
2/2 [==============================] - 0s 31ms/step - loss: 5.9498 - accuracy: 0.2977 - val_loss: 5.0880 - val_accuracy: 0.5385
Epoch 48/100
2/2 [==============================] - 0s 33ms/step - loss: 5.9288 - accuracy: 0.3026 - val_loss: 5.0873 - val_accuracy: 0.5385
Epoch 49/100
2/2 [==============================] - 0s 34ms/step - loss: 5.9191 - accuracy: 0.3050 - val_loss: 5.0861 - val_accuracy: 0.5385
Epoch 50/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9409 - accuracy: 0.3050 - val_loss: 5.0852 - val_accuracy: 0.5385
Epoch 51/100
2/2 [==============================] - 0s 37ms/step - loss: 5.9105 - accuracy: 0.2953 - val_loss: 5.0841 - val_accuracy: 0.5385
Epoch 52/100
2/2 [==============================] - 0s 49ms/step - loss: 5.8975 - accuracy: 0.3147 - val_loss: 5.0831 - val_accuracy: 0.5385
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 5.8841 - accuracy: 0.3196 - val_loss: 5.0820 - val_accuracy: 0.5385
Epoch 54/100
2/2 [==============================] - 0s 35ms/step - loss: 5.8982 - accuracy: 0.3013 - val_loss: 5.0809 - val_accuracy: 0.5385
Epoch 55/100
2/2 [==============================] - 0s 36ms/step - loss: 5.9037 - accuracy: 0.3001 - val_loss: 5.0797 - val_accuracy: 0.5385
Epoch 56/100
2/2 [==============================] - 0s 48ms/step - loss: 5.8828 - accuracy: 0.2880 - val_loss: 5.0785 - val_accuracy: 0.5495
Epoch 57/100
2/2 [==============================] - 0s 42ms/step - loss: 5.8067 - accuracy: 0.3293 - val_loss: 5.0771 - val_accuracy: 0.5385
Epoch 58/100
2/2 [==============================] - 0s 44ms/step - loss: 5.8517 - accuracy: 0.3171 - val_loss: 5.0757 - val_accuracy: 0.5385
Epoch 59/100
2/2 [==============================] - 0s 31ms/step - loss: 5.8552 - accuracy: 0.2965 - val_loss: 5.0743 - val_accuracy: 0.5275
Epoch 60/100
2/2 [==============================] - 0s 33ms/step - loss: 5.8118 - accuracy: 0.3220 - val_loss: 5.0730 - val_accuracy: 0.5275
Epoch 61/100
2/2 [==============================] - 0s 36ms/step - loss: 5.8217 - accuracy: 0.3038 - val_loss: 5.0714 - val_accuracy: 0.5275
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 5.8269 - accuracy: 0.3123 - val_loss: 5.0700 - val_accuracy: 0.5275
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 5.8272 - accuracy: 0.2904 - val_loss: 5.0682 - val_accuracy: 0.5165
Epoch 64/100
2/2 [==============================] - 0s 48ms/step - loss: 5.7783 - accuracy: 0.3026 - val_loss: 5.0665 - val_accuracy: 0.5055
Epoch 65/100
2/2 [==============================] - 0s 47ms/step - loss: 5.8034 - accuracy: 0.3123 - val_loss: 5.0648 - val_accuracy: 0.5055
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7372 - accuracy: 0.3098 - val_loss: 5.0628 - val_accuracy: 0.5055
Epoch 67/100
2/2 [==============================] - 0s 42ms/step - loss: 5.7785 - accuracy: 0.3171 - val_loss: 5.0609 - val_accuracy: 0.5055
Epoch 68/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7730 - accuracy: 0.3220 - val_loss: 5.0590 - val_accuracy: 0.5055
Epoch 69/100
2/2 [==============================] - 0s 35ms/step - loss: 5.7982 - accuracy: 0.3208 - val_loss: 5.0571 - val_accuracy: 0.5055
Epoch 70/100
2/2 [==============================] - 0s 51ms/step - loss: 5.7377 - accuracy: 0.3026 - val_loss: 5.0549 - val_accuracy: 0.5055
Epoch 71/100
2/2 [==============================] - 0s 51ms/step - loss: 5.7095 - accuracy: 0.3208 - val_loss: 5.0530 - val_accuracy: 0.5055
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 5.7253 - accuracy: 0.3341 - val_loss: 5.0508 - val_accuracy: 0.5055
Epoch 73/100
2/2 [==============================] - 0s 30ms/step - loss: 5.7043 - accuracy: 0.3390 - val_loss: 5.0487 - val_accuracy: 0.5055
Epoch 74/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6984 - accuracy: 0.3135 - val_loss: 5.0462 - val_accuracy: 0.5055
Epoch 75/100
2/2 [==============================] - 0s 32ms/step - loss: 5.7148 - accuracy: 0.3208 - val_loss: 5.0440 - val_accuracy: 0.5055
Epoch 76/100
2/2 [==============================] - 0s 52ms/step - loss: 5.7227 - accuracy: 0.3135 - val_loss: 5.0417 - val_accuracy: 0.5055
Epoch 77/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6955 - accuracy: 0.3269 - val_loss: 5.0394 - val_accuracy: 0.5055
Epoch 78/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6662 - accuracy: 0.3098 - val_loss: 5.0367 - val_accuracy: 0.5055
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6341 - accuracy: 0.3232 - val_loss: 5.0342 - val_accuracy: 0.5055
Epoch 80/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6855 - accuracy: 0.3171 - val_loss: 5.0317 - val_accuracy: 0.5055
Epoch 81/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6639 - accuracy: 0.3281 - val_loss: 5.0291 - val_accuracy: 0.5055
Epoch 82/100
2/2 [==============================] - 0s 43ms/step - loss: 5.6116 - accuracy: 0.3378 - val_loss: 5.0263 - val_accuracy: 0.4945
Epoch 83/100
2/2 [==============================] - 0s 45ms/step - loss: 5.6431 - accuracy: 0.3171 - val_loss: 5.0237 - val_accuracy: 0.4945
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6358 - accuracy: 0.3098 - val_loss: 5.0208 - val_accuracy: 0.4945
Epoch 85/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6161 - accuracy: 0.3329 - val_loss: 5.0179 - val_accuracy: 0.4945
Epoch 86/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6192 - accuracy: 0.3244 - val_loss: 5.0149 - val_accuracy: 0.4945
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6217 - accuracy: 0.3159 - val_loss: 5.0119 - val_accuracy: 0.4945
Epoch 88/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5881 - accuracy: 0.3305 - val_loss: 5.0087 - val_accuracy: 0.4945
Epoch 89/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5919 - accuracy: 0.3354 - val_loss: 5.0054 - val_accuracy: 0.4945
Epoch 90/100
2/2 [==============================] - 0s 40ms/step - loss: 5.5723 - accuracy: 0.3135 - val_loss: 5.0024 - val_accuracy: 0.4945
Epoch 91/100
2/2 [==============================] - 0s 45ms/step - loss: 5.5612 - accuracy: 0.3341 - val_loss: 4.9992 - val_accuracy: 0.4945
Epoch 92/100
2/2 [==============================] - 0s 34ms/step - loss: 5.5646 - accuracy: 0.3487 - val_loss: 4.9961 - val_accuracy: 0.4945
Epoch 93/100
2/2 [==============================] - 0s 41ms/step - loss: 5.5750 - accuracy: 0.3281 - val_loss: 4.9930 - val_accuracy: 0.4945
Epoch 94/100
2/2 [==============================] - 0s 40ms/step - loss: 5.5183 - accuracy: 0.3524 - val_loss: 4.9897 - val_accuracy: 0.4945
Epoch 95/100
2/2 [==============================] - 0s 41ms/step - loss: 5.5131 - accuracy: 0.3414 - val_loss: 4.9865 - val_accuracy: 0.4945
Epoch 96/100
2/2 [==============================] - 0s 42ms/step - loss: 5.5031 - accuracy: 0.3451 - val_loss: 4.9832 - val_accuracy: 0.4945
Epoch 97/100
2/2 [==============================] - 0s 40ms/step - loss: 5.5050 - accuracy: 0.3317 - val_loss: 4.9800 - val_accuracy: 0.4945
Epoch 98/100
2/2 [==============================] - 0s 39ms/step - loss: 5.4998 - accuracy: 0.3390 - val_loss: 4.9768 - val_accuracy: 0.4945
Epoch 99/100
2/2 [==============================] - 0s 41ms/step - loss: 5.4997 - accuracy: 0.3366 - val_loss: 4.9731 - val_accuracy: 0.4945
Epoch 100/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5352 - accuracy: 0.3341 - val_loss: 4.9697 - val_accuracy: 0.4945
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 251ms/step - loss: 6.2403 - accuracy: 0.3038 - val_loss: 5.4637 - val_accuracy: 0.4835
Epoch 2/100
2/2 [==============================] - 0s 48ms/step - loss: 6.2146 - accuracy: 0.3013 - val_loss: 5.4707 - val_accuracy: 0.4615
Epoch 3/100
2/2 [==============================] - 0s 40ms/step - loss: 6.2840 - accuracy: 0.2916 - val_loss: 5.4769 - val_accuracy: 0.4505
Epoch 4/100
2/2 [==============================] - 0s 41ms/step - loss: 6.2002 - accuracy: 0.3001 - val_loss: 5.4819 - val_accuracy: 0.4396
Epoch 5/100
2/2 [==============================] - 0s 37ms/step - loss: 6.2097 - accuracy: 0.3098 - val_loss: 5.4866 - val_accuracy: 0.4176
Epoch 6/100
2/2 [==============================] - 0s 35ms/step - loss: 6.2045 - accuracy: 0.2965 - val_loss: 5.4907 - val_accuracy: 0.4176
Epoch 7/100
2/2 [==============================] - 0s 39ms/step - loss: 6.2181 - accuracy: 0.2855 - val_loss: 5.4944 - val_accuracy: 0.4176
Epoch 8/100
2/2 [==============================] - 0s 39ms/step - loss: 6.1464 - accuracy: 0.2940 - val_loss: 5.4979 - val_accuracy: 0.4066
Epoch 9/100
2/2 [==============================] - 0s 38ms/step - loss: 6.1748 - accuracy: 0.2977 - val_loss: 5.5011 - val_accuracy: 0.4066
Epoch 10/100
2/2 [==============================] - 0s 40ms/step - loss: 6.1723 - accuracy: 0.2953 - val_loss: 5.5038 - val_accuracy: 0.3846
Epoch 11/100
2/2 [==============================] - 0s 43ms/step - loss: 6.1573 - accuracy: 0.3123 - val_loss: 5.5064 - val_accuracy: 0.3846
Epoch 12/100
2/2 [==============================] - 0s 40ms/step - loss: 6.1407 - accuracy: 0.2928 - val_loss: 5.5087 - val_accuracy: 0.3846
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 6.1753 - accuracy: 0.3098 - val_loss: 5.5105 - val_accuracy: 0.3846
Epoch 14/100
2/2 [==============================] - 0s 28ms/step - loss: 6.1782 - accuracy: 0.2928 - val_loss: 5.5123 - val_accuracy: 0.3846
Epoch 15/100
2/2 [==============================] - 0s 36ms/step - loss: 6.1112 - accuracy: 0.3098 - val_loss: 5.5141 - val_accuracy: 0.3846
Epoch 16/100
2/2 [==============================] - 0s 35ms/step - loss: 6.1636 - accuracy: 0.3074 - val_loss: 5.5158 - val_accuracy: 0.3846
Epoch 17/100
2/2 [==============================] - 0s 41ms/step - loss: 6.1325 - accuracy: 0.3038 - val_loss: 5.5172 - val_accuracy: 0.3846
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 6.1153 - accuracy: 0.3026 - val_loss: 5.5185 - val_accuracy: 0.3736
Epoch 19/100
2/2 [==============================] - 0s 41ms/step - loss: 6.1125 - accuracy: 0.3086 - val_loss: 5.5197 - val_accuracy: 0.3736
Epoch 20/100
2/2 [==============================] - 0s 41ms/step - loss: 6.0573 - accuracy: 0.2928 - val_loss: 5.5207 - val_accuracy: 0.3736
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 6.0705 - accuracy: 0.3159 - val_loss: 5.5218 - val_accuracy: 0.3736
Epoch 22/100
2/2 [==============================] - 0s 38ms/step - loss: 6.0236 - accuracy: 0.3196 - val_loss: 5.5228 - val_accuracy: 0.3736
Epoch 23/100
2/2 [==============================] - 0s 39ms/step - loss: 6.0534 - accuracy: 0.3244 - val_loss: 5.5237 - val_accuracy: 0.3736
Epoch 24/100
2/2 [==============================] - 0s 28ms/step - loss: 6.0284 - accuracy: 0.3135 - val_loss: 5.5246 - val_accuracy: 0.3736
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 6.0215 - accuracy: 0.3098 - val_loss: 5.5252 - val_accuracy: 0.3736
Epoch 26/100
2/2 [==============================] - 0s 38ms/step - loss: 5.9736 - accuracy: 0.3256 - val_loss: 5.5256 - val_accuracy: 0.3626
Epoch 27/100
2/2 [==============================] - 0s 36ms/step - loss: 6.0317 - accuracy: 0.3123 - val_loss: 5.5258 - val_accuracy: 0.3626
Epoch 28/100
2/2 [==============================] - 0s 53ms/step - loss: 6.0175 - accuracy: 0.3074 - val_loss: 5.5260 - val_accuracy: 0.3626
Epoch 29/100
2/2 [==============================] - 0s 39ms/step - loss: 6.0166 - accuracy: 0.3062 - val_loss: 5.5260 - val_accuracy: 0.3626
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9868 - accuracy: 0.3098 - val_loss: 5.5259 - val_accuracy: 0.3516
Epoch 31/100
2/2 [==============================] - 0s 40ms/step - loss: 5.9795 - accuracy: 0.3026 - val_loss: 5.5260 - val_accuracy: 0.3516
Epoch 32/100
2/2 [==============================] - 0s 37ms/step - loss: 5.9680 - accuracy: 0.3196 - val_loss: 5.5260 - val_accuracy: 0.3516
Epoch 33/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9761 - accuracy: 0.3329 - val_loss: 5.5263 - val_accuracy: 0.3516
Epoch 34/100
2/2 [==============================] - 0s 73ms/step - loss: 5.9490 - accuracy: 0.3269 - val_loss: 5.5260 - val_accuracy: 0.3516
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9273 - accuracy: 0.3281 - val_loss: 5.5256 - val_accuracy: 0.3516
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 5.8931 - accuracy: 0.3208 - val_loss: 5.5253 - val_accuracy: 0.3516
Epoch 37/100
2/2 [==============================] - 0s 51ms/step - loss: 5.8992 - accuracy: 0.3451 - val_loss: 5.5246 - val_accuracy: 0.3516
Epoch 38/100
2/2 [==============================] - 0s 26ms/step - loss: 5.9128 - accuracy: 0.3317 - val_loss: 5.5241 - val_accuracy: 0.3516
Epoch 39/100
2/2 [==============================] - 0s 42ms/step - loss: 5.8704 - accuracy: 0.3341 - val_loss: 5.5238 - val_accuracy: 0.3516
Epoch 40/100
2/2 [==============================] - 0s 39ms/step - loss: 5.8545 - accuracy: 0.3305 - val_loss: 5.5231 - val_accuracy: 0.3516
Epoch 41/100
2/2 [==============================] - 0s 47ms/step - loss: 5.8578 - accuracy: 0.3147 - val_loss: 5.5221 - val_accuracy: 0.3516
Epoch 42/100
2/2 [==============================] - 0s 43ms/step - loss: 5.8131 - accuracy: 0.3305 - val_loss: 5.5214 - val_accuracy: 0.3516
Epoch 43/100
2/2 [==============================] - 0s 41ms/step - loss: 5.8391 - accuracy: 0.3281 - val_loss: 5.5203 - val_accuracy: 0.3516
Epoch 44/100
2/2 [==============================] - 0s 41ms/step - loss: 5.8971 - accuracy: 0.3317 - val_loss: 5.5194 - val_accuracy: 0.3516
Epoch 45/100
2/2 [==============================] - 0s 31ms/step - loss: 5.8441 - accuracy: 0.3220 - val_loss: 5.5183 - val_accuracy: 0.3516
Epoch 46/100
2/2 [==============================] - 0s 37ms/step - loss: 5.8504 - accuracy: 0.3244 - val_loss: 5.5169 - val_accuracy: 0.3516
Epoch 47/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8235 - accuracy: 0.3341 - val_loss: 5.5154 - val_accuracy: 0.3516
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 5.8234 - accuracy: 0.3378 - val_loss: 5.5140 - val_accuracy: 0.3516
Epoch 49/100
2/2 [==============================] - 0s 26ms/step - loss: 5.8160 - accuracy: 0.3366 - val_loss: 5.5126 - val_accuracy: 0.3516
Epoch 50/100
2/2 [==============================] - 0s 43ms/step - loss: 5.7494 - accuracy: 0.3402 - val_loss: 5.5110 - val_accuracy: 0.3516
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7797 - accuracy: 0.3341 - val_loss: 5.5095 - val_accuracy: 0.3516
Epoch 52/100
2/2 [==============================] - 0s 27ms/step - loss: 5.7531 - accuracy: 0.3341 - val_loss: 5.5077 - val_accuracy: 0.3516
Epoch 53/100
2/2 [==============================] - 0s 41ms/step - loss: 5.7165 - accuracy: 0.3402 - val_loss: 5.5060 - val_accuracy: 0.3516
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7409 - accuracy: 0.3512 - val_loss: 5.5043 - val_accuracy: 0.3516
Epoch 55/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7238 - accuracy: 0.3232 - val_loss: 5.5025 - val_accuracy: 0.3516
Epoch 56/100
2/2 [==============================] - 0s 41ms/step - loss: 5.7607 - accuracy: 0.3475 - val_loss: 5.5006 - val_accuracy: 0.3516
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 5.7152 - accuracy: 0.3475 - val_loss: 5.4985 - val_accuracy: 0.3516
Epoch 58/100
2/2 [==============================] - 0s 27ms/step - loss: 5.7126 - accuracy: 0.3378 - val_loss: 5.4963 - val_accuracy: 0.3516
Epoch 59/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6943 - accuracy: 0.3499 - val_loss: 5.4940 - val_accuracy: 0.3516
Epoch 60/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7058 - accuracy: 0.3524 - val_loss: 5.4918 - val_accuracy: 0.3516
Epoch 61/100
2/2 [==============================] - 0s 40ms/step - loss: 5.6728 - accuracy: 0.3499 - val_loss: 5.4893 - val_accuracy: 0.3516
Epoch 62/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6986 - accuracy: 0.3718 - val_loss: 5.4869 - val_accuracy: 0.3516
Epoch 63/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7029 - accuracy: 0.3536 - val_loss: 5.4845 - val_accuracy: 0.3516
Epoch 64/100
2/2 [==============================] - 0s 29ms/step - loss: 5.6384 - accuracy: 0.3609 - val_loss: 5.4819 - val_accuracy: 0.3407
Epoch 65/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6816 - accuracy: 0.3305 - val_loss: 5.4792 - val_accuracy: 0.3407
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6351 - accuracy: 0.3402 - val_loss: 5.4766 - val_accuracy: 0.3407
Epoch 67/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6389 - accuracy: 0.3548 - val_loss: 5.4737 - val_accuracy: 0.3407
Epoch 68/100
2/2 [==============================] - 0s 40ms/step - loss: 5.6689 - accuracy: 0.3475 - val_loss: 5.4709 - val_accuracy: 0.3407
Epoch 69/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5952 - accuracy: 0.3584 - val_loss: 5.4682 - val_accuracy: 0.3407
Epoch 70/100
2/2 [==============================] - 0s 30ms/step - loss: 5.6421 - accuracy: 0.3439 - val_loss: 5.4653 - val_accuracy: 0.3407
Epoch 71/100
2/2 [==============================] - 0s 40ms/step - loss: 5.5990 - accuracy: 0.3609 - val_loss: 5.4625 - val_accuracy: 0.3516
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 5.6033 - accuracy: 0.3597 - val_loss: 5.4594 - val_accuracy: 0.3516
Epoch 73/100
2/2 [==============================] - 0s 42ms/step - loss: 5.5986 - accuracy: 0.3597 - val_loss: 5.4562 - val_accuracy: 0.3516
Epoch 74/100
2/2 [==============================] - 0s 43ms/step - loss: 5.5870 - accuracy: 0.3706 - val_loss: 5.4530 - val_accuracy: 0.3516
Epoch 75/100
2/2 [==============================] - 0s 41ms/step - loss: 5.5872 - accuracy: 0.3536 - val_loss: 5.4497 - val_accuracy: 0.3516
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6009 - accuracy: 0.3414 - val_loss: 5.4463 - val_accuracy: 0.3516
Epoch 77/100
2/2 [==============================] - 0s 41ms/step - loss: 5.5400 - accuracy: 0.3378 - val_loss: 5.4430 - val_accuracy: 0.3516
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5376 - accuracy: 0.3657 - val_loss: 5.4397 - val_accuracy: 0.3516
Epoch 79/100
2/2 [==============================] - 0s 50ms/step - loss: 5.5417 - accuracy: 0.3609 - val_loss: 5.4362 - val_accuracy: 0.3516
Epoch 80/100
2/2 [==============================] - 0s 50ms/step - loss: 5.4965 - accuracy: 0.3742 - val_loss: 5.4325 - val_accuracy: 0.3516
Epoch 81/100
2/2 [==============================] - 0s 27ms/step - loss: 5.5184 - accuracy: 0.3499 - val_loss: 5.4288 - val_accuracy: 0.3516
Epoch 82/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5352 - accuracy: 0.3682 - val_loss: 5.4250 - val_accuracy: 0.3516
Epoch 83/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4824 - accuracy: 0.3670 - val_loss: 5.4212 - val_accuracy: 0.3516
Epoch 84/100
2/2 [==============================] - 0s 26ms/step - loss: 5.4663 - accuracy: 0.3742 - val_loss: 5.4175 - val_accuracy: 0.3516
Epoch 85/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5125 - accuracy: 0.3354 - val_loss: 5.4137 - val_accuracy: 0.3516
Epoch 86/100
2/2 [==============================] - 0s 42ms/step - loss: 5.4629 - accuracy: 0.3742 - val_loss: 5.4098 - val_accuracy: 0.3516
Epoch 87/100
2/2 [==============================] - 0s 40ms/step - loss: 5.4798 - accuracy: 0.3767 - val_loss: 5.4061 - val_accuracy: 0.3516
Epoch 88/100
2/2 [==============================] - 0s 43ms/step - loss: 5.4801 - accuracy: 0.3767 - val_loss: 5.4023 - val_accuracy: 0.3516
Epoch 89/100
2/2 [==============================] - 0s 33ms/step - loss: 5.4210 - accuracy: 0.3937 - val_loss: 5.3981 - val_accuracy: 0.3516
Epoch 90/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4452 - accuracy: 0.3670 - val_loss: 5.3941 - val_accuracy: 0.3516
Epoch 91/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4424 - accuracy: 0.3925 - val_loss: 5.3899 - val_accuracy: 0.3626
Epoch 92/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4609 - accuracy: 0.3645 - val_loss: 5.3856 - val_accuracy: 0.3626
Epoch 93/100
2/2 [==============================] - 0s 38ms/step - loss: 5.3935 - accuracy: 0.3888 - val_loss: 5.3814 - val_accuracy: 0.3626
Epoch 94/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4001 - accuracy: 0.3900 - val_loss: 5.3773 - val_accuracy: 0.3626
Epoch 95/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4182 - accuracy: 0.3913 - val_loss: 5.3730 - val_accuracy: 0.3626
Epoch 96/100
2/2 [==============================] - 0s 33ms/step - loss: 5.3999 - accuracy: 0.3718 - val_loss: 5.3685 - val_accuracy: 0.3626
Epoch 97/100
2/2 [==============================] - 0s 41ms/step - loss: 5.3878 - accuracy: 0.3876 - val_loss: 5.3641 - val_accuracy: 0.3626
Epoch 98/100
2/2 [==============================] - 0s 35ms/step - loss: 5.3634 - accuracy: 0.4156 - val_loss: 5.3597 - val_accuracy: 0.3626
Epoch 99/100
2/2 [==============================] - 0s 46ms/step - loss: 5.3863 - accuracy: 0.3998 - val_loss: 5.3555 - val_accuracy: 0.3626
Epoch 100/100
2/2 [==============================] - 0s 29ms/step - loss: 5.3648 - accuracy: 0.3973 - val_loss: 5.3511 - val_accuracy: 0.3626
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 9ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 242ms/step - loss: 6.0547 - accuracy: 0.2916 - val_loss: 5.3942 - val_accuracy: 0.5934
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 6.0652 - accuracy: 0.3098 - val_loss: 5.3985 - val_accuracy: 0.5824
Epoch 3/100
2/2 [==============================] - 0s 38ms/step - loss: 6.0461 - accuracy: 0.3026 - val_loss: 5.4017 - val_accuracy: 0.5824
Epoch 4/100
2/2 [==============================] - 0s 41ms/step - loss: 6.0296 - accuracy: 0.2989 - val_loss: 5.4043 - val_accuracy: 0.5604
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 6.0221 - accuracy: 0.3038 - val_loss: 5.4062 - val_accuracy: 0.5604
Epoch 6/100
2/2 [==============================] - 0s 38ms/step - loss: 6.0296 - accuracy: 0.2953 - val_loss: 5.4077 - val_accuracy: 0.5604
Epoch 7/100
2/2 [==============================] - 0s 39ms/step - loss: 6.0426 - accuracy: 0.2880 - val_loss: 5.4087 - val_accuracy: 0.5495
Epoch 8/100
2/2 [==============================] - 0s 41ms/step - loss: 6.0167 - accuracy: 0.2940 - val_loss: 5.4093 - val_accuracy: 0.5495
Epoch 9/100
2/2 [==============================] - 0s 38ms/step - loss: 5.9649 - accuracy: 0.3111 - val_loss: 5.4098 - val_accuracy: 0.5385
Epoch 10/100
2/2 [==============================] - 0s 38ms/step - loss: 6.0166 - accuracy: 0.2940 - val_loss: 5.4098 - val_accuracy: 0.5165
Epoch 11/100
2/2 [==============================] - 0s 41ms/step - loss: 6.0058 - accuracy: 0.2977 - val_loss: 5.4095 - val_accuracy: 0.5165
Epoch 12/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9794 - accuracy: 0.3026 - val_loss: 5.4092 - val_accuracy: 0.5165
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 5.9504 - accuracy: 0.3196 - val_loss: 5.4089 - val_accuracy: 0.5165
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 5.9723 - accuracy: 0.2953 - val_loss: 5.4085 - val_accuracy: 0.5165
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 5.9448 - accuracy: 0.3196 - val_loss: 5.4077 - val_accuracy: 0.5165
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 5.9416 - accuracy: 0.3086 - val_loss: 5.4068 - val_accuracy: 0.5165
Epoch 17/100
2/2 [==============================] - 0s 38ms/step - loss: 5.9535 - accuracy: 0.3062 - val_loss: 5.4058 - val_accuracy: 0.5165
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9531 - accuracy: 0.3098 - val_loss: 5.4050 - val_accuracy: 0.5165
Epoch 19/100
2/2 [==============================] - 0s 36ms/step - loss: 5.9178 - accuracy: 0.3159 - val_loss: 5.4041 - val_accuracy: 0.5165
Epoch 20/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8845 - accuracy: 0.3147 - val_loss: 5.4029 - val_accuracy: 0.5165
Epoch 21/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9065 - accuracy: 0.3196 - val_loss: 5.4019 - val_accuracy: 0.5165
Epoch 22/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8841 - accuracy: 0.3147 - val_loss: 5.4007 - val_accuracy: 0.5165
Epoch 23/100
2/2 [==============================] - 0s 37ms/step - loss: 5.9072 - accuracy: 0.3098 - val_loss: 5.3994 - val_accuracy: 0.5165
Epoch 24/100
2/2 [==============================] - 0s 43ms/step - loss: 5.8842 - accuracy: 0.3208 - val_loss: 5.3979 - val_accuracy: 0.5165
Epoch 25/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8654 - accuracy: 0.3293 - val_loss: 5.3966 - val_accuracy: 0.5165
Epoch 26/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8571 - accuracy: 0.3208 - val_loss: 5.3955 - val_accuracy: 0.5055
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 5.8781 - accuracy: 0.3111 - val_loss: 5.3940 - val_accuracy: 0.5055
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 5.8705 - accuracy: 0.3086 - val_loss: 5.3922 - val_accuracy: 0.5055
Epoch 29/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8296 - accuracy: 0.3171 - val_loss: 5.3904 - val_accuracy: 0.5055
Epoch 30/100
2/2 [==============================] - 0s 43ms/step - loss: 5.8426 - accuracy: 0.3244 - val_loss: 5.3889 - val_accuracy: 0.4945
Epoch 31/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8251 - accuracy: 0.3135 - val_loss: 5.3869 - val_accuracy: 0.5055
Epoch 32/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8049 - accuracy: 0.3159 - val_loss: 5.3854 - val_accuracy: 0.5055
Epoch 33/100
2/2 [==============================] - 0s 54ms/step - loss: 5.8025 - accuracy: 0.3354 - val_loss: 5.3835 - val_accuracy: 0.5055
Epoch 34/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7846 - accuracy: 0.3208 - val_loss: 5.3816 - val_accuracy: 0.5055
Epoch 35/100
2/2 [==============================] - 0s 33ms/step - loss: 5.8073 - accuracy: 0.3244 - val_loss: 5.3796 - val_accuracy: 0.5055
Epoch 36/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7586 - accuracy: 0.3475 - val_loss: 5.3776 - val_accuracy: 0.5055
Epoch 37/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7847 - accuracy: 0.3147 - val_loss: 5.3758 - val_accuracy: 0.5055
Epoch 38/100
2/2 [==============================] - 0s 49ms/step - loss: 5.7463 - accuracy: 0.3256 - val_loss: 5.3738 - val_accuracy: 0.5055
Epoch 39/100
2/2 [==============================] - 0s 37ms/step - loss: 5.7787 - accuracy: 0.3293 - val_loss: 5.3715 - val_accuracy: 0.5055
Epoch 40/100
2/2 [==============================] - 0s 41ms/step - loss: 5.7495 - accuracy: 0.3111 - val_loss: 5.3694 - val_accuracy: 0.4945
Epoch 41/100
2/2 [==============================] - 0s 31ms/step - loss: 5.7399 - accuracy: 0.3293 - val_loss: 5.3674 - val_accuracy: 0.4945
Epoch 42/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7558 - accuracy: 0.3305 - val_loss: 5.3651 - val_accuracy: 0.4945
Epoch 43/100
2/2 [==============================] - 0s 38ms/step - loss: 5.7135 - accuracy: 0.3317 - val_loss: 5.3630 - val_accuracy: 0.4945
Epoch 44/100
2/2 [==============================] - 0s 50ms/step - loss: 5.7345 - accuracy: 0.3281 - val_loss: 5.3608 - val_accuracy: 0.4945
Epoch 45/100
2/2 [==============================] - 0s 25ms/step - loss: 5.6885 - accuracy: 0.3256 - val_loss: 5.3583 - val_accuracy: 0.4945
Epoch 46/100
2/2 [==============================] - 0s 37ms/step - loss: 5.7156 - accuracy: 0.3463 - val_loss: 5.3560 - val_accuracy: 0.4945
Epoch 47/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6966 - accuracy: 0.3439 - val_loss: 5.3537 - val_accuracy: 0.4945
Epoch 48/100
2/2 [==============================] - 0s 46ms/step - loss: 5.6890 - accuracy: 0.3281 - val_loss: 5.3512 - val_accuracy: 0.4945
Epoch 49/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7315 - accuracy: 0.3366 - val_loss: 5.3487 - val_accuracy: 0.4945
Epoch 50/100
2/2 [==============================] - 0s 45ms/step - loss: 5.6947 - accuracy: 0.3317 - val_loss: 5.3462 - val_accuracy: 0.5055
Epoch 51/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6725 - accuracy: 0.3499 - val_loss: 5.3435 - val_accuracy: 0.5055
Epoch 52/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6930 - accuracy: 0.3256 - val_loss: 5.3407 - val_accuracy: 0.5055
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 5.6528 - accuracy: 0.3414 - val_loss: 5.3380 - val_accuracy: 0.5055
Epoch 54/100
2/2 [==============================] - 0s 51ms/step - loss: 5.6465 - accuracy: 0.3536 - val_loss: 5.3351 - val_accuracy: 0.5055
Epoch 55/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6445 - accuracy: 0.3560 - val_loss: 5.3324 - val_accuracy: 0.5055
Epoch 56/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6318 - accuracy: 0.3402 - val_loss: 5.3298 - val_accuracy: 0.5055
Epoch 57/100
2/2 [==============================] - 0s 41ms/step - loss: 5.6513 - accuracy: 0.3487 - val_loss: 5.3270 - val_accuracy: 0.5055
Epoch 58/100
2/2 [==============================] - 0s 31ms/step - loss: 5.6242 - accuracy: 0.3414 - val_loss: 5.3241 - val_accuracy: 0.5055
Epoch 59/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6203 - accuracy: 0.3354 - val_loss: 5.3213 - val_accuracy: 0.5055
Epoch 60/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6013 - accuracy: 0.3475 - val_loss: 5.3183 - val_accuracy: 0.5055
Epoch 61/100
2/2 [==============================] - 0s 48ms/step - loss: 5.5834 - accuracy: 0.3560 - val_loss: 5.3153 - val_accuracy: 0.5055
Epoch 62/100
2/2 [==============================] - 0s 42ms/step - loss: 5.5860 - accuracy: 0.3633 - val_loss: 5.3123 - val_accuracy: 0.5055
Epoch 63/100
2/2 [==============================] - 0s 31ms/step - loss: 5.5657 - accuracy: 0.3414 - val_loss: 5.3093 - val_accuracy: 0.5055
Epoch 64/100
2/2 [==============================] - 0s 34ms/step - loss: 5.5791 - accuracy: 0.3439 - val_loss: 5.3062 - val_accuracy: 0.5055
Epoch 65/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5901 - accuracy: 0.3293 - val_loss: 5.3029 - val_accuracy: 0.5055
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5240 - accuracy: 0.3670 - val_loss: 5.2998 - val_accuracy: 0.4945
Epoch 67/100
2/2 [==============================] - 0s 34ms/step - loss: 5.5334 - accuracy: 0.3670 - val_loss: 5.2966 - val_accuracy: 0.4945
Epoch 68/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5354 - accuracy: 0.3475 - val_loss: 5.2933 - val_accuracy: 0.4945
Epoch 69/100
2/2 [==============================] - 0s 37ms/step - loss: 5.5163 - accuracy: 0.3609 - val_loss: 5.2901 - val_accuracy: 0.4945
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5242 - accuracy: 0.3463 - val_loss: 5.2868 - val_accuracy: 0.4945
Epoch 71/100
2/2 [==============================] - 0s 42ms/step - loss: 5.5468 - accuracy: 0.3597 - val_loss: 5.2834 - val_accuracy: 0.4945
Epoch 72/100
2/2 [==============================] - 0s 35ms/step - loss: 5.5441 - accuracy: 0.3572 - val_loss: 5.2802 - val_accuracy: 0.4945
Epoch 73/100
2/2 [==============================] - 0s 30ms/step - loss: 5.4797 - accuracy: 0.3621 - val_loss: 5.2767 - val_accuracy: 0.4945
Epoch 74/100
2/2 [==============================] - 0s 40ms/step - loss: 5.4944 - accuracy: 0.3597 - val_loss: 5.2735 - val_accuracy: 0.4945
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4897 - accuracy: 0.3925 - val_loss: 5.2700 - val_accuracy: 0.4945
Epoch 76/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4749 - accuracy: 0.3730 - val_loss: 5.2666 - val_accuracy: 0.4945
Epoch 77/100
2/2 [==============================] - 0s 49ms/step - loss: 5.4717 - accuracy: 0.3742 - val_loss: 5.2632 - val_accuracy: 0.4945
Epoch 78/100
2/2 [==============================] - 0s 45ms/step - loss: 5.4686 - accuracy: 0.3694 - val_loss: 5.2597 - val_accuracy: 0.4945
Epoch 79/100
2/2 [==============================] - 0s 44ms/step - loss: 5.4336 - accuracy: 0.3840 - val_loss: 5.2562 - val_accuracy: 0.4945
Epoch 80/100
2/2 [==============================] - 0s 42ms/step - loss: 5.4635 - accuracy: 0.3633 - val_loss: 5.2526 - val_accuracy: 0.4945
Epoch 81/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4164 - accuracy: 0.3803 - val_loss: 5.2490 - val_accuracy: 0.4945
Epoch 82/100
2/2 [==============================] - 0s 43ms/step - loss: 5.4199 - accuracy: 0.3742 - val_loss: 5.2453 - val_accuracy: 0.4945
Epoch 83/100
2/2 [==============================] - 0s 35ms/step - loss: 5.4493 - accuracy: 0.3609 - val_loss: 5.2417 - val_accuracy: 0.4945
Epoch 84/100
2/2 [==============================] - 0s 34ms/step - loss: 5.4328 - accuracy: 0.3815 - val_loss: 5.2379 - val_accuracy: 0.4945
Epoch 85/100
2/2 [==============================] - 0s 40ms/step - loss: 5.4191 - accuracy: 0.3803 - val_loss: 5.2342 - val_accuracy: 0.4945
Epoch 86/100
2/2 [==============================] - 0s 38ms/step - loss: 5.4142 - accuracy: 0.3694 - val_loss: 5.2304 - val_accuracy: 0.4945
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4303 - accuracy: 0.3609 - val_loss: 5.2266 - val_accuracy: 0.4945
Epoch 88/100
2/2 [==============================] - 0s 47ms/step - loss: 5.4270 - accuracy: 0.3633 - val_loss: 5.2228 - val_accuracy: 0.4945
Epoch 89/100
2/2 [==============================] - 0s 31ms/step - loss: 5.3983 - accuracy: 0.3888 - val_loss: 5.2187 - val_accuracy: 0.4945
Epoch 90/100
2/2 [==============================] - 0s 36ms/step - loss: 5.4055 - accuracy: 0.3718 - val_loss: 5.2145 - val_accuracy: 0.4945
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 5.3806 - accuracy: 0.3900 - val_loss: 5.2104 - val_accuracy: 0.4945
Epoch 92/100
2/2 [==============================] - 0s 39ms/step - loss: 5.3573 - accuracy: 0.3827 - val_loss: 5.2063 - val_accuracy: 0.4945
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 5.3587 - accuracy: 0.3888 - val_loss: 5.2023 - val_accuracy: 0.4945
Epoch 94/100
2/2 [==============================] - 0s 33ms/step - loss: 5.3653 - accuracy: 0.3767 - val_loss: 5.1980 - val_accuracy: 0.4945
Epoch 95/100
2/2 [==============================] - 0s 35ms/step - loss: 5.3275 - accuracy: 0.3949 - val_loss: 5.1940 - val_accuracy: 0.4945
Epoch 96/100
2/2 [==============================] - 0s 37ms/step - loss: 5.3535 - accuracy: 0.3767 - val_loss: 5.1898 - val_accuracy: 0.4945
Epoch 97/100
2/2 [==============================] - 0s 37ms/step - loss: 5.3648 - accuracy: 0.3803 - val_loss: 5.1857 - val_accuracy: 0.4945
Epoch 98/100
2/2 [==============================] - 0s 43ms/step - loss: 5.3484 - accuracy: 0.4034 - val_loss: 5.1816 - val_accuracy: 0.4945
Epoch 99/100
2/2 [==============================] - 0s 44ms/step - loss: 5.3264 - accuracy: 0.3925 - val_loss: 5.1774 - val_accuracy: 0.4835
Epoch 100/100
2/2 [==============================] - 0s 50ms/step - loss: 5.3195 - accuracy: 0.3864 - val_loss: 5.1732 - val_accuracy: 0.4835
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 248ms/step - loss: 6.0991 - accuracy: 0.3354 - val_loss: 5.7677 - val_accuracy: 0.2527
Epoch 2/100
2/2 [==============================] - 0s 44ms/step - loss: 6.0898 - accuracy: 0.3183 - val_loss: 5.7653 - val_accuracy: 0.2637
Epoch 3/100
2/2 [==============================] - 0s 29ms/step - loss: 6.0654 - accuracy: 0.3232 - val_loss: 5.7623 - val_accuracy: 0.2637
Epoch 4/100
2/2 [==============================] - 0s 33ms/step - loss: 6.0750 - accuracy: 0.3244 - val_loss: 5.7584 - val_accuracy: 0.2637
Epoch 5/100
2/2 [==============================] - 0s 36ms/step - loss: 6.0721 - accuracy: 0.3135 - val_loss: 5.7539 - val_accuracy: 0.2637
Epoch 6/100
2/2 [==============================] - 0s 33ms/step - loss: 6.0696 - accuracy: 0.3208 - val_loss: 5.7490 - val_accuracy: 0.2637
Epoch 7/100
2/2 [==============================] - 0s 36ms/step - loss: 6.0895 - accuracy: 0.3269 - val_loss: 5.7440 - val_accuracy: 0.2637
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 6.0780 - accuracy: 0.3354 - val_loss: 5.7388 - val_accuracy: 0.2637
Epoch 9/100
2/2 [==============================] - 0s 32ms/step - loss: 6.0704 - accuracy: 0.3183 - val_loss: 5.7332 - val_accuracy: 0.2637
Epoch 10/100
2/2 [==============================] - 0s 33ms/step - loss: 6.0231 - accuracy: 0.3317 - val_loss: 5.7275 - val_accuracy: 0.2637
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 6.0147 - accuracy: 0.3354 - val_loss: 5.7217 - val_accuracy: 0.2637
Epoch 12/100
2/2 [==============================] - 0s 35ms/step - loss: 6.0231 - accuracy: 0.3305 - val_loss: 5.7160 - val_accuracy: 0.2637
Epoch 13/100
2/2 [==============================] - 0s 33ms/step - loss: 6.0461 - accuracy: 0.3135 - val_loss: 5.7099 - val_accuracy: 0.2637
Epoch 14/100
2/2 [==============================] - 0s 33ms/step - loss: 6.0330 - accuracy: 0.3341 - val_loss: 5.7039 - val_accuracy: 0.2637
Epoch 15/100
2/2 [==============================] - 0s 51ms/step - loss: 6.0076 - accuracy: 0.3329 - val_loss: 5.6976 - val_accuracy: 0.2527
Epoch 16/100
2/2 [==============================] - 0s 49ms/step - loss: 6.0011 - accuracy: 0.3244 - val_loss: 5.6914 - val_accuracy: 0.2527
Epoch 17/100
2/2 [==============================] - 0s 50ms/step - loss: 5.9894 - accuracy: 0.3244 - val_loss: 5.6854 - val_accuracy: 0.2857
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9442 - accuracy: 0.3487 - val_loss: 5.6795 - val_accuracy: 0.2747
Epoch 19/100
2/2 [==============================] - 0s 32ms/step - loss: 5.9853 - accuracy: 0.3305 - val_loss: 5.6733 - val_accuracy: 0.2747
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9731 - accuracy: 0.3281 - val_loss: 5.6672 - val_accuracy: 0.2747
Epoch 21/100
2/2 [==============================] - 0s 42ms/step - loss: 5.9538 - accuracy: 0.3293 - val_loss: 5.6611 - val_accuracy: 0.2747
Epoch 22/100
2/2 [==============================] - 0s 33ms/step - loss: 5.9439 - accuracy: 0.3293 - val_loss: 5.6552 - val_accuracy: 0.2747
Epoch 23/100
2/2 [==============================] - 0s 34ms/step - loss: 5.9643 - accuracy: 0.3426 - val_loss: 5.6493 - val_accuracy: 0.2747
Epoch 24/100
2/2 [==============================] - 0s 39ms/step - loss: 5.9244 - accuracy: 0.3366 - val_loss: 5.6433 - val_accuracy: 0.2747
Epoch 25/100
2/2 [==============================] - 0s 34ms/step - loss: 5.9434 - accuracy: 0.3281 - val_loss: 5.6376 - val_accuracy: 0.2857
Epoch 26/100
2/2 [==============================] - 0s 34ms/step - loss: 5.9179 - accuracy: 0.3281 - val_loss: 5.6317 - val_accuracy: 0.2967
Epoch 27/100
2/2 [==============================] - 0s 43ms/step - loss: 5.9005 - accuracy: 0.3439 - val_loss: 5.6259 - val_accuracy: 0.2967
Epoch 28/100
2/2 [==============================] - 0s 37ms/step - loss: 5.9025 - accuracy: 0.3402 - val_loss: 5.6200 - val_accuracy: 0.2967
Epoch 29/100
2/2 [==============================] - 0s 50ms/step - loss: 5.9111 - accuracy: 0.3305 - val_loss: 5.6142 - val_accuracy: 0.3077
Epoch 30/100
2/2 [==============================] - 0s 37ms/step - loss: 5.8794 - accuracy: 0.3341 - val_loss: 5.6085 - val_accuracy: 0.3077
Epoch 31/100
2/2 [==============================] - 0s 50ms/step - loss: 5.9016 - accuracy: 0.3584 - val_loss: 5.6027 - val_accuracy: 0.3187
Epoch 32/100
2/2 [==============================] - 0s 51ms/step - loss: 5.8569 - accuracy: 0.3597 - val_loss: 5.5970 - val_accuracy: 0.3187
Epoch 33/100
2/2 [==============================] - 0s 34ms/step - loss: 5.8702 - accuracy: 0.3463 - val_loss: 5.5913 - val_accuracy: 0.3187
Epoch 34/100
2/2 [==============================] - 0s 34ms/step - loss: 5.8669 - accuracy: 0.3426 - val_loss: 5.5855 - val_accuracy: 0.3297
Epoch 35/100
2/2 [==============================] - 0s 34ms/step - loss: 5.8625 - accuracy: 0.3475 - val_loss: 5.5800 - val_accuracy: 0.3297
Epoch 36/100
2/2 [==============================] - 0s 40ms/step - loss: 5.8646 - accuracy: 0.3341 - val_loss: 5.5743 - val_accuracy: 0.3407
Epoch 37/100
2/2 [==============================] - 0s 37ms/step - loss: 5.8331 - accuracy: 0.3524 - val_loss: 5.5687 - val_accuracy: 0.3407
Epoch 38/100
2/2 [==============================] - 0s 35ms/step - loss: 5.8472 - accuracy: 0.3645 - val_loss: 5.5631 - val_accuracy: 0.3407
Epoch 39/100
2/2 [==============================] - 0s 49ms/step - loss: 5.8583 - accuracy: 0.3402 - val_loss: 5.5576 - val_accuracy: 0.3407
Epoch 40/100
2/2 [==============================] - 0s 45ms/step - loss: 5.8216 - accuracy: 0.3512 - val_loss: 5.5522 - val_accuracy: 0.3407
Epoch 41/100
2/2 [==============================] - 0s 42ms/step - loss: 5.8121 - accuracy: 0.3499 - val_loss: 5.5467 - val_accuracy: 0.3407
Epoch 42/100
2/2 [==============================] - 0s 42ms/step - loss: 5.8056 - accuracy: 0.3597 - val_loss: 5.5412 - val_accuracy: 0.3407
Epoch 43/100
2/2 [==============================] - 0s 48ms/step - loss: 5.7809 - accuracy: 0.3572 - val_loss: 5.5357 - val_accuracy: 0.3407
Epoch 44/100
2/2 [==============================] - 0s 42ms/step - loss: 5.8174 - accuracy: 0.3524 - val_loss: 5.5304 - val_accuracy: 0.3407
Epoch 45/100
2/2 [==============================] - 0s 49ms/step - loss: 5.7852 - accuracy: 0.3487 - val_loss: 5.5248 - val_accuracy: 0.3516
Epoch 46/100
2/2 [==============================] - 0s 51ms/step - loss: 5.7674 - accuracy: 0.3548 - val_loss: 5.5195 - val_accuracy: 0.3516
Epoch 47/100
2/2 [==============================] - 0s 49ms/step - loss: 5.7846 - accuracy: 0.3548 - val_loss: 5.5140 - val_accuracy: 0.3516
Epoch 48/100
2/2 [==============================] - 0s 37ms/step - loss: 5.7858 - accuracy: 0.3609 - val_loss: 5.5088 - val_accuracy: 0.3407
Epoch 49/100
2/2 [==============================] - 0s 36ms/step - loss: 5.7767 - accuracy: 0.3633 - val_loss: 5.5033 - val_accuracy: 0.3407
Epoch 50/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7741 - accuracy: 0.3645 - val_loss: 5.4979 - val_accuracy: 0.3407
Epoch 51/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7678 - accuracy: 0.3706 - val_loss: 5.4924 - val_accuracy: 0.3407
Epoch 52/100
2/2 [==============================] - 0s 35ms/step - loss: 5.7125 - accuracy: 0.3706 - val_loss: 5.4871 - val_accuracy: 0.3297
Epoch 53/100
2/2 [==============================] - 0s 34ms/step - loss: 5.7358 - accuracy: 0.3670 - val_loss: 5.4819 - val_accuracy: 0.3297
Epoch 54/100
2/2 [==============================] - 0s 46ms/step - loss: 5.6804 - accuracy: 0.3524 - val_loss: 5.4765 - val_accuracy: 0.3297
Epoch 55/100
2/2 [==============================] - 0s 40ms/step - loss: 5.7245 - accuracy: 0.3645 - val_loss: 5.4710 - val_accuracy: 0.3297
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6743 - accuracy: 0.3742 - val_loss: 5.4656 - val_accuracy: 0.3297
Epoch 57/100
2/2 [==============================] - 0s 37ms/step - loss: 5.7053 - accuracy: 0.3621 - val_loss: 5.4604 - val_accuracy: 0.3407
Epoch 58/100
2/2 [==============================] - 0s 41ms/step - loss: 5.6645 - accuracy: 0.3548 - val_loss: 5.4550 - val_accuracy: 0.3407
Epoch 59/100
2/2 [==============================] - 0s 39ms/step - loss: 5.6766 - accuracy: 0.3682 - val_loss: 5.4497 - val_accuracy: 0.3407
Epoch 60/100
2/2 [==============================] - 0s 34ms/step - loss: 5.6668 - accuracy: 0.3767 - val_loss: 5.4444 - val_accuracy: 0.3407
Epoch 61/100
2/2 [==============================] - 0s 44ms/step - loss: 5.6746 - accuracy: 0.3572 - val_loss: 5.4391 - val_accuracy: 0.3407
Epoch 62/100
2/2 [==============================] - 0s 30ms/step - loss: 5.6517 - accuracy: 0.3706 - val_loss: 5.4340 - val_accuracy: 0.3407
Epoch 63/100
2/2 [==============================] - 0s 33ms/step - loss: 5.6536 - accuracy: 0.3560 - val_loss: 5.4287 - val_accuracy: 0.3407
Epoch 64/100
2/2 [==============================] - 0s 31ms/step - loss: 5.6760 - accuracy: 0.3864 - val_loss: 5.4235 - val_accuracy: 0.3407
Epoch 65/100
2/2 [==============================] - 0s 39ms/step - loss: 5.6385 - accuracy: 0.3706 - val_loss: 5.4183 - val_accuracy: 0.3407
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 5.6163 - accuracy: 0.3670 - val_loss: 5.4131 - val_accuracy: 0.3407
Epoch 67/100
2/2 [==============================] - 0s 53ms/step - loss: 5.6366 - accuracy: 0.3718 - val_loss: 5.4081 - val_accuracy: 0.3407
Epoch 68/100
2/2 [==============================] - 0s 38ms/step - loss: 5.6480 - accuracy: 0.3718 - val_loss: 5.4030 - val_accuracy: 0.3407
Epoch 69/100
2/2 [==============================] - 0s 48ms/step - loss: 5.6092 - accuracy: 0.3657 - val_loss: 5.3977 - val_accuracy: 0.3407
Epoch 70/100
2/2 [==============================] - 0s 48ms/step - loss: 5.6013 - accuracy: 0.3949 - val_loss: 5.3926 - val_accuracy: 0.3516
Epoch 71/100
2/2 [==============================] - 0s 43ms/step - loss: 5.6141 - accuracy: 0.3584 - val_loss: 5.3874 - val_accuracy: 0.3516
Epoch 72/100
2/2 [==============================] - 0s 42ms/step - loss: 5.5978 - accuracy: 0.3682 - val_loss: 5.3821 - val_accuracy: 0.3516
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 5.5719 - accuracy: 0.3888 - val_loss: 5.3769 - val_accuracy: 0.3516
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5511 - accuracy: 0.3852 - val_loss: 5.3718 - val_accuracy: 0.3516
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5812 - accuracy: 0.3852 - val_loss: 5.3667 - val_accuracy: 0.3516
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 5.5816 - accuracy: 0.3657 - val_loss: 5.3613 - val_accuracy: 0.3516
Epoch 77/100
2/2 [==============================] - 0s 45ms/step - loss: 5.5711 - accuracy: 0.3852 - val_loss: 5.3562 - val_accuracy: 0.3516
Epoch 78/100
2/2 [==============================] - 0s 39ms/step - loss: 5.5590 - accuracy: 0.3633 - val_loss: 5.3511 - val_accuracy: 0.3626
Epoch 79/100
2/2 [==============================] - 0s 49ms/step - loss: 5.5417 - accuracy: 0.3657 - val_loss: 5.3459 - val_accuracy: 0.3626
Epoch 80/100
2/2 [==============================] - 0s 83ms/step - loss: 5.5526 - accuracy: 0.3779 - val_loss: 5.3408 - val_accuracy: 0.3626
Epoch 81/100
2/2 [==============================] - 0s 43ms/step - loss: 5.5259 - accuracy: 0.3973 - val_loss: 5.3354 - val_accuracy: 0.3626
Epoch 82/100
2/2 [==============================] - 0s 42ms/step - loss: 5.5364 - accuracy: 0.3779 - val_loss: 5.3305 - val_accuracy: 0.3626
Epoch 83/100
2/2 [==============================] - 0s 40ms/step - loss: 5.5283 - accuracy: 0.3815 - val_loss: 5.3251 - val_accuracy: 0.3626
Epoch 84/100
2/2 [==============================] - 0s 40ms/step - loss: 5.5452 - accuracy: 0.3536 - val_loss: 5.3199 - val_accuracy: 0.3626
Epoch 85/100
2/2 [==============================] - 0s 42ms/step - loss: 5.5035 - accuracy: 0.3840 - val_loss: 5.3147 - val_accuracy: 0.3626
Epoch 86/100
2/2 [==============================] - 0s 95ms/step - loss: 5.4798 - accuracy: 0.4010 - val_loss: 5.3096 - val_accuracy: 0.3736
Epoch 87/100
2/2 [==============================] - 0s 42ms/step - loss: 5.4846 - accuracy: 0.3755 - val_loss: 5.3046 - val_accuracy: 0.3736
Epoch 88/100
2/2 [==============================] - 0s 50ms/step - loss: 5.4574 - accuracy: 0.3973 - val_loss: 5.2994 - val_accuracy: 0.3736
Epoch 89/100
2/2 [==============================] - 0s 43ms/step - loss: 5.4595 - accuracy: 0.3925 - val_loss: 5.2942 - val_accuracy: 0.3736
Epoch 90/100
2/2 [==============================] - 0s 49ms/step - loss: 5.4415 - accuracy: 0.4143 - val_loss: 5.2890 - val_accuracy: 0.3736
Epoch 91/100
2/2 [==============================] - 0s 41ms/step - loss: 5.4764 - accuracy: 0.3973 - val_loss: 5.2839 - val_accuracy: 0.3736
Epoch 92/100
2/2 [==============================] - 0s 49ms/step - loss: 5.4716 - accuracy: 0.4010 - val_loss: 5.2787 - val_accuracy: 0.3736
Epoch 93/100
2/2 [==============================] - 0s 42ms/step - loss: 5.4508 - accuracy: 0.3864 - val_loss: 5.2734 - val_accuracy: 0.3736
Epoch 94/100
2/2 [==============================] - 0s 47ms/step - loss: 5.4760 - accuracy: 0.3791 - val_loss: 5.2680 - val_accuracy: 0.3736
Epoch 95/100
2/2 [==============================] - 0s 33ms/step - loss: 5.4508 - accuracy: 0.3840 - val_loss: 5.2630 - val_accuracy: 0.3736
Epoch 96/100
2/2 [==============================] - 0s 41ms/step - loss: 5.4460 - accuracy: 0.4034 - val_loss: 5.2578 - val_accuracy: 0.3736
Epoch 97/100
2/2 [==============================] - 0s 33ms/step - loss: 5.4382 - accuracy: 0.3827 - val_loss: 5.2525 - val_accuracy: 0.3736
Epoch 98/100
2/2 [==============================] - 0s 48ms/step - loss: 5.3977 - accuracy: 0.4070 - val_loss: 5.2472 - val_accuracy: 0.3736
Epoch 99/100
2/2 [==============================] - 0s 41ms/step - loss: 5.3827 - accuracy: 0.4034 - val_loss: 5.2418 - val_accuracy: 0.3846
Epoch 100/100
2/2 [==============================] - 0s 37ms/step - loss: 5.4166 - accuracy: 0.4010 - val_loss: 5.2364 - val_accuracy: 0.3846
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Experiment number: 7
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 3.7505 - accuracy: 0.4136 - val_loss: 3.2088 - val_accuracy: 0.4674
Epoch 2/100
7/7 [==============================] - 0s 10ms/step - loss: 3.7634 - accuracy: 0.4258 - val_loss: 3.2089 - val_accuracy: 0.4783
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7392 - accuracy: 0.4161 - val_loss: 3.2083 - val_accuracy: 0.4783
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6711 - accuracy: 0.4221 - val_loss: 3.2069 - val_accuracy: 0.4891
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7029 - accuracy: 0.4380 - val_loss: 3.2046 - val_accuracy: 0.4891
Epoch 6/100
7/7 [==============================] - 0s 11ms/step - loss: 3.7301 - accuracy: 0.4258 - val_loss: 3.2017 - val_accuracy: 0.4891
Epoch 7/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6731 - accuracy: 0.4343 - val_loss: 3.1981 - val_accuracy: 0.5000
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7004 - accuracy: 0.4173 - val_loss: 3.1939 - val_accuracy: 0.5000
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6399 - accuracy: 0.4246 - val_loss: 3.1892 - val_accuracy: 0.5217
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6221 - accuracy: 0.4489 - val_loss: 3.1837 - val_accuracy: 0.5326
Epoch 11/100
7/7 [==============================] - 0s 10ms/step - loss: 3.6752 - accuracy: 0.4355 - val_loss: 3.1778 - val_accuracy: 0.5543
Epoch 12/100
7/7 [==============================] - 0s 11ms/step - loss: 3.5617 - accuracy: 0.4489 - val_loss: 3.1717 - val_accuracy: 0.5870
Epoch 13/100
7/7 [==============================] - 0s 10ms/step - loss: 3.5682 - accuracy: 0.4440 - val_loss: 3.1650 - val_accuracy: 0.5978
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4937 - accuracy: 0.4672 - val_loss: 3.1578 - val_accuracy: 0.6087
Epoch 15/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4873 - accuracy: 0.4465 - val_loss: 3.1507 - val_accuracy: 0.6087
Epoch 16/100
7/7 [==============================] - 0s 10ms/step - loss: 3.4750 - accuracy: 0.4465 - val_loss: 3.1435 - val_accuracy: 0.6087
Epoch 17/100
7/7 [==============================] - 0s 11ms/step - loss: 3.4327 - accuracy: 0.4623 - val_loss: 3.1358 - val_accuracy: 0.6304
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5188 - accuracy: 0.4623 - val_loss: 3.1279 - val_accuracy: 0.6413
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4046 - accuracy: 0.4964 - val_loss: 3.1197 - val_accuracy: 0.6304
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4189 - accuracy: 0.4927 - val_loss: 3.1116 - val_accuracy: 0.6522
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3977 - accuracy: 0.4842 - val_loss: 3.1034 - val_accuracy: 0.6630
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4014 - accuracy: 0.4818 - val_loss: 3.0954 - val_accuracy: 0.6848
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4458 - accuracy: 0.4684 - val_loss: 3.0875 - val_accuracy: 0.7065
Epoch 24/100
7/7 [==============================] - 0s 10ms/step - loss: 3.4201 - accuracy: 0.4842 - val_loss: 3.0796 - val_accuracy: 0.7283
Epoch 25/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3216 - accuracy: 0.5036 - val_loss: 3.0720 - val_accuracy: 0.7283
Epoch 26/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2969 - accuracy: 0.5146 - val_loss: 3.0644 - val_accuracy: 0.7283
Epoch 27/100
7/7 [==============================] - 0s 10ms/step - loss: 3.3701 - accuracy: 0.4891 - val_loss: 3.0573 - val_accuracy: 0.7391
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2942 - accuracy: 0.4951 - val_loss: 3.0502 - val_accuracy: 0.7283
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2995 - accuracy: 0.5146 - val_loss: 3.0429 - val_accuracy: 0.7391
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3023 - accuracy: 0.5353 - val_loss: 3.0363 - val_accuracy: 0.7391
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2581 - accuracy: 0.5280 - val_loss: 3.0297 - val_accuracy: 0.7391
Epoch 32/100
7/7 [==============================] - 0s 7ms/step - loss: 3.2688 - accuracy: 0.5353 - val_loss: 3.0227 - val_accuracy: 0.7391
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3003 - accuracy: 0.5049 - val_loss: 3.0159 - val_accuracy: 0.7391
Epoch 34/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2497 - accuracy: 0.5474 - val_loss: 3.0095 - val_accuracy: 0.7500
Epoch 35/100
7/7 [==============================] - 0s 10ms/step - loss: 3.2002 - accuracy: 0.5596 - val_loss: 3.0032 - val_accuracy: 0.7500
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2351 - accuracy: 0.5487 - val_loss: 2.9969 - val_accuracy: 0.7609
Epoch 37/100
7/7 [==============================] - 0s 11ms/step - loss: 3.1804 - accuracy: 0.5693 - val_loss: 2.9908 - val_accuracy: 0.7609
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1977 - accuracy: 0.5742 - val_loss: 2.9849 - val_accuracy: 0.7609
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1654 - accuracy: 0.5560 - val_loss: 2.9787 - val_accuracy: 0.7609
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1506 - accuracy: 0.5852 - val_loss: 2.9726 - val_accuracy: 0.7717
Epoch 41/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1655 - accuracy: 0.5608 - val_loss: 2.9671 - val_accuracy: 0.7717
Epoch 42/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1547 - accuracy: 0.5560 - val_loss: 2.9611 - val_accuracy: 0.7717
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1243 - accuracy: 0.5681 - val_loss: 2.9554 - val_accuracy: 0.7717
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1192 - accuracy: 0.5827 - val_loss: 2.9499 - val_accuracy: 0.7717
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1125 - accuracy: 0.5681 - val_loss: 2.9442 - val_accuracy: 0.7717
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1464 - accuracy: 0.5693 - val_loss: 2.9389 - val_accuracy: 0.7717
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0707 - accuracy: 0.6058 - val_loss: 2.9330 - val_accuracy: 0.7717
Epoch 48/100
7/7 [==============================] - 0s 10ms/step - loss: 3.1189 - accuracy: 0.5912 - val_loss: 2.9275 - val_accuracy: 0.7717
Epoch 49/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0593 - accuracy: 0.5949 - val_loss: 2.9223 - val_accuracy: 0.7717
Epoch 50/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0165 - accuracy: 0.6204 - val_loss: 2.9166 - val_accuracy: 0.7717
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0571 - accuracy: 0.6192 - val_loss: 2.9110 - val_accuracy: 0.7717
Epoch 52/100
7/7 [==============================] - 0s 7ms/step - loss: 3.0367 - accuracy: 0.5949 - val_loss: 2.9056 - val_accuracy: 0.7609
Epoch 53/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0296 - accuracy: 0.6131 - val_loss: 2.9007 - val_accuracy: 0.7609
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0148 - accuracy: 0.6411 - val_loss: 2.8947 - val_accuracy: 0.7609
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9880 - accuracy: 0.6387 - val_loss: 2.8895 - val_accuracy: 0.7609
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0034 - accuracy: 0.6107 - val_loss: 2.8836 - val_accuracy: 0.7609
Epoch 57/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0048 - accuracy: 0.6277 - val_loss: 2.8782 - val_accuracy: 0.7609
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9846 - accuracy: 0.6204 - val_loss: 2.8726 - val_accuracy: 0.7609
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9932 - accuracy: 0.6533 - val_loss: 2.8676 - val_accuracy: 0.7609
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0159 - accuracy: 0.6204 - val_loss: 2.8626 - val_accuracy: 0.7609
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9465 - accuracy: 0.6277 - val_loss: 2.8573 - val_accuracy: 0.7609
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9590 - accuracy: 0.6326 - val_loss: 2.8516 - val_accuracy: 0.7609
Epoch 63/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9437 - accuracy: 0.6569 - val_loss: 2.8461 - val_accuracy: 0.7717
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9415 - accuracy: 0.6241 - val_loss: 2.8405 - val_accuracy: 0.7717
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9104 - accuracy: 0.6788 - val_loss: 2.8354 - val_accuracy: 0.7717
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9005 - accuracy: 0.6423 - val_loss: 2.8297 - val_accuracy: 0.7717
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9259 - accuracy: 0.6582 - val_loss: 2.8241 - val_accuracy: 0.7609
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9074 - accuracy: 0.6496 - val_loss: 2.8182 - val_accuracy: 0.7609
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8953 - accuracy: 0.6667 - val_loss: 2.8127 - val_accuracy: 0.7609
Epoch 70/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8927 - accuracy: 0.6691 - val_loss: 2.8067 - val_accuracy: 0.7609
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8779 - accuracy: 0.6667 - val_loss: 2.8007 - val_accuracy: 0.7609
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8821 - accuracy: 0.6752 - val_loss: 2.7946 - val_accuracy: 0.7609
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8674 - accuracy: 0.6642 - val_loss: 2.7888 - val_accuracy: 0.7609
Epoch 74/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8719 - accuracy: 0.6788 - val_loss: 2.7836 - val_accuracy: 0.7609
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8565 - accuracy: 0.6788 - val_loss: 2.7779 - val_accuracy: 0.7609
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8321 - accuracy: 0.7068 - val_loss: 2.7718 - val_accuracy: 0.7609
Epoch 77/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8027 - accuracy: 0.6934 - val_loss: 2.7661 - val_accuracy: 0.7609
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8656 - accuracy: 0.6691 - val_loss: 2.7601 - val_accuracy: 0.7609
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8657 - accuracy: 0.6606 - val_loss: 2.7543 - val_accuracy: 0.7609
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8295 - accuracy: 0.6679 - val_loss: 2.7488 - val_accuracy: 0.7609
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8237 - accuracy: 0.7214 - val_loss: 2.7431 - val_accuracy: 0.7609
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7981 - accuracy: 0.7080 - val_loss: 2.7376 - val_accuracy: 0.7609
Epoch 83/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7874 - accuracy: 0.6837 - val_loss: 2.7318 - val_accuracy: 0.7717
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7586 - accuracy: 0.6983 - val_loss: 2.7264 - val_accuracy: 0.7826
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7897 - accuracy: 0.7178 - val_loss: 2.7215 - val_accuracy: 0.7935
Epoch 86/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7813 - accuracy: 0.6946 - val_loss: 2.7162 - val_accuracy: 0.7935
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7821 - accuracy: 0.7141 - val_loss: 2.7108 - val_accuracy: 0.7935
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7796 - accuracy: 0.7007 - val_loss: 2.7057 - val_accuracy: 0.7935
Epoch 89/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8046 - accuracy: 0.6740 - val_loss: 2.7001 - val_accuracy: 0.7826
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7618 - accuracy: 0.6886 - val_loss: 2.6945 - val_accuracy: 0.7826
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7457 - accuracy: 0.7117 - val_loss: 2.6894 - val_accuracy: 0.7826
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7534 - accuracy: 0.7336 - val_loss: 2.6841 - val_accuracy: 0.7935
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7437 - accuracy: 0.7080 - val_loss: 2.6783 - val_accuracy: 0.7935
Epoch 94/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7527 - accuracy: 0.7117 - val_loss: 2.6731 - val_accuracy: 0.7935
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7279 - accuracy: 0.7226 - val_loss: 2.6678 - val_accuracy: 0.7935
Epoch 96/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7199 - accuracy: 0.7190 - val_loss: 2.6630 - val_accuracy: 0.8152
Epoch 97/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7071 - accuracy: 0.7202 - val_loss: 2.6578 - val_accuracy: 0.8152
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7434 - accuracy: 0.7129 - val_loss: 2.6531 - val_accuracy: 0.8152
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6912 - accuracy: 0.7360 - val_loss: 2.6482 - val_accuracy: 0.8152
Epoch 100/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6888 - accuracy: 0.7457 - val_loss: 2.6434 - val_accuracy: 0.8261
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 44ms/step - loss: 3.7201 - accuracy: 0.4380 - val_loss: 3.1596 - val_accuracy: 0.4674
Epoch 2/100
7/7 [==============================] - 0s 7ms/step - loss: 3.7016 - accuracy: 0.4465 - val_loss: 3.1586 - val_accuracy: 0.4674
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6667 - accuracy: 0.4623 - val_loss: 3.1570 - val_accuracy: 0.4891
Epoch 4/100
7/7 [==============================] - 0s 12ms/step - loss: 3.6974 - accuracy: 0.4513 - val_loss: 3.1546 - val_accuracy: 0.4674
Epoch 5/100
7/7 [==============================] - 0s 7ms/step - loss: 3.6924 - accuracy: 0.4404 - val_loss: 3.1517 - val_accuracy: 0.4783
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6644 - accuracy: 0.4550 - val_loss: 3.1482 - val_accuracy: 0.4783
Epoch 7/100
7/7 [==============================] - 0s 10ms/step - loss: 3.6407 - accuracy: 0.4684 - val_loss: 3.1439 - val_accuracy: 0.4783
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6761 - accuracy: 0.4331 - val_loss: 3.1394 - val_accuracy: 0.4891
Epoch 9/100
7/7 [==============================] - 0s 11ms/step - loss: 3.6261 - accuracy: 0.4720 - val_loss: 3.1343 - val_accuracy: 0.5109
Epoch 10/100
7/7 [==============================] - 0s 11ms/step - loss: 3.6207 - accuracy: 0.4392 - val_loss: 3.1291 - val_accuracy: 0.5109
Epoch 11/100
7/7 [==============================] - 0s 11ms/step - loss: 3.6188 - accuracy: 0.4599 - val_loss: 3.1235 - val_accuracy: 0.5217
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6338 - accuracy: 0.4696 - val_loss: 3.1173 - val_accuracy: 0.5217
Epoch 13/100
7/7 [==============================] - 0s 7ms/step - loss: 3.5500 - accuracy: 0.4964 - val_loss: 3.1105 - val_accuracy: 0.5326
Epoch 14/100
7/7 [==============================] - 0s 10ms/step - loss: 3.5522 - accuracy: 0.4927 - val_loss: 3.1036 - val_accuracy: 0.5217
Epoch 15/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4966 - accuracy: 0.4732 - val_loss: 3.0962 - val_accuracy: 0.5109
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5415 - accuracy: 0.4550 - val_loss: 3.0886 - val_accuracy: 0.5326
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4958 - accuracy: 0.4757 - val_loss: 3.0804 - val_accuracy: 0.5435
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 3.5008 - accuracy: 0.4781 - val_loss: 3.0722 - val_accuracy: 0.5652
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4369 - accuracy: 0.4842 - val_loss: 3.0639 - val_accuracy: 0.5652
Epoch 20/100
7/7 [==============================] - 0s 10ms/step - loss: 3.3901 - accuracy: 0.5012 - val_loss: 3.0558 - val_accuracy: 0.5870
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3909 - accuracy: 0.5231 - val_loss: 3.0475 - val_accuracy: 0.5978
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4217 - accuracy: 0.5073 - val_loss: 3.0393 - val_accuracy: 0.6196
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3843 - accuracy: 0.5085 - val_loss: 3.0306 - val_accuracy: 0.6304
Epoch 24/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3494 - accuracy: 0.5073 - val_loss: 3.0218 - val_accuracy: 0.6304
Epoch 25/100
7/7 [==============================] - 0s 10ms/step - loss: 3.3439 - accuracy: 0.4951 - val_loss: 3.0132 - val_accuracy: 0.6413
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3167 - accuracy: 0.5061 - val_loss: 3.0048 - val_accuracy: 0.6522
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3098 - accuracy: 0.5134 - val_loss: 2.9964 - val_accuracy: 0.6630
Epoch 28/100
7/7 [==============================] - 0s 10ms/step - loss: 3.3354 - accuracy: 0.5036 - val_loss: 2.9875 - val_accuracy: 0.6630
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2873 - accuracy: 0.5158 - val_loss: 2.9792 - val_accuracy: 0.6630
Epoch 30/100
7/7 [==============================] - 0s 10ms/step - loss: 3.2951 - accuracy: 0.5146 - val_loss: 2.9706 - val_accuracy: 0.6739
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2149 - accuracy: 0.5231 - val_loss: 2.9624 - val_accuracy: 0.6739
Epoch 32/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2165 - accuracy: 0.5414 - val_loss: 2.9536 - val_accuracy: 0.6739
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 3.2497 - accuracy: 0.5207 - val_loss: 2.9454 - val_accuracy: 0.6739
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2430 - accuracy: 0.5195 - val_loss: 2.9370 - val_accuracy: 0.6739
Epoch 35/100
7/7 [==============================] - 0s 7ms/step - loss: 3.2246 - accuracy: 0.5341 - val_loss: 2.9287 - val_accuracy: 0.6848
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1938 - accuracy: 0.5207 - val_loss: 2.9205 - val_accuracy: 0.6957
Epoch 37/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1968 - accuracy: 0.5341 - val_loss: 2.9125 - val_accuracy: 0.6957
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1280 - accuracy: 0.5560 - val_loss: 2.9048 - val_accuracy: 0.6848
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1623 - accuracy: 0.5450 - val_loss: 2.8967 - val_accuracy: 0.6848
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 3.0877 - accuracy: 0.5669 - val_loss: 2.8889 - val_accuracy: 0.6848
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1442 - accuracy: 0.5462 - val_loss: 2.8809 - val_accuracy: 0.6848
Epoch 42/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1267 - accuracy: 0.5438 - val_loss: 2.8727 - val_accuracy: 0.7174
Epoch 43/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0985 - accuracy: 0.5401 - val_loss: 2.8650 - val_accuracy: 0.7283
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1210 - accuracy: 0.5596 - val_loss: 2.8571 - val_accuracy: 0.7391
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0792 - accuracy: 0.5596 - val_loss: 2.8491 - val_accuracy: 0.7391
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0890 - accuracy: 0.5718 - val_loss: 2.8414 - val_accuracy: 0.7500
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0522 - accuracy: 0.5900 - val_loss: 2.8343 - val_accuracy: 0.7500
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0622 - accuracy: 0.5864 - val_loss: 2.8266 - val_accuracy: 0.7500
Epoch 49/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0480 - accuracy: 0.5925 - val_loss: 2.8190 - val_accuracy: 0.7500
Epoch 50/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0560 - accuracy: 0.5633 - val_loss: 2.8108 - val_accuracy: 0.7500
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0514 - accuracy: 0.5912 - val_loss: 2.8034 - val_accuracy: 0.7609
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0004 - accuracy: 0.5998 - val_loss: 2.7961 - val_accuracy: 0.7717
Epoch 53/100
7/7 [==============================] - 0s 7ms/step - loss: 3.0095 - accuracy: 0.5912 - val_loss: 2.7886 - val_accuracy: 0.7826
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9556 - accuracy: 0.6168 - val_loss: 2.7810 - val_accuracy: 0.7826
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9943 - accuracy: 0.6071 - val_loss: 2.7738 - val_accuracy: 0.7826
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9901 - accuracy: 0.6022 - val_loss: 2.7667 - val_accuracy: 0.7826
Epoch 57/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9652 - accuracy: 0.5779 - val_loss: 2.7595 - val_accuracy: 0.7826
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9839 - accuracy: 0.5888 - val_loss: 2.7523 - val_accuracy: 0.7826
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9618 - accuracy: 0.6156 - val_loss: 2.7453 - val_accuracy: 0.7826
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9284 - accuracy: 0.6253 - val_loss: 2.7384 - val_accuracy: 0.7826
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9504 - accuracy: 0.6156 - val_loss: 2.7313 - val_accuracy: 0.7935
Epoch 62/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9263 - accuracy: 0.6217 - val_loss: 2.7247 - val_accuracy: 0.7935
Epoch 63/100
7/7 [==============================] - 0s 12ms/step - loss: 2.9076 - accuracy: 0.6168 - val_loss: 2.7179 - val_accuracy: 0.7935
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9130 - accuracy: 0.6241 - val_loss: 2.7114 - val_accuracy: 0.7935
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8623 - accuracy: 0.6472 - val_loss: 2.7046 - val_accuracy: 0.8043
Epoch 66/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9320 - accuracy: 0.6034 - val_loss: 2.6978 - val_accuracy: 0.8043
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8952 - accuracy: 0.6436 - val_loss: 2.6908 - val_accuracy: 0.8043
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8865 - accuracy: 0.6545 - val_loss: 2.6839 - val_accuracy: 0.8043
Epoch 69/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8918 - accuracy: 0.6277 - val_loss: 2.6770 - val_accuracy: 0.7935
Epoch 70/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8895 - accuracy: 0.6472 - val_loss: 2.6704 - val_accuracy: 0.7935
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8629 - accuracy: 0.6582 - val_loss: 2.6640 - val_accuracy: 0.7935
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8118 - accuracy: 0.6715 - val_loss: 2.6573 - val_accuracy: 0.7935
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8410 - accuracy: 0.6521 - val_loss: 2.6506 - val_accuracy: 0.7935
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8760 - accuracy: 0.6521 - val_loss: 2.6441 - val_accuracy: 0.7935
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8246 - accuracy: 0.6715 - val_loss: 2.6375 - val_accuracy: 0.8043
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8261 - accuracy: 0.6655 - val_loss: 2.6314 - val_accuracy: 0.8043
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7932 - accuracy: 0.6703 - val_loss: 2.6249 - val_accuracy: 0.8043
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8092 - accuracy: 0.6715 - val_loss: 2.6183 - val_accuracy: 0.8043
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8025 - accuracy: 0.6910 - val_loss: 2.6122 - val_accuracy: 0.8152
Epoch 80/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8031 - accuracy: 0.6849 - val_loss: 2.6059 - val_accuracy: 0.8261
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8333 - accuracy: 0.6642 - val_loss: 2.5999 - val_accuracy: 0.8261
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7477 - accuracy: 0.6800 - val_loss: 2.5939 - val_accuracy: 0.8370
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7938 - accuracy: 0.6776 - val_loss: 2.5880 - val_accuracy: 0.8478
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7999 - accuracy: 0.6776 - val_loss: 2.5824 - val_accuracy: 0.8478
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7538 - accuracy: 0.7105 - val_loss: 2.5766 - val_accuracy: 0.8587
Epoch 86/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7490 - accuracy: 0.6983 - val_loss: 2.5711 - val_accuracy: 0.8478
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7481 - accuracy: 0.7080 - val_loss: 2.5656 - val_accuracy: 0.8478
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7500 - accuracy: 0.6788 - val_loss: 2.5603 - val_accuracy: 0.8478
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7383 - accuracy: 0.7056 - val_loss: 2.5548 - val_accuracy: 0.8478
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7175 - accuracy: 0.7044 - val_loss: 2.5494 - val_accuracy: 0.8478
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7103 - accuracy: 0.7202 - val_loss: 2.5441 - val_accuracy: 0.8478
Epoch 92/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7287 - accuracy: 0.7080 - val_loss: 2.5391 - val_accuracy: 0.8478
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7001 - accuracy: 0.7129 - val_loss: 2.5333 - val_accuracy: 0.8478
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7084 - accuracy: 0.7372 - val_loss: 2.5281 - val_accuracy: 0.8478
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6926 - accuracy: 0.7275 - val_loss: 2.5227 - val_accuracy: 0.8478
Epoch 96/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6875 - accuracy: 0.7190 - val_loss: 2.5176 - val_accuracy: 0.8478
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7189 - accuracy: 0.7092 - val_loss: 2.5125 - val_accuracy: 0.8478
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6559 - accuracy: 0.7336 - val_loss: 2.5075 - val_accuracy: 0.8587
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6894 - accuracy: 0.7226 - val_loss: 2.5025 - val_accuracy: 0.8587
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6926 - accuracy: 0.7178 - val_loss: 2.4976 - val_accuracy: 0.8587
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 44ms/step - loss: 4.0413 - accuracy: 0.3333 - val_loss: 3.0918 - val_accuracy: 0.5870
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 3.9825 - accuracy: 0.3297 - val_loss: 3.0969 - val_accuracy: 0.5761
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 3.9661 - accuracy: 0.3370 - val_loss: 3.1011 - val_accuracy: 0.5652
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 3.9154 - accuracy: 0.3370 - val_loss: 3.1044 - val_accuracy: 0.5543
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 3.9362 - accuracy: 0.3285 - val_loss: 3.1062 - val_accuracy: 0.5435
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.9146 - accuracy: 0.3224 - val_loss: 3.1070 - val_accuracy: 0.5435
Epoch 7/100
7/7 [==============================] - 0s 11ms/step - loss: 3.8436 - accuracy: 0.3540 - val_loss: 3.1068 - val_accuracy: 0.5435
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8072 - accuracy: 0.3832 - val_loss: 3.1054 - val_accuracy: 0.5543
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 3.8005 - accuracy: 0.3528 - val_loss: 3.1033 - val_accuracy: 0.5543
Epoch 10/100
7/7 [==============================] - 0s 11ms/step - loss: 3.7564 - accuracy: 0.3601 - val_loss: 3.1002 - val_accuracy: 0.5652
Epoch 11/100
7/7 [==============================] - 0s 11ms/step - loss: 3.7518 - accuracy: 0.3601 - val_loss: 3.0963 - val_accuracy: 0.5761
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6998 - accuracy: 0.3406 - val_loss: 3.0914 - val_accuracy: 0.5870
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6761 - accuracy: 0.3564 - val_loss: 3.0861 - val_accuracy: 0.5870
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6357 - accuracy: 0.3723 - val_loss: 3.0801 - val_accuracy: 0.5652
Epoch 15/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5890 - accuracy: 0.3723 - val_loss: 3.0737 - val_accuracy: 0.5543
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5815 - accuracy: 0.3625 - val_loss: 3.0666 - val_accuracy: 0.5652
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 3.5679 - accuracy: 0.3674 - val_loss: 3.0591 - val_accuracy: 0.6087
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5123 - accuracy: 0.3662 - val_loss: 3.0511 - val_accuracy: 0.6196
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4790 - accuracy: 0.3990 - val_loss: 3.0430 - val_accuracy: 0.6413
Epoch 20/100
7/7 [==============================] - 0s 11ms/step - loss: 3.4717 - accuracy: 0.3905 - val_loss: 3.0345 - val_accuracy: 0.6522
Epoch 21/100
7/7 [==============================] - 0s 10ms/step - loss: 3.4608 - accuracy: 0.4063 - val_loss: 3.0260 - val_accuracy: 0.6739
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4169 - accuracy: 0.4112 - val_loss: 3.0180 - val_accuracy: 0.6848
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3652 - accuracy: 0.4392 - val_loss: 3.0094 - val_accuracy: 0.7174
Epoch 24/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3390 - accuracy: 0.4501 - val_loss: 3.0011 - val_accuracy: 0.7391
Epoch 25/100
7/7 [==============================] - 0s 10ms/step - loss: 3.3214 - accuracy: 0.4501 - val_loss: 2.9929 - val_accuracy: 0.7283
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3025 - accuracy: 0.4513 - val_loss: 2.9849 - val_accuracy: 0.7283
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3240 - accuracy: 0.4659 - val_loss: 2.9774 - val_accuracy: 0.7391
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3043 - accuracy: 0.4684 - val_loss: 2.9700 - val_accuracy: 0.7391
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2957 - accuracy: 0.4757 - val_loss: 2.9625 - val_accuracy: 0.7391
Epoch 30/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2733 - accuracy: 0.4793 - val_loss: 2.9550 - val_accuracy: 0.7500
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2398 - accuracy: 0.5255 - val_loss: 2.9475 - val_accuracy: 0.7500
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2640 - accuracy: 0.4976 - val_loss: 2.9407 - val_accuracy: 0.7609
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2254 - accuracy: 0.5097 - val_loss: 2.9342 - val_accuracy: 0.7609
Epoch 34/100
7/7 [==============================] - 0s 11ms/step - loss: 3.1921 - accuracy: 0.5134 - val_loss: 2.9274 - val_accuracy: 0.7717
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1992 - accuracy: 0.5061 - val_loss: 2.9204 - val_accuracy: 0.7717
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2253 - accuracy: 0.4988 - val_loss: 2.9139 - val_accuracy: 0.7609
Epoch 37/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1894 - accuracy: 0.5377 - val_loss: 2.9073 - val_accuracy: 0.7609
Epoch 38/100
7/7 [==============================] - 0s 11ms/step - loss: 3.1752 - accuracy: 0.5341 - val_loss: 2.9008 - val_accuracy: 0.7609
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1598 - accuracy: 0.5511 - val_loss: 2.8943 - val_accuracy: 0.7609
Epoch 40/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1650 - accuracy: 0.5304 - val_loss: 2.8877 - val_accuracy: 0.7717
Epoch 41/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1326 - accuracy: 0.5377 - val_loss: 2.8813 - val_accuracy: 0.7717
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0807 - accuracy: 0.5560 - val_loss: 2.8747 - val_accuracy: 0.7717
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1109 - accuracy: 0.5535 - val_loss: 2.8682 - val_accuracy: 0.7717
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1046 - accuracy: 0.5693 - val_loss: 2.8619 - val_accuracy: 0.7717
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1214 - accuracy: 0.5681 - val_loss: 2.8559 - val_accuracy: 0.7717
Epoch 46/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0672 - accuracy: 0.5742 - val_loss: 2.8495 - val_accuracy: 0.7717
Epoch 47/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0796 - accuracy: 0.5815 - val_loss: 2.8431 - val_accuracy: 0.7935
Epoch 48/100
7/7 [==============================] - 0s 7ms/step - loss: 3.0716 - accuracy: 0.5669 - val_loss: 2.8365 - val_accuracy: 0.7935
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0868 - accuracy: 0.5779 - val_loss: 2.8300 - val_accuracy: 0.7826
Epoch 50/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0465 - accuracy: 0.5985 - val_loss: 2.8234 - val_accuracy: 0.7826
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0601 - accuracy: 0.6107 - val_loss: 2.8172 - val_accuracy: 0.7717
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0123 - accuracy: 0.5815 - val_loss: 2.8111 - val_accuracy: 0.7717
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0190 - accuracy: 0.5998 - val_loss: 2.8052 - val_accuracy: 0.7717
Epoch 54/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0200 - accuracy: 0.5961 - val_loss: 2.7991 - val_accuracy: 0.7609
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9688 - accuracy: 0.6484 - val_loss: 2.7932 - val_accuracy: 0.7609
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0150 - accuracy: 0.6083 - val_loss: 2.7872 - val_accuracy: 0.7609
Epoch 57/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9762 - accuracy: 0.6119 - val_loss: 2.7809 - val_accuracy: 0.7609
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0108 - accuracy: 0.6095 - val_loss: 2.7755 - val_accuracy: 0.7609
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9901 - accuracy: 0.5803 - val_loss: 2.7699 - val_accuracy: 0.7609
Epoch 60/100
7/7 [==============================] - 0s 11ms/step - loss: 2.9608 - accuracy: 0.6204 - val_loss: 2.7637 - val_accuracy: 0.7717
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9199 - accuracy: 0.6314 - val_loss: 2.7577 - val_accuracy: 0.7826
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9266 - accuracy: 0.6314 - val_loss: 2.7518 - val_accuracy: 0.7826
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9023 - accuracy: 0.6411 - val_loss: 2.7461 - val_accuracy: 0.7826
Epoch 64/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9037 - accuracy: 0.6326 - val_loss: 2.7406 - val_accuracy: 0.7935
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9205 - accuracy: 0.6484 - val_loss: 2.7348 - val_accuracy: 0.7935
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9168 - accuracy: 0.6314 - val_loss: 2.7289 - val_accuracy: 0.7935
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9211 - accuracy: 0.6241 - val_loss: 2.7239 - val_accuracy: 0.7935
Epoch 68/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9109 - accuracy: 0.6472 - val_loss: 2.7184 - val_accuracy: 0.7935
Epoch 69/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8921 - accuracy: 0.6350 - val_loss: 2.7133 - val_accuracy: 0.7935
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8419 - accuracy: 0.6642 - val_loss: 2.7080 - val_accuracy: 0.8043
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9239 - accuracy: 0.6423 - val_loss: 2.7026 - val_accuracy: 0.8043
Epoch 72/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8580 - accuracy: 0.6582 - val_loss: 2.6971 - val_accuracy: 0.8043
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8553 - accuracy: 0.6557 - val_loss: 2.6920 - val_accuracy: 0.8043
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8658 - accuracy: 0.6630 - val_loss: 2.6868 - val_accuracy: 0.8370
Epoch 75/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8533 - accuracy: 0.6423 - val_loss: 2.6813 - val_accuracy: 0.8370
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8473 - accuracy: 0.6569 - val_loss: 2.6767 - val_accuracy: 0.8370
Epoch 77/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8396 - accuracy: 0.6582 - val_loss: 2.6715 - val_accuracy: 0.8478
Epoch 78/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8165 - accuracy: 0.6703 - val_loss: 2.6663 - val_accuracy: 0.8478
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8211 - accuracy: 0.6703 - val_loss: 2.6614 - val_accuracy: 0.8478
Epoch 80/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8030 - accuracy: 0.6813 - val_loss: 2.6567 - val_accuracy: 0.8478
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7923 - accuracy: 0.6776 - val_loss: 2.6517 - val_accuracy: 0.8478
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7773 - accuracy: 0.6861 - val_loss: 2.6471 - val_accuracy: 0.8478
Epoch 83/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7955 - accuracy: 0.6934 - val_loss: 2.6422 - val_accuracy: 0.8478
Epoch 84/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7992 - accuracy: 0.6813 - val_loss: 2.6373 - val_accuracy: 0.8478
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7403 - accuracy: 0.7165 - val_loss: 2.6323 - val_accuracy: 0.8478
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7693 - accuracy: 0.6886 - val_loss: 2.6278 - val_accuracy: 0.8478
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7196 - accuracy: 0.7226 - val_loss: 2.6228 - val_accuracy: 0.8478
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7627 - accuracy: 0.7044 - val_loss: 2.6180 - val_accuracy: 0.8478
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7789 - accuracy: 0.6971 - val_loss: 2.6133 - val_accuracy: 0.8478
Epoch 90/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7241 - accuracy: 0.6934 - val_loss: 2.6084 - val_accuracy: 0.8478
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7443 - accuracy: 0.7080 - val_loss: 2.6036 - val_accuracy: 0.8478
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6857 - accuracy: 0.7226 - val_loss: 2.5990 - val_accuracy: 0.8478
Epoch 93/100
7/7 [==============================] - 0s 11ms/step - loss: 2.6831 - accuracy: 0.7153 - val_loss: 2.5945 - val_accuracy: 0.8478
Epoch 94/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7200 - accuracy: 0.7141 - val_loss: 2.5898 - val_accuracy: 0.8478
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6917 - accuracy: 0.7238 - val_loss: 2.5854 - val_accuracy: 0.8478
Epoch 96/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7135 - accuracy: 0.7202 - val_loss: 2.5808 - val_accuracy: 0.8370
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6725 - accuracy: 0.7214 - val_loss: 2.5763 - val_accuracy: 0.8370
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7017 - accuracy: 0.7056 - val_loss: 2.5719 - val_accuracy: 0.8370
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7027 - accuracy: 0.7299 - val_loss: 2.5673 - val_accuracy: 0.8370
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6620 - accuracy: 0.7384 - val_loss: 2.5628 - val_accuracy: 0.8370
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 223us/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 3.8567 - accuracy: 0.3698 - val_loss: 3.5137 - val_accuracy: 0.1196
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 3.9628 - accuracy: 0.3491 - val_loss: 3.5024 - val_accuracy: 0.1196
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8797 - accuracy: 0.3394 - val_loss: 3.4899 - val_accuracy: 0.1196
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8690 - accuracy: 0.3637 - val_loss: 3.4770 - val_accuracy: 0.1196
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 3.8661 - accuracy: 0.3552 - val_loss: 3.4627 - val_accuracy: 0.1304
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 3.8210 - accuracy: 0.3796 - val_loss: 3.4473 - val_accuracy: 0.1304
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7870 - accuracy: 0.3771 - val_loss: 3.4315 - val_accuracy: 0.1413
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7805 - accuracy: 0.3832 - val_loss: 3.4146 - val_accuracy: 0.1522
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 3.8008 - accuracy: 0.3893 - val_loss: 3.3975 - val_accuracy: 0.1848
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7016 - accuracy: 0.3942 - val_loss: 3.3801 - val_accuracy: 0.2065
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7228 - accuracy: 0.4051 - val_loss: 3.3617 - val_accuracy: 0.2826
Epoch 12/100
7/7 [==============================] - 0s 11ms/step - loss: 3.6791 - accuracy: 0.3978 - val_loss: 3.3428 - val_accuracy: 0.3261
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6280 - accuracy: 0.3990 - val_loss: 3.3239 - val_accuracy: 0.3370
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5321 - accuracy: 0.4343 - val_loss: 3.3045 - val_accuracy: 0.3913
Epoch 15/100
7/7 [==============================] - 0s 11ms/step - loss: 3.5110 - accuracy: 0.4696 - val_loss: 3.2851 - val_accuracy: 0.4348
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5842 - accuracy: 0.4453 - val_loss: 3.2657 - val_accuracy: 0.4783
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 3.5260 - accuracy: 0.4659 - val_loss: 3.2466 - val_accuracy: 0.5109
Epoch 18/100
7/7 [==============================] - 0s 11ms/step - loss: 3.4670 - accuracy: 0.4781 - val_loss: 3.2270 - val_accuracy: 0.5326
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4766 - accuracy: 0.4720 - val_loss: 3.2077 - val_accuracy: 0.5652
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4393 - accuracy: 0.4745 - val_loss: 3.1892 - val_accuracy: 0.5870
Epoch 21/100
7/7 [==============================] - 1s 91ms/step - loss: 3.4272 - accuracy: 0.4830 - val_loss: 3.1705 - val_accuracy: 0.6196
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4058 - accuracy: 0.5109 - val_loss: 3.1526 - val_accuracy: 0.6304
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3746 - accuracy: 0.5231 - val_loss: 3.1347 - val_accuracy: 0.6304
Epoch 24/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3774 - accuracy: 0.5085 - val_loss: 3.1172 - val_accuracy: 0.6522
Epoch 25/100
7/7 [==============================] - 0s 11ms/step - loss: 3.3746 - accuracy: 0.5012 - val_loss: 3.1009 - val_accuracy: 0.6522
Epoch 26/100
7/7 [==============================] - 0s 11ms/step - loss: 3.3740 - accuracy: 0.5146 - val_loss: 3.0848 - val_accuracy: 0.6630
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3178 - accuracy: 0.5255 - val_loss: 3.0695 - val_accuracy: 0.6630
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3138 - accuracy: 0.5280 - val_loss: 3.0538 - val_accuracy: 0.6630
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2950 - accuracy: 0.5620 - val_loss: 3.0391 - val_accuracy: 0.6630
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3494 - accuracy: 0.5328 - val_loss: 3.0244 - val_accuracy: 0.6739
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2934 - accuracy: 0.5487 - val_loss: 3.0106 - val_accuracy: 0.6739
Epoch 32/100
7/7 [==============================] - 0s 11ms/step - loss: 3.3233 - accuracy: 0.5268 - val_loss: 2.9974 - val_accuracy: 0.6739
Epoch 33/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2615 - accuracy: 0.5450 - val_loss: 2.9842 - val_accuracy: 0.6739
Epoch 34/100
7/7 [==============================] - 0s 10ms/step - loss: 3.2990 - accuracy: 0.5341 - val_loss: 2.9717 - val_accuracy: 0.6739
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2983 - accuracy: 0.5523 - val_loss: 2.9595 - val_accuracy: 0.6739
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2267 - accuracy: 0.5766 - val_loss: 2.9472 - val_accuracy: 0.6739
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2645 - accuracy: 0.5766 - val_loss: 2.9347 - val_accuracy: 0.6739
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2416 - accuracy: 0.5693 - val_loss: 2.9230 - val_accuracy: 0.6848
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2092 - accuracy: 0.5839 - val_loss: 2.9120 - val_accuracy: 0.6957
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 3.2103 - accuracy: 0.5718 - val_loss: 2.9010 - val_accuracy: 0.7065
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2037 - accuracy: 0.5693 - val_loss: 2.8907 - val_accuracy: 0.7174
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1494 - accuracy: 0.6022 - val_loss: 2.8800 - val_accuracy: 0.7174
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1283 - accuracy: 0.5852 - val_loss: 2.8700 - val_accuracy: 0.7174
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1511 - accuracy: 0.6034 - val_loss: 2.8610 - val_accuracy: 0.7065
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1498 - accuracy: 0.5925 - val_loss: 2.8513 - val_accuracy: 0.7174
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1481 - accuracy: 0.6034 - val_loss: 2.8418 - val_accuracy: 0.7391
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0855 - accuracy: 0.6119 - val_loss: 2.8321 - val_accuracy: 0.7391
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1362 - accuracy: 0.6131 - val_loss: 2.8224 - val_accuracy: 0.7391
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1236 - accuracy: 0.6022 - val_loss: 2.8143 - val_accuracy: 0.7609
Epoch 50/100
7/7 [==============================] - 0s 12ms/step - loss: 3.1310 - accuracy: 0.5949 - val_loss: 2.8053 - val_accuracy: 0.7717
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0749 - accuracy: 0.5985 - val_loss: 2.7965 - val_accuracy: 0.7826
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0826 - accuracy: 0.6046 - val_loss: 2.7875 - val_accuracy: 0.7935
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0754 - accuracy: 0.6277 - val_loss: 2.7785 - val_accuracy: 0.7935
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0704 - accuracy: 0.6229 - val_loss: 2.7699 - val_accuracy: 0.7935
Epoch 55/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0837 - accuracy: 0.5985 - val_loss: 2.7613 - val_accuracy: 0.7935
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0444 - accuracy: 0.6411 - val_loss: 2.7531 - val_accuracy: 0.7935
Epoch 57/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0285 - accuracy: 0.6387 - val_loss: 2.7445 - val_accuracy: 0.7935
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0187 - accuracy: 0.6436 - val_loss: 2.7357 - val_accuracy: 0.7935
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0394 - accuracy: 0.5973 - val_loss: 2.7270 - val_accuracy: 0.7935
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0084 - accuracy: 0.6302 - val_loss: 2.7182 - val_accuracy: 0.7826
Epoch 61/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0031 - accuracy: 0.6168 - val_loss: 2.7099 - val_accuracy: 0.7826
Epoch 62/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0200 - accuracy: 0.6107 - val_loss: 2.7023 - val_accuracy: 0.7935
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9880 - accuracy: 0.6290 - val_loss: 2.6942 - val_accuracy: 0.7935
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9529 - accuracy: 0.6557 - val_loss: 2.6860 - val_accuracy: 0.7935
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9593 - accuracy: 0.6496 - val_loss: 2.6779 - val_accuracy: 0.7935
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9351 - accuracy: 0.6521 - val_loss: 2.6690 - val_accuracy: 0.7935
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9666 - accuracy: 0.6521 - val_loss: 2.6613 - val_accuracy: 0.7935
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9620 - accuracy: 0.6496 - val_loss: 2.6528 - val_accuracy: 0.7935
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9316 - accuracy: 0.6363 - val_loss: 2.6448 - val_accuracy: 0.7935
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8860 - accuracy: 0.6484 - val_loss: 2.6378 - val_accuracy: 0.7935
Epoch 71/100
7/7 [==============================] - 0s 11ms/step - loss: 2.9556 - accuracy: 0.6606 - val_loss: 2.6303 - val_accuracy: 0.7935
Epoch 72/100
7/7 [==============================] - 0s 11ms/step - loss: 2.9200 - accuracy: 0.6399 - val_loss: 2.6229 - val_accuracy: 0.8043
Epoch 73/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8790 - accuracy: 0.6569 - val_loss: 2.6161 - val_accuracy: 0.8043
Epoch 74/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9183 - accuracy: 0.6533 - val_loss: 2.6092 - val_accuracy: 0.8043
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9007 - accuracy: 0.6436 - val_loss: 2.6019 - val_accuracy: 0.8043
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8538 - accuracy: 0.7044 - val_loss: 2.5953 - val_accuracy: 0.8043
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8792 - accuracy: 0.6655 - val_loss: 2.5883 - val_accuracy: 0.8152
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8518 - accuracy: 0.6715 - val_loss: 2.5819 - val_accuracy: 0.8261
Epoch 79/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8562 - accuracy: 0.6776 - val_loss: 2.5751 - val_accuracy: 0.8261
Epoch 80/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8631 - accuracy: 0.6727 - val_loss: 2.5686 - val_accuracy: 0.8261
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8440 - accuracy: 0.6825 - val_loss: 2.5621 - val_accuracy: 0.8261
Epoch 82/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8222 - accuracy: 0.6764 - val_loss: 2.5557 - val_accuracy: 0.8261
Epoch 83/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8407 - accuracy: 0.6630 - val_loss: 2.5496 - val_accuracy: 0.8261
Epoch 84/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8055 - accuracy: 0.6946 - val_loss: 2.5435 - val_accuracy: 0.8261
Epoch 85/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8501 - accuracy: 0.6873 - val_loss: 2.5373 - val_accuracy: 0.8261
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8162 - accuracy: 0.6764 - val_loss: 2.5309 - val_accuracy: 0.8370
Epoch 87/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8115 - accuracy: 0.6849 - val_loss: 2.5248 - val_accuracy: 0.8370
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7858 - accuracy: 0.7092 - val_loss: 2.5194 - val_accuracy: 0.8370
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8082 - accuracy: 0.6788 - val_loss: 2.5133 - val_accuracy: 0.8370
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7675 - accuracy: 0.7007 - val_loss: 2.5075 - val_accuracy: 0.8370
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7707 - accuracy: 0.7092 - val_loss: 2.5016 - val_accuracy: 0.8478
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7442 - accuracy: 0.7202 - val_loss: 2.4961 - val_accuracy: 0.8587
Epoch 93/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7650 - accuracy: 0.7044 - val_loss: 2.4911 - val_accuracy: 0.8478
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7158 - accuracy: 0.7287 - val_loss: 2.4860 - val_accuracy: 0.8587
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7669 - accuracy: 0.7056 - val_loss: 2.4798 - val_accuracy: 0.8587
Epoch 96/100
7/7 [==============================] - 0s 11ms/step - loss: 2.7393 - accuracy: 0.7238 - val_loss: 2.4746 - val_accuracy: 0.8587
Epoch 97/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7474 - accuracy: 0.7007 - val_loss: 2.4693 - val_accuracy: 0.8587
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7371 - accuracy: 0.7287 - val_loss: 2.4642 - val_accuracy: 0.8696
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7389 - accuracy: 0.7165 - val_loss: 2.4591 - val_accuracy: 0.8804
Epoch 100/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7241 - accuracy: 0.7360 - val_loss: 2.4538 - val_accuracy: 0.8804
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 46ms/step - loss: 3.6319 - accuracy: 0.3925 - val_loss: 3.2242 - val_accuracy: 0.3736
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5748 - accuracy: 0.3961 - val_loss: 3.2204 - val_accuracy: 0.4066
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5806 - accuracy: 0.4022 - val_loss: 3.2157 - val_accuracy: 0.4066
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 3.5929 - accuracy: 0.3949 - val_loss: 3.2107 - val_accuracy: 0.4176
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5961 - accuracy: 0.4156 - val_loss: 3.2051 - val_accuracy: 0.4176
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6214 - accuracy: 0.4216 - val_loss: 3.1991 - val_accuracy: 0.4066
Epoch 7/100
7/7 [==============================] - 0s 10ms/step - loss: 3.5574 - accuracy: 0.4192 - val_loss: 3.1923 - val_accuracy: 0.4066
Epoch 8/100
7/7 [==============================] - 0s 11ms/step - loss: 3.6040 - accuracy: 0.3961 - val_loss: 3.1853 - val_accuracy: 0.4286
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5375 - accuracy: 0.4265 - val_loss: 3.1779 - val_accuracy: 0.4615
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5778 - accuracy: 0.3973 - val_loss: 3.1700 - val_accuracy: 0.4615
Epoch 11/100
7/7 [==============================] - 0s 10ms/step - loss: 3.5126 - accuracy: 0.3998 - val_loss: 3.1615 - val_accuracy: 0.4725
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4985 - accuracy: 0.4386 - val_loss: 3.1527 - val_accuracy: 0.4725
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4736 - accuracy: 0.4338 - val_loss: 3.1440 - val_accuracy: 0.4945
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4686 - accuracy: 0.4168 - val_loss: 3.1350 - val_accuracy: 0.5055
Epoch 15/100
7/7 [==============================] - 0s 11ms/step - loss: 3.4269 - accuracy: 0.4605 - val_loss: 3.1261 - val_accuracy: 0.5165
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4715 - accuracy: 0.4301 - val_loss: 3.1167 - val_accuracy: 0.5385
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4576 - accuracy: 0.4435 - val_loss: 3.1072 - val_accuracy: 0.5714
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4251 - accuracy: 0.4435 - val_loss: 3.0974 - val_accuracy: 0.5714
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3542 - accuracy: 0.4897 - val_loss: 3.0880 - val_accuracy: 0.5824
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4073 - accuracy: 0.4471 - val_loss: 3.0777 - val_accuracy: 0.6154
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3869 - accuracy: 0.4860 - val_loss: 3.0676 - val_accuracy: 0.6264
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3523 - accuracy: 0.4751 - val_loss: 3.0577 - val_accuracy: 0.6593
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3565 - accuracy: 0.4800 - val_loss: 3.0480 - val_accuracy: 0.6593
Epoch 24/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2930 - accuracy: 0.4824 - val_loss: 3.0382 - val_accuracy: 0.6703
Epoch 25/100
7/7 [==============================] - 0s 11ms/step - loss: 3.3206 - accuracy: 0.4921 - val_loss: 3.0285 - val_accuracy: 0.6813
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2518 - accuracy: 0.5140 - val_loss: 3.0188 - val_accuracy: 0.6923
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2740 - accuracy: 0.4970 - val_loss: 3.0092 - val_accuracy: 0.6923
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2743 - accuracy: 0.4848 - val_loss: 2.9994 - val_accuracy: 0.6923
Epoch 29/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2681 - accuracy: 0.5225 - val_loss: 2.9896 - val_accuracy: 0.6923
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2241 - accuracy: 0.5322 - val_loss: 2.9799 - val_accuracy: 0.6923
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2348 - accuracy: 0.5152 - val_loss: 2.9704 - val_accuracy: 0.7033
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1626 - accuracy: 0.5492 - val_loss: 2.9611 - val_accuracy: 0.7143
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2070 - accuracy: 0.5395 - val_loss: 2.9519 - val_accuracy: 0.7253
Epoch 34/100
7/7 [==============================] - 0s 10ms/step - loss: 3.2004 - accuracy: 0.5419 - val_loss: 2.9429 - val_accuracy: 0.7253
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1852 - accuracy: 0.5371 - val_loss: 2.9342 - val_accuracy: 0.7363
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2057 - accuracy: 0.5516 - val_loss: 2.9253 - val_accuracy: 0.7473
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1738 - accuracy: 0.5529 - val_loss: 2.9164 - val_accuracy: 0.7473
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1680 - accuracy: 0.5358 - val_loss: 2.9078 - val_accuracy: 0.7473
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1285 - accuracy: 0.5650 - val_loss: 2.8991 - val_accuracy: 0.7473
Epoch 40/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1018 - accuracy: 0.5565 - val_loss: 2.8906 - val_accuracy: 0.7582
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1485 - accuracy: 0.5699 - val_loss: 2.8826 - val_accuracy: 0.7692
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1533 - accuracy: 0.5383 - val_loss: 2.8743 - val_accuracy: 0.7692
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0895 - accuracy: 0.5759 - val_loss: 2.8662 - val_accuracy: 0.7692
Epoch 44/100
7/7 [==============================] - 0s 11ms/step - loss: 3.1400 - accuracy: 0.5589 - val_loss: 2.8583 - val_accuracy: 0.7692
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0945 - accuracy: 0.5638 - val_loss: 2.8503 - val_accuracy: 0.7692
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0691 - accuracy: 0.5759 - val_loss: 2.8422 - val_accuracy: 0.7692
Epoch 47/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0778 - accuracy: 0.5784 - val_loss: 2.8343 - val_accuracy: 0.7692
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0601 - accuracy: 0.5626 - val_loss: 2.8268 - val_accuracy: 0.7692
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0295 - accuracy: 0.6027 - val_loss: 2.8189 - val_accuracy: 0.7692
Epoch 50/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0512 - accuracy: 0.5869 - val_loss: 2.8111 - val_accuracy: 0.7692
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0265 - accuracy: 0.5808 - val_loss: 2.8036 - val_accuracy: 0.7692
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9851 - accuracy: 0.6185 - val_loss: 2.7963 - val_accuracy: 0.7692
Epoch 53/100
7/7 [==============================] - 0s 11ms/step - loss: 2.9992 - accuracy: 0.6063 - val_loss: 2.7887 - val_accuracy: 0.7692
Epoch 54/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9981 - accuracy: 0.6075 - val_loss: 2.7816 - val_accuracy: 0.7692
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9917 - accuracy: 0.6124 - val_loss: 2.7745 - val_accuracy: 0.7692
Epoch 56/100
7/7 [==============================] - 0s 11ms/step - loss: 2.9849 - accuracy: 0.5990 - val_loss: 2.7678 - val_accuracy: 0.7692
Epoch 57/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9595 - accuracy: 0.6136 - val_loss: 2.7608 - val_accuracy: 0.7692
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0054 - accuracy: 0.5917 - val_loss: 2.7538 - val_accuracy: 0.7692
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9825 - accuracy: 0.6136 - val_loss: 2.7471 - val_accuracy: 0.7692
Epoch 60/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9538 - accuracy: 0.6233 - val_loss: 2.7405 - val_accuracy: 0.7692
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9366 - accuracy: 0.6343 - val_loss: 2.7335 - val_accuracy: 0.7802
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9349 - accuracy: 0.6343 - val_loss: 2.7268 - val_accuracy: 0.7802
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9364 - accuracy: 0.6403 - val_loss: 2.7201 - val_accuracy: 0.7912
Epoch 64/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9060 - accuracy: 0.6245 - val_loss: 2.7136 - val_accuracy: 0.7912
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9438 - accuracy: 0.6160 - val_loss: 2.7069 - val_accuracy: 0.7912
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9287 - accuracy: 0.6306 - val_loss: 2.7003 - val_accuracy: 0.8022
Epoch 67/100
7/7 [==============================] - 0s 6ms/step - loss: 2.8721 - accuracy: 0.6525 - val_loss: 2.6935 - val_accuracy: 0.8022
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8923 - accuracy: 0.6379 - val_loss: 2.6868 - val_accuracy: 0.8022
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9357 - accuracy: 0.6343 - val_loss: 2.6803 - val_accuracy: 0.8022
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8902 - accuracy: 0.6428 - val_loss: 2.6742 - val_accuracy: 0.8022
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8913 - accuracy: 0.6343 - val_loss: 2.6675 - val_accuracy: 0.8022
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8983 - accuracy: 0.6452 - val_loss: 2.6612 - val_accuracy: 0.8022
Epoch 73/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8879 - accuracy: 0.6513 - val_loss: 2.6550 - val_accuracy: 0.8022
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8726 - accuracy: 0.6440 - val_loss: 2.6488 - val_accuracy: 0.8022
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8850 - accuracy: 0.6464 - val_loss: 2.6424 - val_accuracy: 0.8132
Epoch 76/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8153 - accuracy: 0.6792 - val_loss: 2.6365 - val_accuracy: 0.8132
Epoch 77/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8213 - accuracy: 0.6586 - val_loss: 2.6305 - val_accuracy: 0.8242
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8273 - accuracy: 0.6780 - val_loss: 2.6244 - val_accuracy: 0.8242
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8326 - accuracy: 0.6646 - val_loss: 2.6184 - val_accuracy: 0.8242
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8195 - accuracy: 0.6646 - val_loss: 2.6127 - val_accuracy: 0.8242
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7783 - accuracy: 0.6987 - val_loss: 2.6068 - val_accuracy: 0.8242
Epoch 82/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7806 - accuracy: 0.7011 - val_loss: 2.6012 - val_accuracy: 0.8242
Epoch 83/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8050 - accuracy: 0.6610 - val_loss: 2.5952 - val_accuracy: 0.8242
Epoch 84/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7938 - accuracy: 0.6792 - val_loss: 2.5895 - val_accuracy: 0.8242
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7675 - accuracy: 0.6877 - val_loss: 2.5837 - val_accuracy: 0.8242
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7585 - accuracy: 0.7060 - val_loss: 2.5778 - val_accuracy: 0.8242
Epoch 87/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7495 - accuracy: 0.6987 - val_loss: 2.5720 - val_accuracy: 0.8242
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7828 - accuracy: 0.6780 - val_loss: 2.5666 - val_accuracy: 0.8132
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8256 - accuracy: 0.6634 - val_loss: 2.5611 - val_accuracy: 0.8132
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7219 - accuracy: 0.6987 - val_loss: 2.5559 - val_accuracy: 0.8352
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7258 - accuracy: 0.6926 - val_loss: 2.5508 - val_accuracy: 0.8242
Epoch 92/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7484 - accuracy: 0.6950 - val_loss: 2.5454 - val_accuracy: 0.8242
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7462 - accuracy: 0.6841 - val_loss: 2.5400 - val_accuracy: 0.8242
Epoch 94/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7273 - accuracy: 0.7132 - val_loss: 2.5349 - val_accuracy: 0.8242
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6813 - accuracy: 0.7278 - val_loss: 2.5297 - val_accuracy: 0.8352
Epoch 96/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7353 - accuracy: 0.6999 - val_loss: 2.5244 - val_accuracy: 0.8352
Epoch 97/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7293 - accuracy: 0.6756 - val_loss: 2.5190 - val_accuracy: 0.8352
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7065 - accuracy: 0.7254 - val_loss: 2.5140 - val_accuracy: 0.8352
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6981 - accuracy: 0.7120 - val_loss: 2.5087 - val_accuracy: 0.8352
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6709 - accuracy: 0.7436 - val_loss: 2.5037 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 7ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 45ms/step - loss: 3.8405 - accuracy: 0.3147 - val_loss: 3.2801 - val_accuracy: 0.2747
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8058 - accuracy: 0.3123 - val_loss: 3.2802 - val_accuracy: 0.2747
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 3.9317 - accuracy: 0.3050 - val_loss: 3.2786 - val_accuracy: 0.2747
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8104 - accuracy: 0.3572 - val_loss: 3.2762 - val_accuracy: 0.2967
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8224 - accuracy: 0.3329 - val_loss: 3.2727 - val_accuracy: 0.3077
Epoch 6/100
7/7 [==============================] - 0s 6ms/step - loss: 3.7570 - accuracy: 0.3269 - val_loss: 3.2684 - val_accuracy: 0.3297
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7203 - accuracy: 0.3378 - val_loss: 3.2630 - val_accuracy: 0.3407
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6791 - accuracy: 0.3742 - val_loss: 3.2567 - val_accuracy: 0.3516
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7316 - accuracy: 0.3609 - val_loss: 3.2496 - val_accuracy: 0.3516
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6392 - accuracy: 0.3755 - val_loss: 3.2418 - val_accuracy: 0.3626
Epoch 11/100
7/7 [==============================] - 0s 11ms/step - loss: 3.5948 - accuracy: 0.4022 - val_loss: 3.2331 - val_accuracy: 0.3956
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 3.5857 - accuracy: 0.3852 - val_loss: 3.2237 - val_accuracy: 0.3956
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5123 - accuracy: 0.4168 - val_loss: 3.2139 - val_accuracy: 0.3956
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5610 - accuracy: 0.4228 - val_loss: 3.2034 - val_accuracy: 0.4176
Epoch 15/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5263 - accuracy: 0.4253 - val_loss: 3.1924 - val_accuracy: 0.4396
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4934 - accuracy: 0.4070 - val_loss: 3.1810 - val_accuracy: 0.4615
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5224 - accuracy: 0.4362 - val_loss: 3.1694 - val_accuracy: 0.4835
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4221 - accuracy: 0.4666 - val_loss: 3.1575 - val_accuracy: 0.5165
Epoch 19/100
7/7 [==============================] - 0s 10ms/step - loss: 3.4054 - accuracy: 0.4326 - val_loss: 3.1455 - val_accuracy: 0.5495
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4177 - accuracy: 0.4605 - val_loss: 3.1331 - val_accuracy: 0.5604
Epoch 21/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3912 - accuracy: 0.4739 - val_loss: 3.1213 - val_accuracy: 0.5934
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3697 - accuracy: 0.4836 - val_loss: 3.1090 - val_accuracy: 0.6044
Epoch 23/100
7/7 [==============================] - 0s 7ms/step - loss: 3.3440 - accuracy: 0.5164 - val_loss: 3.0971 - val_accuracy: 0.6264
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3322 - accuracy: 0.5261 - val_loss: 3.0852 - val_accuracy: 0.6484
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2928 - accuracy: 0.5237 - val_loss: 3.0737 - val_accuracy: 0.6484
Epoch 26/100
7/7 [==============================] - 0s 11ms/step - loss: 3.3437 - accuracy: 0.5030 - val_loss: 3.0617 - val_accuracy: 0.6484
Epoch 27/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2749 - accuracy: 0.5310 - val_loss: 3.0505 - val_accuracy: 0.6703
Epoch 28/100
7/7 [==============================] - 0s 10ms/step - loss: 3.2585 - accuracy: 0.5273 - val_loss: 3.0393 - val_accuracy: 0.6703
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2909 - accuracy: 0.5516 - val_loss: 3.0280 - val_accuracy: 0.6703
Epoch 30/100
7/7 [==============================] - 0s 7ms/step - loss: 3.2488 - accuracy: 0.5614 - val_loss: 3.0170 - val_accuracy: 0.6923
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1735 - accuracy: 0.5820 - val_loss: 3.0065 - val_accuracy: 0.6923
Epoch 32/100
7/7 [==============================] - 0s 11ms/step - loss: 3.1624 - accuracy: 0.5942 - val_loss: 2.9961 - val_accuracy: 0.6923
Epoch 33/100
7/7 [==============================] - 0s 10ms/step - loss: 3.2383 - accuracy: 0.5723 - val_loss: 2.9860 - val_accuracy: 0.6923
Epoch 34/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2111 - accuracy: 0.5784 - val_loss: 2.9757 - val_accuracy: 0.7033
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1984 - accuracy: 0.5966 - val_loss: 2.9656 - val_accuracy: 0.7033
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1472 - accuracy: 0.6075 - val_loss: 2.9562 - val_accuracy: 0.7143
Epoch 37/100
7/7 [==============================] - 0s 10ms/step - loss: 3.1713 - accuracy: 0.5954 - val_loss: 2.9473 - val_accuracy: 0.7143
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1535 - accuracy: 0.6039 - val_loss: 2.9388 - val_accuracy: 0.7253
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1353 - accuracy: 0.6124 - val_loss: 2.9296 - val_accuracy: 0.7253
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1254 - accuracy: 0.6136 - val_loss: 2.9210 - val_accuracy: 0.7143
Epoch 41/100
7/7 [==============================] - 0s 10ms/step - loss: 3.1399 - accuracy: 0.6002 - val_loss: 2.9125 - val_accuracy: 0.7143
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1420 - accuracy: 0.6063 - val_loss: 2.9042 - val_accuracy: 0.7143
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1435 - accuracy: 0.6112 - val_loss: 2.8958 - val_accuracy: 0.7253
Epoch 44/100
7/7 [==============================] - 0s 11ms/step - loss: 3.1191 - accuracy: 0.6355 - val_loss: 2.8880 - val_accuracy: 0.7253
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1148 - accuracy: 0.6197 - val_loss: 2.8801 - val_accuracy: 0.7253
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1192 - accuracy: 0.6087 - val_loss: 2.8723 - val_accuracy: 0.7253
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0809 - accuracy: 0.6549 - val_loss: 2.8649 - val_accuracy: 0.7143
Epoch 48/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0808 - accuracy: 0.6270 - val_loss: 2.8572 - val_accuracy: 0.7143
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0396 - accuracy: 0.6440 - val_loss: 2.8496 - val_accuracy: 0.7143
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0462 - accuracy: 0.6537 - val_loss: 2.8424 - val_accuracy: 0.7253
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0343 - accuracy: 0.6634 - val_loss: 2.8354 - val_accuracy: 0.7363
Epoch 52/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0577 - accuracy: 0.6258 - val_loss: 2.8286 - val_accuracy: 0.7473
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9945 - accuracy: 0.6452 - val_loss: 2.8212 - val_accuracy: 0.7473
Epoch 54/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0062 - accuracy: 0.6355 - val_loss: 2.8144 - val_accuracy: 0.7582
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9994 - accuracy: 0.6683 - val_loss: 2.8075 - val_accuracy: 0.7582
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0411 - accuracy: 0.6330 - val_loss: 2.8008 - val_accuracy: 0.7692
Epoch 57/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9667 - accuracy: 0.6707 - val_loss: 2.7944 - val_accuracy: 0.7692
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9953 - accuracy: 0.6561 - val_loss: 2.7875 - val_accuracy: 0.7692
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0052 - accuracy: 0.6318 - val_loss: 2.7810 - val_accuracy: 0.7582
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9683 - accuracy: 0.6391 - val_loss: 2.7744 - val_accuracy: 0.7582
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9506 - accuracy: 0.6598 - val_loss: 2.7682 - val_accuracy: 0.7582
Epoch 62/100
7/7 [==============================] - 0s 6ms/step - loss: 2.9673 - accuracy: 0.6817 - val_loss: 2.7626 - val_accuracy: 0.7582
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9322 - accuracy: 0.6792 - val_loss: 2.7569 - val_accuracy: 0.7582
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9382 - accuracy: 0.6817 - val_loss: 2.7507 - val_accuracy: 0.7582
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9303 - accuracy: 0.6634 - val_loss: 2.7447 - val_accuracy: 0.7692
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9092 - accuracy: 0.6817 - val_loss: 2.7389 - val_accuracy: 0.7802
Epoch 67/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8976 - accuracy: 0.6829 - val_loss: 2.7330 - val_accuracy: 0.7802
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8522 - accuracy: 0.7011 - val_loss: 2.7269 - val_accuracy: 0.7802
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8583 - accuracy: 0.6804 - val_loss: 2.7211 - val_accuracy: 0.7802
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8634 - accuracy: 0.6914 - val_loss: 2.7154 - val_accuracy: 0.7802
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8393 - accuracy: 0.6902 - val_loss: 2.7099 - val_accuracy: 0.7802
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8922 - accuracy: 0.6731 - val_loss: 2.7047 - val_accuracy: 0.7912
Epoch 73/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8452 - accuracy: 0.6889 - val_loss: 2.6993 - val_accuracy: 0.7912
Epoch 74/100
7/7 [==============================] - 0s 12ms/step - loss: 2.8572 - accuracy: 0.7108 - val_loss: 2.6935 - val_accuracy: 0.7912
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8616 - accuracy: 0.6768 - val_loss: 2.6880 - val_accuracy: 0.7912
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8729 - accuracy: 0.6841 - val_loss: 2.6827 - val_accuracy: 0.7912
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8524 - accuracy: 0.6902 - val_loss: 2.6774 - val_accuracy: 0.7912
Epoch 78/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8110 - accuracy: 0.7254 - val_loss: 2.6717 - val_accuracy: 0.7912
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8337 - accuracy: 0.7072 - val_loss: 2.6664 - val_accuracy: 0.8022
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8068 - accuracy: 0.6974 - val_loss: 2.6616 - val_accuracy: 0.8022
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7819 - accuracy: 0.7096 - val_loss: 2.6570 - val_accuracy: 0.8022
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8247 - accuracy: 0.7035 - val_loss: 2.6517 - val_accuracy: 0.8022
Epoch 83/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7960 - accuracy: 0.7181 - val_loss: 2.6464 - val_accuracy: 0.8132
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8034 - accuracy: 0.6962 - val_loss: 2.6415 - val_accuracy: 0.8242
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8039 - accuracy: 0.7157 - val_loss: 2.6360 - val_accuracy: 0.8352
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7847 - accuracy: 0.7011 - val_loss: 2.6310 - val_accuracy: 0.8352
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7806 - accuracy: 0.7205 - val_loss: 2.6259 - val_accuracy: 0.8352
Epoch 88/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7593 - accuracy: 0.7193 - val_loss: 2.6208 - val_accuracy: 0.8352
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7880 - accuracy: 0.7266 - val_loss: 2.6156 - val_accuracy: 0.8352
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7510 - accuracy: 0.7327 - val_loss: 2.6105 - val_accuracy: 0.8352
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7418 - accuracy: 0.7388 - val_loss: 2.6055 - val_accuracy: 0.8352
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7328 - accuracy: 0.7485 - val_loss: 2.6000 - val_accuracy: 0.8352
Epoch 93/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7627 - accuracy: 0.7461 - val_loss: 2.5953 - val_accuracy: 0.8352
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7080 - accuracy: 0.7363 - val_loss: 2.5902 - val_accuracy: 0.8352
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7082 - accuracy: 0.7533 - val_loss: 2.5849 - val_accuracy: 0.8352
Epoch 96/100
7/7 [==============================] - 0s 11ms/step - loss: 2.7008 - accuracy: 0.7363 - val_loss: 2.5796 - val_accuracy: 0.8352
Epoch 97/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6863 - accuracy: 0.7546 - val_loss: 2.5750 - val_accuracy: 0.8352
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7112 - accuracy: 0.7485 - val_loss: 2.5707 - val_accuracy: 0.8462
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6830 - accuracy: 0.7485 - val_loss: 2.5658 - val_accuracy: 0.8462
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6867 - accuracy: 0.7533 - val_loss: 2.5613 - val_accuracy: 0.8462
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 44ms/step - loss: 3.9697 - accuracy: 0.2649 - val_loss: 3.1982 - val_accuracy: 0.3516
Epoch 2/100
7/7 [==============================] - 0s 11ms/step - loss: 3.9747 - accuracy: 0.2491 - val_loss: 3.2007 - val_accuracy: 0.3516
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 3.9073 - accuracy: 0.2515 - val_loss: 3.2025 - val_accuracy: 0.3407
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 3.9244 - accuracy: 0.2442 - val_loss: 3.2032 - val_accuracy: 0.3297
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 3.9090 - accuracy: 0.2479 - val_loss: 3.2023 - val_accuracy: 0.3516
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8521 - accuracy: 0.2527 - val_loss: 3.2001 - val_accuracy: 0.3626
Epoch 7/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8271 - accuracy: 0.2491 - val_loss: 3.1969 - val_accuracy: 0.3407
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7676 - accuracy: 0.2588 - val_loss: 3.1926 - val_accuracy: 0.3626
Epoch 9/100
7/7 [==============================] - 0s 10ms/step - loss: 3.8113 - accuracy: 0.2783 - val_loss: 3.1875 - val_accuracy: 0.3626
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7385 - accuracy: 0.2770 - val_loss: 3.1813 - val_accuracy: 0.3407
Epoch 11/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6195 - accuracy: 0.3038 - val_loss: 3.1742 - val_accuracy: 0.3736
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6637 - accuracy: 0.3098 - val_loss: 3.1667 - val_accuracy: 0.3846
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6101 - accuracy: 0.3111 - val_loss: 3.1584 - val_accuracy: 0.4066
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5940 - accuracy: 0.3013 - val_loss: 3.1495 - val_accuracy: 0.4066
Epoch 15/100
7/7 [==============================] - 0s 11ms/step - loss: 3.5378 - accuracy: 0.3341 - val_loss: 3.1402 - val_accuracy: 0.4505
Epoch 16/100
7/7 [==============================] - 0s 7ms/step - loss: 3.4964 - accuracy: 0.3560 - val_loss: 3.1305 - val_accuracy: 0.4835
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4905 - accuracy: 0.3572 - val_loss: 3.1207 - val_accuracy: 0.5604
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4692 - accuracy: 0.3645 - val_loss: 3.1108 - val_accuracy: 0.5495
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4173 - accuracy: 0.3852 - val_loss: 3.1010 - val_accuracy: 0.5604
Epoch 20/100
7/7 [==============================] - 0s 7ms/step - loss: 3.3664 - accuracy: 0.4083 - val_loss: 3.0911 - val_accuracy: 0.5604
Epoch 21/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4218 - accuracy: 0.4362 - val_loss: 3.0814 - val_accuracy: 0.5604
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3447 - accuracy: 0.4435 - val_loss: 3.0716 - val_accuracy: 0.5824
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3562 - accuracy: 0.4241 - val_loss: 3.0621 - val_accuracy: 0.6044
Epoch 24/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2750 - accuracy: 0.4909 - val_loss: 3.0525 - val_accuracy: 0.5934
Epoch 25/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3334 - accuracy: 0.4909 - val_loss: 3.0435 - val_accuracy: 0.5714
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3070 - accuracy: 0.4678 - val_loss: 3.0344 - val_accuracy: 0.5714
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3114 - accuracy: 0.4885 - val_loss: 3.0256 - val_accuracy: 0.5824
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2883 - accuracy: 0.5200 - val_loss: 3.0172 - val_accuracy: 0.5934
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2217 - accuracy: 0.5346 - val_loss: 3.0090 - val_accuracy: 0.5934
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2630 - accuracy: 0.5225 - val_loss: 3.0005 - val_accuracy: 0.6264
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2541 - accuracy: 0.5334 - val_loss: 2.9924 - val_accuracy: 0.6374
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2503 - accuracy: 0.5164 - val_loss: 2.9847 - val_accuracy: 0.6593
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1886 - accuracy: 0.5553 - val_loss: 2.9766 - val_accuracy: 0.6703
Epoch 34/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2386 - accuracy: 0.5456 - val_loss: 2.9692 - val_accuracy: 0.6703
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2183 - accuracy: 0.5286 - val_loss: 2.9617 - val_accuracy: 0.6703
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1968 - accuracy: 0.5541 - val_loss: 2.9541 - val_accuracy: 0.6703
Epoch 37/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1872 - accuracy: 0.5504 - val_loss: 2.9471 - val_accuracy: 0.6813
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1834 - accuracy: 0.5723 - val_loss: 2.9396 - val_accuracy: 0.6923
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1323 - accuracy: 0.5529 - val_loss: 2.9319 - val_accuracy: 0.6923
Epoch 40/100
7/7 [==============================] - 0s 11ms/step - loss: 3.1697 - accuracy: 0.5529 - val_loss: 2.9246 - val_accuracy: 0.6923
Epoch 41/100
7/7 [==============================] - 0s 10ms/step - loss: 3.1612 - accuracy: 0.5614 - val_loss: 2.9170 - val_accuracy: 0.6923
Epoch 42/100
7/7 [==============================] - 0s 7ms/step - loss: 3.1229 - accuracy: 0.5820 - val_loss: 2.9096 - val_accuracy: 0.7033
Epoch 43/100
7/7 [==============================] - 0s 7ms/step - loss: 3.1840 - accuracy: 0.5662 - val_loss: 2.9022 - val_accuracy: 0.7033
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1413 - accuracy: 0.5650 - val_loss: 2.8946 - val_accuracy: 0.7033
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1056 - accuracy: 0.5942 - val_loss: 2.8873 - val_accuracy: 0.7033
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0806 - accuracy: 0.5917 - val_loss: 2.8796 - val_accuracy: 0.7033
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0700 - accuracy: 0.5978 - val_loss: 2.8722 - val_accuracy: 0.6923
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0695 - accuracy: 0.5808 - val_loss: 2.8648 - val_accuracy: 0.6923
Epoch 49/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0455 - accuracy: 0.5905 - val_loss: 2.8576 - val_accuracy: 0.6923
Epoch 50/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0756 - accuracy: 0.5784 - val_loss: 2.8500 - val_accuracy: 0.6923
Epoch 51/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0351 - accuracy: 0.6039 - val_loss: 2.8425 - val_accuracy: 0.7033
Epoch 52/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0283 - accuracy: 0.5966 - val_loss: 2.8349 - val_accuracy: 0.7033
Epoch 53/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0227 - accuracy: 0.5917 - val_loss: 2.8277 - val_accuracy: 0.7143
Epoch 54/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0124 - accuracy: 0.6100 - val_loss: 2.8206 - val_accuracy: 0.7143
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0168 - accuracy: 0.5942 - val_loss: 2.8131 - val_accuracy: 0.7143
Epoch 56/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9973 - accuracy: 0.6136 - val_loss: 2.8063 - val_accuracy: 0.7253
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9771 - accuracy: 0.6075 - val_loss: 2.7988 - val_accuracy: 0.7253
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9883 - accuracy: 0.6294 - val_loss: 2.7915 - val_accuracy: 0.7143
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9489 - accuracy: 0.6270 - val_loss: 2.7840 - val_accuracy: 0.7143
Epoch 60/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9899 - accuracy: 0.5978 - val_loss: 2.7771 - val_accuracy: 0.7253
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9831 - accuracy: 0.6233 - val_loss: 2.7701 - val_accuracy: 0.7253
Epoch 62/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9268 - accuracy: 0.6245 - val_loss: 2.7628 - val_accuracy: 0.7253
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9438 - accuracy: 0.6173 - val_loss: 2.7563 - val_accuracy: 0.7253
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8871 - accuracy: 0.6464 - val_loss: 2.7495 - val_accuracy: 0.7253
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9060 - accuracy: 0.6416 - val_loss: 2.7426 - val_accuracy: 0.7253
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9005 - accuracy: 0.6428 - val_loss: 2.7360 - val_accuracy: 0.7253
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9017 - accuracy: 0.6379 - val_loss: 2.7290 - val_accuracy: 0.7253
Epoch 68/100
7/7 [==============================] - 0s 11ms/step - loss: 2.9081 - accuracy: 0.6355 - val_loss: 2.7222 - val_accuracy: 0.7253
Epoch 69/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8945 - accuracy: 0.6452 - val_loss: 2.7155 - val_accuracy: 0.7253
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8285 - accuracy: 0.6695 - val_loss: 2.7086 - val_accuracy: 0.7253
Epoch 71/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8909 - accuracy: 0.6379 - val_loss: 2.7019 - val_accuracy: 0.7363
Epoch 72/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8233 - accuracy: 0.6574 - val_loss: 2.6948 - val_accuracy: 0.7363
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8556 - accuracy: 0.6513 - val_loss: 2.6886 - val_accuracy: 0.7363
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8284 - accuracy: 0.6428 - val_loss: 2.6818 - val_accuracy: 0.7582
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8131 - accuracy: 0.6646 - val_loss: 2.6753 - val_accuracy: 0.7582
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8067 - accuracy: 0.6561 - val_loss: 2.6687 - val_accuracy: 0.7582
Epoch 77/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8183 - accuracy: 0.6574 - val_loss: 2.6625 - val_accuracy: 0.7912
Epoch 78/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7880 - accuracy: 0.6719 - val_loss: 2.6560 - val_accuracy: 0.8022
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8061 - accuracy: 0.6768 - val_loss: 2.6496 - val_accuracy: 0.8022
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7816 - accuracy: 0.6780 - val_loss: 2.6433 - val_accuracy: 0.8132
Epoch 81/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8247 - accuracy: 0.6646 - val_loss: 2.6377 - val_accuracy: 0.8132
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8112 - accuracy: 0.6476 - val_loss: 2.6319 - val_accuracy: 0.8132
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7556 - accuracy: 0.6877 - val_loss: 2.6264 - val_accuracy: 0.8132
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7512 - accuracy: 0.6987 - val_loss: 2.6205 - val_accuracy: 0.8132
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7610 - accuracy: 0.6780 - val_loss: 2.6156 - val_accuracy: 0.8132
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7541 - accuracy: 0.6841 - val_loss: 2.6099 - val_accuracy: 0.8132
Epoch 87/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7219 - accuracy: 0.7181 - val_loss: 2.6042 - val_accuracy: 0.8132
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7397 - accuracy: 0.6768 - val_loss: 2.5995 - val_accuracy: 0.8132
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7142 - accuracy: 0.7169 - val_loss: 2.5942 - val_accuracy: 0.8132
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7227 - accuracy: 0.7060 - val_loss: 2.5888 - val_accuracy: 0.8132
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7206 - accuracy: 0.7157 - val_loss: 2.5838 - val_accuracy: 0.8132
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7190 - accuracy: 0.6999 - val_loss: 2.5785 - val_accuracy: 0.8132
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6629 - accuracy: 0.7375 - val_loss: 2.5728 - val_accuracy: 0.8132
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7007 - accuracy: 0.7193 - val_loss: 2.5673 - val_accuracy: 0.8242
Epoch 95/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6984 - accuracy: 0.7011 - val_loss: 2.5621 - val_accuracy: 0.8242
Epoch 96/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6801 - accuracy: 0.7035 - val_loss: 2.5569 - val_accuracy: 0.8242
Epoch 97/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6710 - accuracy: 0.7375 - val_loss: 2.5518 - val_accuracy: 0.8242
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6644 - accuracy: 0.7290 - val_loss: 2.5467 - val_accuracy: 0.8242
Epoch 99/100
7/7 [==============================] - 0s 13ms/step - loss: 2.6547 - accuracy: 0.7497 - val_loss: 2.5414 - val_accuracy: 0.8242
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6597 - accuracy: 0.7254 - val_loss: 2.5359 - val_accuracy: 0.8242
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 44ms/step - loss: 4.3033 - accuracy: 0.3524 - val_loss: 3.4923 - val_accuracy: 0.2308
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 4.2998 - accuracy: 0.3560 - val_loss: 3.4853 - val_accuracy: 0.2308
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 4.2409 - accuracy: 0.3706 - val_loss: 3.4778 - val_accuracy: 0.2418
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 4.2530 - accuracy: 0.3597 - val_loss: 3.4700 - val_accuracy: 0.2418
Epoch 5/100
7/7 [==============================] - 0s 11ms/step - loss: 4.2436 - accuracy: 0.3475 - val_loss: 3.4614 - val_accuracy: 0.2527
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 4.1758 - accuracy: 0.3730 - val_loss: 3.4523 - val_accuracy: 0.2967
Epoch 7/100
7/7 [==============================] - 0s 10ms/step - loss: 4.1011 - accuracy: 0.3937 - val_loss: 3.4432 - val_accuracy: 0.2967
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 4.0827 - accuracy: 0.3852 - val_loss: 3.4337 - val_accuracy: 0.3077
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 4.0536 - accuracy: 0.3900 - val_loss: 3.4238 - val_accuracy: 0.3187
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 4.0149 - accuracy: 0.4010 - val_loss: 3.4136 - val_accuracy: 0.3297
Epoch 11/100
7/7 [==============================] - 0s 11ms/step - loss: 3.9752 - accuracy: 0.4216 - val_loss: 3.4033 - val_accuracy: 0.3297
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 3.9406 - accuracy: 0.4095 - val_loss: 3.3934 - val_accuracy: 0.3626
Epoch 13/100
7/7 [==============================] - 0s 7ms/step - loss: 3.9042 - accuracy: 0.4046 - val_loss: 3.3829 - val_accuracy: 0.3626
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7840 - accuracy: 0.4399 - val_loss: 3.3726 - val_accuracy: 0.3956
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7448 - accuracy: 0.4326 - val_loss: 3.3624 - val_accuracy: 0.4066
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7403 - accuracy: 0.4593 - val_loss: 3.3525 - val_accuracy: 0.4396
Epoch 17/100
7/7 [==============================] - 0s 11ms/step - loss: 3.6732 - accuracy: 0.4617 - val_loss: 3.3427 - val_accuracy: 0.4615
Epoch 18/100
7/7 [==============================] - 0s 10ms/step - loss: 3.5935 - accuracy: 0.4775 - val_loss: 3.3335 - val_accuracy: 0.4505
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5884 - accuracy: 0.4836 - val_loss: 3.3241 - val_accuracy: 0.4396
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5192 - accuracy: 0.5140 - val_loss: 3.3153 - val_accuracy: 0.4505
Epoch 21/100
7/7 [==============================] - 0s 11ms/step - loss: 3.5696 - accuracy: 0.5091 - val_loss: 3.3067 - val_accuracy: 0.4615
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4738 - accuracy: 0.4982 - val_loss: 3.2986 - val_accuracy: 0.4725
Epoch 23/100
7/7 [==============================] - 0s 11ms/step - loss: 3.4418 - accuracy: 0.5091 - val_loss: 3.2912 - val_accuracy: 0.4615
Epoch 24/100
7/7 [==============================] - 0s 11ms/step - loss: 3.4664 - accuracy: 0.5030 - val_loss: 3.2847 - val_accuracy: 0.4615
Epoch 25/100
7/7 [==============================] - 0s 11ms/step - loss: 3.4383 - accuracy: 0.5273 - val_loss: 3.2783 - val_accuracy: 0.4615
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4290 - accuracy: 0.5225 - val_loss: 3.2726 - val_accuracy: 0.4725
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4107 - accuracy: 0.5383 - val_loss: 3.2680 - val_accuracy: 0.4835
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4244 - accuracy: 0.5310 - val_loss: 3.2640 - val_accuracy: 0.5055
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4072 - accuracy: 0.5213 - val_loss: 3.2603 - val_accuracy: 0.5385
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3908 - accuracy: 0.5431 - val_loss: 3.2567 - val_accuracy: 0.5495
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4013 - accuracy: 0.5395 - val_loss: 3.2534 - val_accuracy: 0.5495
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3299 - accuracy: 0.5443 - val_loss: 3.2498 - val_accuracy: 0.5495
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2894 - accuracy: 0.5784 - val_loss: 3.2478 - val_accuracy: 0.5604
Epoch 34/100
7/7 [==============================] - 0s 6ms/step - loss: 3.2954 - accuracy: 0.5772 - val_loss: 3.2464 - val_accuracy: 0.5604
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2985 - accuracy: 0.5747 - val_loss: 3.2443 - val_accuracy: 0.5604
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2999 - accuracy: 0.5419 - val_loss: 3.2430 - val_accuracy: 0.5604
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2868 - accuracy: 0.5699 - val_loss: 3.2413 - val_accuracy: 0.5604
Epoch 38/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2788 - accuracy: 0.5893 - val_loss: 3.2401 - val_accuracy: 0.5604
Epoch 39/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2442 - accuracy: 0.5857 - val_loss: 3.2388 - val_accuracy: 0.5604
Epoch 40/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2705 - accuracy: 0.5772 - val_loss: 3.2371 - val_accuracy: 0.5714
Epoch 41/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2494 - accuracy: 0.5844 - val_loss: 3.2363 - val_accuracy: 0.5714
Epoch 42/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2729 - accuracy: 0.6002 - val_loss: 3.2353 - val_accuracy: 0.5714
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2176 - accuracy: 0.5820 - val_loss: 3.2335 - val_accuracy: 0.5714
Epoch 44/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2222 - accuracy: 0.5844 - val_loss: 3.2319 - val_accuracy: 0.5714
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2138 - accuracy: 0.5954 - val_loss: 3.2306 - val_accuracy: 0.5714
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1740 - accuracy: 0.6173 - val_loss: 3.2290 - val_accuracy: 0.5714
Epoch 47/100
7/7 [==============================] - 0s 11ms/step - loss: 3.2030 - accuracy: 0.5978 - val_loss: 3.2267 - val_accuracy: 0.5604
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1510 - accuracy: 0.6075 - val_loss: 3.2237 - val_accuracy: 0.5604
Epoch 49/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1361 - accuracy: 0.6051 - val_loss: 3.2201 - val_accuracy: 0.5604
Epoch 50/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1277 - accuracy: 0.6221 - val_loss: 3.2168 - val_accuracy: 0.5604
Epoch 51/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0997 - accuracy: 0.6330 - val_loss: 3.2121 - val_accuracy: 0.5604
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1099 - accuracy: 0.5978 - val_loss: 3.2072 - val_accuracy: 0.5714
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1160 - accuracy: 0.6367 - val_loss: 3.2021 - val_accuracy: 0.5714
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1133 - accuracy: 0.6112 - val_loss: 3.1975 - val_accuracy: 0.5714
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0761 - accuracy: 0.6282 - val_loss: 3.1923 - val_accuracy: 0.5604
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0988 - accuracy: 0.6270 - val_loss: 3.1872 - val_accuracy: 0.5604
Epoch 57/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0761 - accuracy: 0.6100 - val_loss: 3.1818 - val_accuracy: 0.5604
Epoch 58/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0772 - accuracy: 0.6209 - val_loss: 3.1759 - val_accuracy: 0.5604
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1031 - accuracy: 0.6282 - val_loss: 3.1697 - val_accuracy: 0.5604
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0018 - accuracy: 0.6659 - val_loss: 3.1632 - val_accuracy: 0.5604
Epoch 61/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0451 - accuracy: 0.6379 - val_loss: 3.1562 - val_accuracy: 0.5604
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0428 - accuracy: 0.6403 - val_loss: 3.1491 - val_accuracy: 0.5604
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9650 - accuracy: 0.6695 - val_loss: 3.1409 - val_accuracy: 0.5604
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0285 - accuracy: 0.6379 - val_loss: 3.1327 - val_accuracy: 0.5714
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0250 - accuracy: 0.6379 - val_loss: 3.1247 - val_accuracy: 0.5714
Epoch 66/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9998 - accuracy: 0.6428 - val_loss: 3.1159 - val_accuracy: 0.5824
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9878 - accuracy: 0.6622 - val_loss: 3.1084 - val_accuracy: 0.5934
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9702 - accuracy: 0.6574 - val_loss: 3.0991 - val_accuracy: 0.5934
Epoch 69/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9682 - accuracy: 0.6598 - val_loss: 3.0907 - val_accuracy: 0.6154
Epoch 70/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9202 - accuracy: 0.6877 - val_loss: 3.0820 - val_accuracy: 0.6154
Epoch 71/100
7/7 [==============================] - 0s 11ms/step - loss: 2.9733 - accuracy: 0.6598 - val_loss: 3.0741 - val_accuracy: 0.6154
Epoch 72/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9367 - accuracy: 0.6744 - val_loss: 3.0655 - val_accuracy: 0.6374
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9268 - accuracy: 0.6768 - val_loss: 3.0562 - val_accuracy: 0.6374
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9162 - accuracy: 0.6598 - val_loss: 3.0484 - val_accuracy: 0.6374
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8927 - accuracy: 0.6841 - val_loss: 3.0400 - val_accuracy: 0.6374
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9101 - accuracy: 0.6792 - val_loss: 3.0324 - val_accuracy: 0.6484
Epoch 77/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9321 - accuracy: 0.6537 - val_loss: 3.0239 - val_accuracy: 0.6484
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9011 - accuracy: 0.6695 - val_loss: 3.0160 - val_accuracy: 0.6484
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8913 - accuracy: 0.6877 - val_loss: 3.0083 - val_accuracy: 0.6703
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9332 - accuracy: 0.6610 - val_loss: 3.0005 - val_accuracy: 0.6703
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8725 - accuracy: 0.6877 - val_loss: 2.9931 - val_accuracy: 0.6703
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8863 - accuracy: 0.6646 - val_loss: 2.9852 - val_accuracy: 0.6703
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8752 - accuracy: 0.6889 - val_loss: 2.9773 - val_accuracy: 0.6813
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8761 - accuracy: 0.6598 - val_loss: 2.9703 - val_accuracy: 0.6923
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8114 - accuracy: 0.7108 - val_loss: 2.9632 - val_accuracy: 0.6923
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8556 - accuracy: 0.6756 - val_loss: 2.9568 - val_accuracy: 0.6923
Epoch 87/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8278 - accuracy: 0.6914 - val_loss: 2.9507 - val_accuracy: 0.6923
Epoch 88/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8611 - accuracy: 0.6889 - val_loss: 2.9447 - val_accuracy: 0.6923
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8277 - accuracy: 0.6914 - val_loss: 2.9388 - val_accuracy: 0.7033
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8320 - accuracy: 0.7096 - val_loss: 2.9325 - val_accuracy: 0.7033
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7988 - accuracy: 0.7011 - val_loss: 2.9264 - val_accuracy: 0.7033
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8017 - accuracy: 0.7230 - val_loss: 2.9193 - val_accuracy: 0.7033
Epoch 93/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8338 - accuracy: 0.6999 - val_loss: 2.9134 - val_accuracy: 0.7033
Epoch 94/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8064 - accuracy: 0.7084 - val_loss: 2.9077 - val_accuracy: 0.7033
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7827 - accuracy: 0.7169 - val_loss: 2.9008 - val_accuracy: 0.7033
Epoch 96/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7381 - accuracy: 0.7169 - val_loss: 2.8953 - val_accuracy: 0.7033
Epoch 97/100
7/7 [==============================] - 0s 11ms/step - loss: 2.8051 - accuracy: 0.7108 - val_loss: 2.8896 - val_accuracy: 0.7033
Epoch 98/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7689 - accuracy: 0.7132 - val_loss: 2.8839 - val_accuracy: 0.7033
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7590 - accuracy: 0.7217 - val_loss: 2.8774 - val_accuracy: 0.7033
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7431 - accuracy: 0.7303 - val_loss: 2.8717 - val_accuracy: 0.7033
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 45ms/step - loss: 3.7160 - accuracy: 0.2989 - val_loss: 3.3087 - val_accuracy: 0.1538
Epoch 2/100
7/7 [==============================] - 0s 10ms/step - loss: 3.7105 - accuracy: 0.3123 - val_loss: 3.3055 - val_accuracy: 0.1538
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7226 - accuracy: 0.3026 - val_loss: 3.3017 - val_accuracy: 0.1538
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7008 - accuracy: 0.3183 - val_loss: 3.2970 - val_accuracy: 0.1538
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6745 - accuracy: 0.3208 - val_loss: 3.2915 - val_accuracy: 0.1538
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6898 - accuracy: 0.2928 - val_loss: 3.2854 - val_accuracy: 0.1758
Epoch 7/100
7/7 [==============================] - 0s 11ms/step - loss: 3.6619 - accuracy: 0.3074 - val_loss: 3.2788 - val_accuracy: 0.1868
Epoch 8/100
7/7 [==============================] - 0s 12ms/step - loss: 3.6437 - accuracy: 0.3050 - val_loss: 3.2714 - val_accuracy: 0.1978
Epoch 9/100
7/7 [==============================] - 0s 11ms/step - loss: 3.6127 - accuracy: 0.3402 - val_loss: 3.2636 - val_accuracy: 0.2198
Epoch 10/100
7/7 [==============================] - 0s 11ms/step - loss: 3.5954 - accuracy: 0.3366 - val_loss: 3.2549 - val_accuracy: 0.2308
Epoch 11/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5814 - accuracy: 0.3329 - val_loss: 3.2459 - val_accuracy: 0.2527
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5675 - accuracy: 0.3499 - val_loss: 3.2364 - val_accuracy: 0.2527
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5030 - accuracy: 0.3694 - val_loss: 3.2269 - val_accuracy: 0.2418
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4732 - accuracy: 0.3730 - val_loss: 3.2167 - val_accuracy: 0.2747
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4747 - accuracy: 0.4046 - val_loss: 3.2063 - val_accuracy: 0.3407
Epoch 16/100
7/7 [==============================] - 0s 7ms/step - loss: 3.4707 - accuracy: 0.3864 - val_loss: 3.1954 - val_accuracy: 0.3626
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4320 - accuracy: 0.4253 - val_loss: 3.1844 - val_accuracy: 0.4176
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4398 - accuracy: 0.4034 - val_loss: 3.1737 - val_accuracy: 0.4505
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3809 - accuracy: 0.4107 - val_loss: 3.1626 - val_accuracy: 0.4615
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3676 - accuracy: 0.4642 - val_loss: 3.1515 - val_accuracy: 0.4945
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3836 - accuracy: 0.4301 - val_loss: 3.1406 - val_accuracy: 0.5055
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3598 - accuracy: 0.4411 - val_loss: 3.1297 - val_accuracy: 0.5275
Epoch 23/100
7/7 [==============================] - 0s 7ms/step - loss: 3.3239 - accuracy: 0.4690 - val_loss: 3.1188 - val_accuracy: 0.5495
Epoch 24/100
7/7 [==============================] - 0s 7ms/step - loss: 3.2914 - accuracy: 0.4787 - val_loss: 3.1078 - val_accuracy: 0.5495
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3197 - accuracy: 0.4897 - val_loss: 3.0975 - val_accuracy: 0.5934
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2969 - accuracy: 0.5067 - val_loss: 3.0871 - val_accuracy: 0.6154
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2666 - accuracy: 0.5200 - val_loss: 3.0767 - val_accuracy: 0.6264
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2767 - accuracy: 0.5213 - val_loss: 3.0667 - val_accuracy: 0.6264
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2470 - accuracy: 0.5200 - val_loss: 3.0568 - val_accuracy: 0.6374
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2218 - accuracy: 0.5456 - val_loss: 3.0471 - val_accuracy: 0.6484
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2702 - accuracy: 0.5176 - val_loss: 3.0376 - val_accuracy: 0.6593
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2574 - accuracy: 0.5322 - val_loss: 3.0281 - val_accuracy: 0.6703
Epoch 33/100
7/7 [==============================] - 0s 10ms/step - loss: 3.2147 - accuracy: 0.5273 - val_loss: 3.0189 - val_accuracy: 0.6813
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2298 - accuracy: 0.5419 - val_loss: 3.0096 - val_accuracy: 0.6813
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2383 - accuracy: 0.5662 - val_loss: 3.0007 - val_accuracy: 0.7033
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2124 - accuracy: 0.5529 - val_loss: 2.9918 - val_accuracy: 0.7143
Epoch 37/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1585 - accuracy: 0.5674 - val_loss: 2.9826 - val_accuracy: 0.7143
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1777 - accuracy: 0.5844 - val_loss: 2.9736 - val_accuracy: 0.7253
Epoch 39/100
7/7 [==============================] - 0s 7ms/step - loss: 3.1748 - accuracy: 0.5784 - val_loss: 2.9655 - val_accuracy: 0.7253
Epoch 40/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1423 - accuracy: 0.5747 - val_loss: 2.9571 - val_accuracy: 0.7253
Epoch 41/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1572 - accuracy: 0.5917 - val_loss: 2.9489 - val_accuracy: 0.7253
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1288 - accuracy: 0.5857 - val_loss: 2.9413 - val_accuracy: 0.7363
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1294 - accuracy: 0.5820 - val_loss: 2.9337 - val_accuracy: 0.7363
Epoch 44/100
7/7 [==============================] - 0s 7ms/step - loss: 3.1193 - accuracy: 0.6063 - val_loss: 2.9260 - val_accuracy: 0.7363
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1366 - accuracy: 0.5942 - val_loss: 2.9186 - val_accuracy: 0.7363
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0695 - accuracy: 0.6039 - val_loss: 2.9114 - val_accuracy: 0.7363
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0910 - accuracy: 0.6051 - val_loss: 2.9041 - val_accuracy: 0.7363
Epoch 48/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0974 - accuracy: 0.5978 - val_loss: 2.8969 - val_accuracy: 0.7363
Epoch 49/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0940 - accuracy: 0.6160 - val_loss: 2.8895 - val_accuracy: 0.7363
Epoch 50/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0106 - accuracy: 0.6306 - val_loss: 2.8825 - val_accuracy: 0.7363
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0673 - accuracy: 0.6136 - val_loss: 2.8755 - val_accuracy: 0.7582
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0081 - accuracy: 0.6270 - val_loss: 2.8682 - val_accuracy: 0.7582
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0515 - accuracy: 0.6233 - val_loss: 2.8612 - val_accuracy: 0.7692
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0181 - accuracy: 0.6391 - val_loss: 2.8546 - val_accuracy: 0.7692
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0452 - accuracy: 0.6245 - val_loss: 2.8477 - val_accuracy: 0.7692
Epoch 56/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9865 - accuracy: 0.6416 - val_loss: 2.8410 - val_accuracy: 0.7692
Epoch 57/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0096 - accuracy: 0.6197 - val_loss: 2.8345 - val_accuracy: 0.7692
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0003 - accuracy: 0.6233 - val_loss: 2.8279 - val_accuracy: 0.7692
Epoch 59/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9416 - accuracy: 0.6646 - val_loss: 2.8214 - val_accuracy: 0.7692
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9567 - accuracy: 0.6525 - val_loss: 2.8142 - val_accuracy: 0.7692
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9372 - accuracy: 0.6403 - val_loss: 2.8076 - val_accuracy: 0.7912
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9560 - accuracy: 0.6452 - val_loss: 2.8016 - val_accuracy: 0.8022
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9278 - accuracy: 0.6476 - val_loss: 2.7952 - val_accuracy: 0.8022
Epoch 64/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9559 - accuracy: 0.6452 - val_loss: 2.7887 - val_accuracy: 0.8022
Epoch 65/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9323 - accuracy: 0.6719 - val_loss: 2.7828 - val_accuracy: 0.8022
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9443 - accuracy: 0.6464 - val_loss: 2.7773 - val_accuracy: 0.8022
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9337 - accuracy: 0.6355 - val_loss: 2.7705 - val_accuracy: 0.8132
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9317 - accuracy: 0.6586 - val_loss: 2.7649 - val_accuracy: 0.8132
Epoch 69/100
7/7 [==============================] - 0s 11ms/step - loss: 2.9445 - accuracy: 0.6488 - val_loss: 2.7590 - val_accuracy: 0.8242
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9566 - accuracy: 0.6525 - val_loss: 2.7531 - val_accuracy: 0.8242
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8810 - accuracy: 0.6719 - val_loss: 2.7470 - val_accuracy: 0.8352
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8462 - accuracy: 0.6889 - val_loss: 2.7409 - val_accuracy: 0.8352
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8775 - accuracy: 0.6659 - val_loss: 2.7347 - val_accuracy: 0.8352
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8695 - accuracy: 0.6610 - val_loss: 2.7287 - val_accuracy: 0.8352
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8513 - accuracy: 0.6659 - val_loss: 2.7227 - val_accuracy: 0.8352
Epoch 76/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8503 - accuracy: 0.6695 - val_loss: 2.7171 - val_accuracy: 0.8352
Epoch 77/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8548 - accuracy: 0.6792 - val_loss: 2.7110 - val_accuracy: 0.8352
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8479 - accuracy: 0.6792 - val_loss: 2.7051 - val_accuracy: 0.8352
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8515 - accuracy: 0.6659 - val_loss: 2.6993 - val_accuracy: 0.8352
Epoch 80/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8259 - accuracy: 0.6731 - val_loss: 2.6938 - val_accuracy: 0.8352
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8156 - accuracy: 0.6914 - val_loss: 2.6878 - val_accuracy: 0.8352
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8289 - accuracy: 0.6865 - val_loss: 2.6816 - val_accuracy: 0.8352
Epoch 83/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7923 - accuracy: 0.6877 - val_loss: 2.6760 - val_accuracy: 0.8352
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8123 - accuracy: 0.6792 - val_loss: 2.6702 - val_accuracy: 0.8352
Epoch 85/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7982 - accuracy: 0.6962 - val_loss: 2.6637 - val_accuracy: 0.8352
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7812 - accuracy: 0.6950 - val_loss: 2.6583 - val_accuracy: 0.8352
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8132 - accuracy: 0.6914 - val_loss: 2.6530 - val_accuracy: 0.8352
Epoch 88/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7589 - accuracy: 0.6987 - val_loss: 2.6476 - val_accuracy: 0.8352
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8086 - accuracy: 0.6926 - val_loss: 2.6421 - val_accuracy: 0.8352
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7847 - accuracy: 0.6962 - val_loss: 2.6367 - val_accuracy: 0.8352
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7621 - accuracy: 0.7278 - val_loss: 2.6310 - val_accuracy: 0.8352
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7447 - accuracy: 0.7108 - val_loss: 2.6251 - val_accuracy: 0.8352
Epoch 93/100
7/7 [==============================] - 0s 11ms/step - loss: 2.7298 - accuracy: 0.7193 - val_loss: 2.6196 - val_accuracy: 0.8352
Epoch 94/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7286 - accuracy: 0.7072 - val_loss: 2.6141 - val_accuracy: 0.8352
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7161 - accuracy: 0.7120 - val_loss: 2.6088 - val_accuracy: 0.8352
Epoch 96/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7164 - accuracy: 0.7108 - val_loss: 2.6030 - val_accuracy: 0.8352
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7566 - accuracy: 0.7096 - val_loss: 2.5972 - val_accuracy: 0.8352
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7446 - accuracy: 0.7266 - val_loss: 2.5916 - val_accuracy: 0.8462
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7424 - accuracy: 0.7132 - val_loss: 2.5860 - val_accuracy: 0.8462
Epoch 100/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7104 - accuracy: 0.7108 - val_loss: 2.5804 - val_accuracy: 0.8462
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 3.7303 - accuracy: 0.3852 - val_loss: 3.2614 - val_accuracy: 0.1868
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7692 - accuracy: 0.3657 - val_loss: 3.2584 - val_accuracy: 0.2198
Epoch 3/100
7/7 [==============================] - 0s 11ms/step - loss: 3.8016 - accuracy: 0.3657 - val_loss: 3.2547 - val_accuracy: 0.2198
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7085 - accuracy: 0.3706 - val_loss: 3.2499 - val_accuracy: 0.2198
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7404 - accuracy: 0.3426 - val_loss: 3.2445 - val_accuracy: 0.2308
Epoch 6/100
7/7 [==============================] - 0s 10ms/step - loss: 3.6970 - accuracy: 0.3803 - val_loss: 3.2381 - val_accuracy: 0.2418
Epoch 7/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7014 - accuracy: 0.3767 - val_loss: 3.2311 - val_accuracy: 0.3077
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6683 - accuracy: 0.3755 - val_loss: 3.2235 - val_accuracy: 0.3297
Epoch 9/100
7/7 [==============================] - 0s 12ms/step - loss: 3.5734 - accuracy: 0.4168 - val_loss: 3.2154 - val_accuracy: 0.3516
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 3.6059 - accuracy: 0.3961 - val_loss: 3.2066 - val_accuracy: 0.3736
Epoch 11/100
7/7 [==============================] - 0s 11ms/step - loss: 3.5697 - accuracy: 0.4083 - val_loss: 3.1972 - val_accuracy: 0.4066
Epoch 12/100
7/7 [==============================] - 0s 7ms/step - loss: 3.5363 - accuracy: 0.4156 - val_loss: 3.1876 - val_accuracy: 0.4396
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5304 - accuracy: 0.4216 - val_loss: 3.1775 - val_accuracy: 0.4615
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5260 - accuracy: 0.4313 - val_loss: 3.1671 - val_accuracy: 0.4725
Epoch 15/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4401 - accuracy: 0.4362 - val_loss: 3.1566 - val_accuracy: 0.4725
Epoch 16/100
7/7 [==============================] - 0s 10ms/step - loss: 3.4404 - accuracy: 0.4532 - val_loss: 3.1456 - val_accuracy: 0.5055
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4091 - accuracy: 0.4532 - val_loss: 3.1345 - val_accuracy: 0.5165
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3948 - accuracy: 0.4629 - val_loss: 3.1239 - val_accuracy: 0.5385
Epoch 19/100
7/7 [==============================] - 0s 10ms/step - loss: 3.4148 - accuracy: 0.4860 - val_loss: 3.1130 - val_accuracy: 0.5385
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3973 - accuracy: 0.4812 - val_loss: 3.1020 - val_accuracy: 0.5495
Epoch 21/100
7/7 [==============================] - 0s 7ms/step - loss: 3.3600 - accuracy: 0.4921 - val_loss: 3.0913 - val_accuracy: 0.5714
Epoch 22/100
7/7 [==============================] - 0s 11ms/step - loss: 3.3089 - accuracy: 0.5115 - val_loss: 3.0811 - val_accuracy: 0.5934
Epoch 23/100
7/7 [==============================] - 0s 10ms/step - loss: 3.3429 - accuracy: 0.5140 - val_loss: 3.0709 - val_accuracy: 0.6044
Epoch 24/100
7/7 [==============================] - 0s 10ms/step - loss: 3.2525 - accuracy: 0.5115 - val_loss: 3.0610 - val_accuracy: 0.6264
Epoch 25/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2757 - accuracy: 0.5371 - val_loss: 3.0513 - val_accuracy: 0.6374
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2246 - accuracy: 0.5358 - val_loss: 3.0411 - val_accuracy: 0.6374
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2744 - accuracy: 0.5553 - val_loss: 3.0316 - val_accuracy: 0.6484
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2725 - accuracy: 0.5443 - val_loss: 3.0221 - val_accuracy: 0.6374
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1970 - accuracy: 0.5699 - val_loss: 3.0135 - val_accuracy: 0.6264
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2047 - accuracy: 0.5553 - val_loss: 3.0052 - val_accuracy: 0.6374
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1738 - accuracy: 0.5674 - val_loss: 2.9971 - val_accuracy: 0.6374
Epoch 32/100
7/7 [==============================] - 0s 7ms/step - loss: 3.1981 - accuracy: 0.5553 - val_loss: 2.9894 - val_accuracy: 0.6374
Epoch 33/100
7/7 [==============================] - 0s 10ms/step - loss: 3.1846 - accuracy: 0.5747 - val_loss: 2.9815 - val_accuracy: 0.6374
Epoch 34/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1826 - accuracy: 0.5966 - val_loss: 2.9744 - val_accuracy: 0.6484
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1505 - accuracy: 0.5857 - val_loss: 2.9673 - val_accuracy: 0.6593
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1389 - accuracy: 0.5954 - val_loss: 2.9608 - val_accuracy: 0.6593
Epoch 37/100
7/7 [==============================] - 0s 7ms/step - loss: 3.1758 - accuracy: 0.5893 - val_loss: 2.9543 - val_accuracy: 0.6593
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1590 - accuracy: 0.6027 - val_loss: 2.9480 - val_accuracy: 0.6813
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1183 - accuracy: 0.5930 - val_loss: 2.9423 - val_accuracy: 0.6813
Epoch 40/100
7/7 [==============================] - 0s 10ms/step - loss: 3.1217 - accuracy: 0.5881 - val_loss: 2.9365 - val_accuracy: 0.6813
Epoch 41/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0988 - accuracy: 0.6027 - val_loss: 2.9312 - val_accuracy: 0.6813
Epoch 42/100
7/7 [==============================] - 0s 11ms/step - loss: 3.1013 - accuracy: 0.5954 - val_loss: 2.9258 - val_accuracy: 0.6813
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0793 - accuracy: 0.6112 - val_loss: 2.9209 - val_accuracy: 0.6813
Epoch 44/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0738 - accuracy: 0.6112 - val_loss: 2.9157 - val_accuracy: 0.6923
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0472 - accuracy: 0.6245 - val_loss: 2.9106 - val_accuracy: 0.6923
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0294 - accuracy: 0.6270 - val_loss: 2.9050 - val_accuracy: 0.7033
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0194 - accuracy: 0.6294 - val_loss: 2.8999 - val_accuracy: 0.7033
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0188 - accuracy: 0.6282 - val_loss: 2.8945 - val_accuracy: 0.7033
Epoch 49/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0198 - accuracy: 0.6209 - val_loss: 2.8891 - val_accuracy: 0.7033
Epoch 50/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9988 - accuracy: 0.6087 - val_loss: 2.8840 - val_accuracy: 0.7033
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0181 - accuracy: 0.6136 - val_loss: 2.8789 - val_accuracy: 0.7033
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9637 - accuracy: 0.6294 - val_loss: 2.8733 - val_accuracy: 0.7033
Epoch 53/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9630 - accuracy: 0.6233 - val_loss: 2.8677 - val_accuracy: 0.7143
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9879 - accuracy: 0.6221 - val_loss: 2.8628 - val_accuracy: 0.7143
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9376 - accuracy: 0.6598 - val_loss: 2.8578 - val_accuracy: 0.7143
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9295 - accuracy: 0.6428 - val_loss: 2.8521 - val_accuracy: 0.7143
Epoch 57/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9522 - accuracy: 0.6379 - val_loss: 2.8469 - val_accuracy: 0.7143
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9381 - accuracy: 0.6525 - val_loss: 2.8412 - val_accuracy: 0.7143
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9083 - accuracy: 0.6659 - val_loss: 2.8360 - val_accuracy: 0.7143
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9133 - accuracy: 0.6537 - val_loss: 2.8301 - val_accuracy: 0.7253
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9029 - accuracy: 0.6379 - val_loss: 2.8248 - val_accuracy: 0.7253
Epoch 62/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9107 - accuracy: 0.6513 - val_loss: 2.8192 - val_accuracy: 0.7253
Epoch 63/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9285 - accuracy: 0.6330 - val_loss: 2.8137 - val_accuracy: 0.7363
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8949 - accuracy: 0.6501 - val_loss: 2.8080 - val_accuracy: 0.7473
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 2.8985 - accuracy: 0.6646 - val_loss: 2.8021 - val_accuracy: 0.7473
Epoch 66/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9019 - accuracy: 0.6622 - val_loss: 2.7966 - val_accuracy: 0.7363
Epoch 67/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8265 - accuracy: 0.6804 - val_loss: 2.7906 - val_accuracy: 0.7363
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8363 - accuracy: 0.6671 - val_loss: 2.7843 - val_accuracy: 0.7363
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8090 - accuracy: 0.6768 - val_loss: 2.7785 - val_accuracy: 0.7473
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8582 - accuracy: 0.6501 - val_loss: 2.7727 - val_accuracy: 0.7473
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8494 - accuracy: 0.6622 - val_loss: 2.7667 - val_accuracy: 0.7473
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8233 - accuracy: 0.6671 - val_loss: 2.7613 - val_accuracy: 0.7473
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8106 - accuracy: 0.6695 - val_loss: 2.7554 - val_accuracy: 0.7473
Epoch 74/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7781 - accuracy: 0.6780 - val_loss: 2.7498 - val_accuracy: 0.7473
Epoch 75/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7783 - accuracy: 0.6889 - val_loss: 2.7447 - val_accuracy: 0.7473
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8232 - accuracy: 0.6586 - val_loss: 2.7391 - val_accuracy: 0.7473
Epoch 77/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7626 - accuracy: 0.6938 - val_loss: 2.7336 - val_accuracy: 0.7473
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7454 - accuracy: 0.7132 - val_loss: 2.7280 - val_accuracy: 0.7582
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7734 - accuracy: 0.7047 - val_loss: 2.7224 - val_accuracy: 0.7582
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7395 - accuracy: 0.7072 - val_loss: 2.7170 - val_accuracy: 0.7582
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7494 - accuracy: 0.7108 - val_loss: 2.7123 - val_accuracy: 0.7582
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7530 - accuracy: 0.6938 - val_loss: 2.7072 - val_accuracy: 0.7582
Epoch 83/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7565 - accuracy: 0.6999 - val_loss: 2.7016 - val_accuracy: 0.7582
Epoch 84/100
7/7 [==============================] - 0s 12ms/step - loss: 2.7524 - accuracy: 0.6926 - val_loss: 2.6963 - val_accuracy: 0.7582
Epoch 85/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7017 - accuracy: 0.7242 - val_loss: 2.6915 - val_accuracy: 0.7582
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7335 - accuracy: 0.7108 - val_loss: 2.6868 - val_accuracy: 0.7692
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7074 - accuracy: 0.7096 - val_loss: 2.6820 - val_accuracy: 0.7692
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7118 - accuracy: 0.7072 - val_loss: 2.6763 - val_accuracy: 0.7692
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6874 - accuracy: 0.7193 - val_loss: 2.6712 - val_accuracy: 0.7692
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7131 - accuracy: 0.7157 - val_loss: 2.6661 - val_accuracy: 0.7692
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6682 - accuracy: 0.7363 - val_loss: 2.6611 - val_accuracy: 0.7802
Epoch 92/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7006 - accuracy: 0.7157 - val_loss: 2.6562 - val_accuracy: 0.7802
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6861 - accuracy: 0.7193 - val_loss: 2.6508 - val_accuracy: 0.7802
Epoch 94/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6650 - accuracy: 0.7363 - val_loss: 2.6457 - val_accuracy: 0.7802
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6385 - accuracy: 0.7363 - val_loss: 2.6405 - val_accuracy: 0.7692
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6566 - accuracy: 0.7254 - val_loss: 2.6359 - val_accuracy: 0.7692
Epoch 97/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6457 - accuracy: 0.7388 - val_loss: 2.6311 - val_accuracy: 0.7692
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6624 - accuracy: 0.7303 - val_loss: 2.6261 - val_accuracy: 0.7692
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6363 - accuracy: 0.7412 - val_loss: 2.6216 - val_accuracy: 0.7692
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6305 - accuracy: 0.7400 - val_loss: 2.6164 - val_accuracy: 0.7692
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Experiment number: 8
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 247ms/step - loss: 1.8888 - accuracy: 0.3686 - val_loss: 1.2368 - val_accuracy: 0.5978
Epoch 2/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8944 - accuracy: 0.3735 - val_loss: 1.2396 - val_accuracy: 0.5978
Epoch 3/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8994 - accuracy: 0.3747 - val_loss: 1.2418 - val_accuracy: 0.5978
Epoch 4/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8497 - accuracy: 0.3929 - val_loss: 1.2437 - val_accuracy: 0.5978
Epoch 5/100
2/2 [==============================] - 0s 49ms/step - loss: 1.8820 - accuracy: 0.3589 - val_loss: 1.2451 - val_accuracy: 0.5978
Epoch 6/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8705 - accuracy: 0.3881 - val_loss: 1.2459 - val_accuracy: 0.5978
Epoch 7/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8050 - accuracy: 0.3978 - val_loss: 1.2463 - val_accuracy: 0.5978
Epoch 8/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8582 - accuracy: 0.3905 - val_loss: 1.2462 - val_accuracy: 0.5978
Epoch 9/100
2/2 [==============================] - 0s 37ms/step - loss: 1.8192 - accuracy: 0.3954 - val_loss: 1.2457 - val_accuracy: 0.5978
Epoch 10/100
2/2 [==============================] - 0s 47ms/step - loss: 1.8561 - accuracy: 0.4015 - val_loss: 1.2447 - val_accuracy: 0.5978
Epoch 11/100
2/2 [==============================] - 0s 45ms/step - loss: 1.7805 - accuracy: 0.4015 - val_loss: 1.2431 - val_accuracy: 0.5978
Epoch 12/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8262 - accuracy: 0.4039 - val_loss: 1.2411 - val_accuracy: 0.5978
Epoch 13/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7923 - accuracy: 0.3954 - val_loss: 1.2390 - val_accuracy: 0.5978
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7917 - accuracy: 0.4282 - val_loss: 1.2364 - val_accuracy: 0.5978
Epoch 15/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7552 - accuracy: 0.4185 - val_loss: 1.2332 - val_accuracy: 0.5978
Epoch 16/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7403 - accuracy: 0.3905 - val_loss: 1.2296 - val_accuracy: 0.5978
Epoch 17/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7901 - accuracy: 0.4039 - val_loss: 1.2257 - val_accuracy: 0.5978
Epoch 18/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7462 - accuracy: 0.4002 - val_loss: 1.2212 - val_accuracy: 0.5978
Epoch 19/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7166 - accuracy: 0.4100 - val_loss: 1.2167 - val_accuracy: 0.5978
Epoch 20/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7702 - accuracy: 0.4148 - val_loss: 1.2117 - val_accuracy: 0.5978
Epoch 21/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7020 - accuracy: 0.4161 - val_loss: 1.2065 - val_accuracy: 0.5978
Epoch 22/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6997 - accuracy: 0.4124 - val_loss: 1.2009 - val_accuracy: 0.5978
Epoch 23/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7024 - accuracy: 0.4039 - val_loss: 1.1949 - val_accuracy: 0.5978
Epoch 24/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6710 - accuracy: 0.4161 - val_loss: 1.1887 - val_accuracy: 0.5978
Epoch 25/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6574 - accuracy: 0.4367 - val_loss: 1.1823 - val_accuracy: 0.5978
Epoch 26/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6414 - accuracy: 0.4221 - val_loss: 1.1755 - val_accuracy: 0.5978
Epoch 27/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5752 - accuracy: 0.4538 - val_loss: 1.1685 - val_accuracy: 0.6196
Epoch 28/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5799 - accuracy: 0.4489 - val_loss: 1.1613 - val_accuracy: 0.6304
Epoch 29/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5977 - accuracy: 0.4319 - val_loss: 1.1539 - val_accuracy: 0.6196
Epoch 30/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5811 - accuracy: 0.4550 - val_loss: 1.1462 - val_accuracy: 0.6304
Epoch 31/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5487 - accuracy: 0.4611 - val_loss: 1.1383 - val_accuracy: 0.6304
Epoch 32/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5901 - accuracy: 0.4513 - val_loss: 1.1303 - val_accuracy: 0.6304
Epoch 33/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5345 - accuracy: 0.4294 - val_loss: 1.1220 - val_accuracy: 0.6304
Epoch 34/100
2/2 [==============================] - 0s 52ms/step - loss: 1.5464 - accuracy: 0.4477 - val_loss: 1.1136 - val_accuracy: 0.6304
Epoch 35/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5232 - accuracy: 0.4769 - val_loss: 1.1051 - val_accuracy: 0.6304
Epoch 36/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4977 - accuracy: 0.4611 - val_loss: 1.0965 - val_accuracy: 0.6413
Epoch 37/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4326 - accuracy: 0.4830 - val_loss: 1.0879 - val_accuracy: 0.6413
Epoch 38/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4656 - accuracy: 0.4805 - val_loss: 1.0790 - val_accuracy: 0.6413
Epoch 39/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4230 - accuracy: 0.4672 - val_loss: 1.0700 - val_accuracy: 0.6413
Epoch 40/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4123 - accuracy: 0.4915 - val_loss: 1.0609 - val_accuracy: 0.6413
Epoch 41/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4145 - accuracy: 0.4951 - val_loss: 1.0518 - val_accuracy: 0.6522
Epoch 42/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3914 - accuracy: 0.5085 - val_loss: 1.0427 - val_accuracy: 0.6522
Epoch 43/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3472 - accuracy: 0.5170 - val_loss: 1.0335 - val_accuracy: 0.6522
Epoch 44/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3192 - accuracy: 0.5097 - val_loss: 1.0243 - val_accuracy: 0.6522
Epoch 45/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3613 - accuracy: 0.4793 - val_loss: 1.0151 - val_accuracy: 0.6630
Epoch 46/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2829 - accuracy: 0.5341 - val_loss: 1.0058 - val_accuracy: 0.6630
Epoch 47/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3340 - accuracy: 0.5109 - val_loss: 0.9966 - val_accuracy: 0.6739
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2755 - accuracy: 0.5487 - val_loss: 0.9874 - val_accuracy: 0.6739
Epoch 49/100
2/2 [==============================] - 0s 28ms/step - loss: 1.2587 - accuracy: 0.5426 - val_loss: 0.9784 - val_accuracy: 0.6848
Epoch 50/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2773 - accuracy: 0.5328 - val_loss: 0.9693 - val_accuracy: 0.6957
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2629 - accuracy: 0.5620 - val_loss: 0.9604 - val_accuracy: 0.6957
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2082 - accuracy: 0.5754 - val_loss: 0.9514 - val_accuracy: 0.7065
Epoch 53/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1760 - accuracy: 0.5900 - val_loss: 0.9426 - val_accuracy: 0.7065
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1544 - accuracy: 0.5791 - val_loss: 0.9339 - val_accuracy: 0.7174
Epoch 55/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1583 - accuracy: 0.5839 - val_loss: 0.9253 - val_accuracy: 0.7174
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1962 - accuracy: 0.5779 - val_loss: 0.9168 - val_accuracy: 0.7174
Epoch 57/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1169 - accuracy: 0.6131 - val_loss: 0.9084 - val_accuracy: 0.7174
Epoch 58/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1691 - accuracy: 0.5839 - val_loss: 0.9001 - val_accuracy: 0.7174
Epoch 59/100
2/2 [==============================] - 0s 34ms/step - loss: 1.0645 - accuracy: 0.6326 - val_loss: 0.8920 - val_accuracy: 0.7174
Epoch 60/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0875 - accuracy: 0.6302 - val_loss: 0.8840 - val_accuracy: 0.7174
Epoch 61/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0846 - accuracy: 0.6338 - val_loss: 0.8762 - val_accuracy: 0.7174
Epoch 62/100
2/2 [==============================] - 0s 33ms/step - loss: 1.0928 - accuracy: 0.6156 - val_loss: 0.8686 - val_accuracy: 0.7500
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0559 - accuracy: 0.6363 - val_loss: 0.8611 - val_accuracy: 0.7609
Epoch 64/100
2/2 [==============================] - 0s 45ms/step - loss: 1.0582 - accuracy: 0.6606 - val_loss: 0.8537 - val_accuracy: 0.7935
Epoch 65/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0649 - accuracy: 0.6363 - val_loss: 0.8466 - val_accuracy: 0.8043
Epoch 66/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0527 - accuracy: 0.6533 - val_loss: 0.8396 - val_accuracy: 0.8043
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0175 - accuracy: 0.6679 - val_loss: 0.8328 - val_accuracy: 0.8152
Epoch 68/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0149 - accuracy: 0.6752 - val_loss: 0.8262 - val_accuracy: 0.8152
Epoch 69/100
2/2 [==============================] - 0s 35ms/step - loss: 1.0234 - accuracy: 0.6582 - val_loss: 0.8198 - val_accuracy: 0.8261
Epoch 70/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9781 - accuracy: 0.6886 - val_loss: 0.8136 - val_accuracy: 0.8370
Epoch 71/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9764 - accuracy: 0.6849 - val_loss: 0.8076 - val_accuracy: 0.8370
Epoch 72/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9547 - accuracy: 0.6959 - val_loss: 0.8017 - val_accuracy: 0.8370
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9455 - accuracy: 0.7044 - val_loss: 0.7960 - val_accuracy: 0.8478
Epoch 74/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9268 - accuracy: 0.7068 - val_loss: 0.7904 - val_accuracy: 0.8478
Epoch 75/100
2/2 [==============================] - 0s 48ms/step - loss: 0.9256 - accuracy: 0.7044 - val_loss: 0.7851 - val_accuracy: 0.8587
Epoch 76/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9473 - accuracy: 0.7190 - val_loss: 0.7799 - val_accuracy: 0.8587
Epoch 77/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9234 - accuracy: 0.7165 - val_loss: 0.7748 - val_accuracy: 0.8587
Epoch 78/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9254 - accuracy: 0.7214 - val_loss: 0.7699 - val_accuracy: 0.8587
Epoch 79/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8874 - accuracy: 0.7372 - val_loss: 0.7651 - val_accuracy: 0.8478
Epoch 80/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9020 - accuracy: 0.7214 - val_loss: 0.7606 - val_accuracy: 0.8478
Epoch 81/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9047 - accuracy: 0.7397 - val_loss: 0.7561 - val_accuracy: 0.8478
Epoch 82/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8741 - accuracy: 0.7494 - val_loss: 0.7518 - val_accuracy: 0.8478
Epoch 83/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8784 - accuracy: 0.7311 - val_loss: 0.7476 - val_accuracy: 0.8478
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8590 - accuracy: 0.7591 - val_loss: 0.7436 - val_accuracy: 0.8587
Epoch 85/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8538 - accuracy: 0.7591 - val_loss: 0.7397 - val_accuracy: 0.8587
Epoch 86/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8528 - accuracy: 0.7689 - val_loss: 0.7359 - val_accuracy: 0.8587
Epoch 87/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8188 - accuracy: 0.7737 - val_loss: 0.7322 - val_accuracy: 0.8587
Epoch 88/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8354 - accuracy: 0.7689 - val_loss: 0.7287 - val_accuracy: 0.8587
Epoch 89/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8467 - accuracy: 0.7518 - val_loss: 0.7253 - val_accuracy: 0.8478
Epoch 90/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7992 - accuracy: 0.7762 - val_loss: 0.7220 - val_accuracy: 0.8478
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8226 - accuracy: 0.7725 - val_loss: 0.7188 - val_accuracy: 0.8478
Epoch 92/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7904 - accuracy: 0.7956 - val_loss: 0.7157 - val_accuracy: 0.8478
Epoch 93/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8042 - accuracy: 0.7762 - val_loss: 0.7128 - val_accuracy: 0.8478
Epoch 94/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8065 - accuracy: 0.7810 - val_loss: 0.7099 - val_accuracy: 0.8478
Epoch 95/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7821 - accuracy: 0.7932 - val_loss: 0.7072 - val_accuracy: 0.8478
Epoch 96/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7983 - accuracy: 0.7932 - val_loss: 0.7045 - val_accuracy: 0.8478
Epoch 97/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7633 - accuracy: 0.8017 - val_loss: 0.7019 - val_accuracy: 0.8478
Epoch 98/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7473 - accuracy: 0.8017 - val_loss: 0.6994 - val_accuracy: 0.8478
Epoch 99/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7703 - accuracy: 0.8054 - val_loss: 0.6970 - val_accuracy: 0.8478
Epoch 100/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7706 - accuracy: 0.7956 - val_loss: 0.6946 - val_accuracy: 0.8478
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 238ms/step - loss: 1.5155 - accuracy: 0.3321 - val_loss: 1.1930 - val_accuracy: 0.4783
Epoch 2/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5346 - accuracy: 0.3309 - val_loss: 1.1939 - val_accuracy: 0.4783
Epoch 3/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5565 - accuracy: 0.3309 - val_loss: 1.1944 - val_accuracy: 0.4674
Epoch 4/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5095 - accuracy: 0.3309 - val_loss: 1.1946 - val_accuracy: 0.4674
Epoch 5/100
2/2 [==============================] - 0s 51ms/step - loss: 1.5630 - accuracy: 0.3370 - val_loss: 1.1946 - val_accuracy: 0.4674
Epoch 6/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5507 - accuracy: 0.3248 - val_loss: 1.1943 - val_accuracy: 0.4674
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5494 - accuracy: 0.3236 - val_loss: 1.1937 - val_accuracy: 0.4674
Epoch 8/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5479 - accuracy: 0.3127 - val_loss: 1.1928 - val_accuracy: 0.4674
Epoch 9/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4962 - accuracy: 0.3187 - val_loss: 1.1916 - val_accuracy: 0.4674
Epoch 10/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5197 - accuracy: 0.3187 - val_loss: 1.1902 - val_accuracy: 0.4674
Epoch 11/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4939 - accuracy: 0.3333 - val_loss: 1.1884 - val_accuracy: 0.4783
Epoch 12/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5071 - accuracy: 0.3370 - val_loss: 1.1865 - val_accuracy: 0.4783
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5465 - accuracy: 0.3345 - val_loss: 1.1843 - val_accuracy: 0.4783
Epoch 14/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4878 - accuracy: 0.3443 - val_loss: 1.1818 - val_accuracy: 0.5000
Epoch 15/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5202 - accuracy: 0.3345 - val_loss: 1.1791 - val_accuracy: 0.5109
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4832 - accuracy: 0.3516 - val_loss: 1.1762 - val_accuracy: 0.5217
Epoch 17/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4618 - accuracy: 0.3345 - val_loss: 1.1731 - val_accuracy: 0.5326
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4766 - accuracy: 0.3577 - val_loss: 1.1698 - val_accuracy: 0.5326
Epoch 19/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4197 - accuracy: 0.3723 - val_loss: 1.1662 - val_accuracy: 0.5326
Epoch 20/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4569 - accuracy: 0.3479 - val_loss: 1.1625 - val_accuracy: 0.5543
Epoch 21/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4583 - accuracy: 0.3564 - val_loss: 1.1585 - val_accuracy: 0.5543
Epoch 22/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4451 - accuracy: 0.3467 - val_loss: 1.1543 - val_accuracy: 0.5543
Epoch 23/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4124 - accuracy: 0.3832 - val_loss: 1.1500 - val_accuracy: 0.5543
Epoch 24/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4454 - accuracy: 0.3771 - val_loss: 1.1456 - val_accuracy: 0.5543
Epoch 25/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4226 - accuracy: 0.3686 - val_loss: 1.1409 - val_accuracy: 0.5543
Epoch 26/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4403 - accuracy: 0.3516 - val_loss: 1.1360 - val_accuracy: 0.5652
Epoch 27/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3896 - accuracy: 0.3869 - val_loss: 1.1310 - val_accuracy: 0.5652
Epoch 28/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4045 - accuracy: 0.3856 - val_loss: 1.1258 - val_accuracy: 0.5652
Epoch 29/100
2/2 [==============================] - 0s 27ms/step - loss: 1.3727 - accuracy: 0.4002 - val_loss: 1.1204 - val_accuracy: 0.5652
Epoch 30/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3690 - accuracy: 0.4148 - val_loss: 1.1149 - val_accuracy: 0.5761
Epoch 31/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3586 - accuracy: 0.4063 - val_loss: 1.1094 - val_accuracy: 0.5870
Epoch 32/100
2/2 [==============================] - 0s 27ms/step - loss: 1.3438 - accuracy: 0.4185 - val_loss: 1.1036 - val_accuracy: 0.5978
Epoch 33/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3576 - accuracy: 0.4063 - val_loss: 1.0978 - val_accuracy: 0.5978
Epoch 34/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3462 - accuracy: 0.4112 - val_loss: 1.0918 - val_accuracy: 0.6196
Epoch 35/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3129 - accuracy: 0.4416 - val_loss: 1.0858 - val_accuracy: 0.6304
Epoch 36/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2920 - accuracy: 0.4440 - val_loss: 1.0797 - val_accuracy: 0.6304
Epoch 37/100
2/2 [==============================] - 0s 53ms/step - loss: 1.2744 - accuracy: 0.4453 - val_loss: 1.0734 - val_accuracy: 0.6413
Epoch 38/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2798 - accuracy: 0.4623 - val_loss: 1.0671 - val_accuracy: 0.6413
Epoch 39/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2663 - accuracy: 0.4745 - val_loss: 1.0608 - val_accuracy: 0.6522
Epoch 40/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2534 - accuracy: 0.4793 - val_loss: 1.0543 - val_accuracy: 0.6630
Epoch 41/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2419 - accuracy: 0.4647 - val_loss: 1.0478 - val_accuracy: 0.6630
Epoch 42/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2504 - accuracy: 0.4672 - val_loss: 1.0411 - val_accuracy: 0.6630
Epoch 43/100
2/2 [==============================] - 0s 28ms/step - loss: 1.2249 - accuracy: 0.4793 - val_loss: 1.0344 - val_accuracy: 0.6630
Epoch 44/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1976 - accuracy: 0.5122 - val_loss: 1.0277 - val_accuracy: 0.6630
Epoch 45/100
2/2 [==============================] - 0s 35ms/step - loss: 1.1826 - accuracy: 0.5012 - val_loss: 1.0210 - val_accuracy: 0.6630
Epoch 46/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1772 - accuracy: 0.5073 - val_loss: 1.0142 - val_accuracy: 0.6739
Epoch 47/100
2/2 [==============================] - 0s 46ms/step - loss: 1.2163 - accuracy: 0.5061 - val_loss: 1.0073 - val_accuracy: 0.6739
Epoch 48/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1929 - accuracy: 0.5243 - val_loss: 1.0005 - val_accuracy: 0.6739
Epoch 49/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1774 - accuracy: 0.5462 - val_loss: 0.9936 - val_accuracy: 0.6739
Epoch 50/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1547 - accuracy: 0.5438 - val_loss: 0.9867 - val_accuracy: 0.6739
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1493 - accuracy: 0.5462 - val_loss: 0.9798 - val_accuracy: 0.6739
Epoch 52/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1439 - accuracy: 0.5608 - val_loss: 0.9729 - val_accuracy: 0.6848
Epoch 53/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1304 - accuracy: 0.5754 - val_loss: 0.9660 - val_accuracy: 0.6848
Epoch 54/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1231 - accuracy: 0.5669 - val_loss: 0.9591 - val_accuracy: 0.6739
Epoch 55/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1078 - accuracy: 0.5852 - val_loss: 0.9523 - val_accuracy: 0.6739
Epoch 56/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0965 - accuracy: 0.5864 - val_loss: 0.9455 - val_accuracy: 0.6848
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0778 - accuracy: 0.5888 - val_loss: 0.9387 - val_accuracy: 0.6848
Epoch 58/100
2/2 [==============================] - 0s 48ms/step - loss: 1.0889 - accuracy: 0.6083 - val_loss: 0.9318 - val_accuracy: 0.7174
Epoch 59/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0682 - accuracy: 0.6034 - val_loss: 0.9251 - val_accuracy: 0.7174
Epoch 60/100
2/2 [==============================] - 0s 44ms/step - loss: 1.0404 - accuracy: 0.6217 - val_loss: 0.9183 - val_accuracy: 0.7065
Epoch 61/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0535 - accuracy: 0.6229 - val_loss: 0.9116 - val_accuracy: 0.7065
Epoch 62/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0075 - accuracy: 0.6375 - val_loss: 0.9049 - val_accuracy: 0.7065
Epoch 63/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0144 - accuracy: 0.6448 - val_loss: 0.8982 - val_accuracy: 0.7065
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9888 - accuracy: 0.6460 - val_loss: 0.8916 - val_accuracy: 0.7065
Epoch 65/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0083 - accuracy: 0.6545 - val_loss: 0.8850 - val_accuracy: 0.7174
Epoch 66/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9989 - accuracy: 0.6618 - val_loss: 0.8785 - val_accuracy: 0.7174
Epoch 67/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9801 - accuracy: 0.6703 - val_loss: 0.8720 - val_accuracy: 0.7174
Epoch 68/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9736 - accuracy: 0.6886 - val_loss: 0.8655 - val_accuracy: 0.7174
Epoch 69/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9813 - accuracy: 0.6691 - val_loss: 0.8592 - val_accuracy: 0.7174
Epoch 70/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9216 - accuracy: 0.7032 - val_loss: 0.8528 - val_accuracy: 0.7174
Epoch 71/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9132 - accuracy: 0.7080 - val_loss: 0.8466 - val_accuracy: 0.7174
Epoch 72/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9394 - accuracy: 0.7007 - val_loss: 0.8404 - val_accuracy: 0.7283
Epoch 73/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9160 - accuracy: 0.7032 - val_loss: 0.8342 - val_accuracy: 0.7391
Epoch 74/100
2/2 [==============================] - 0s 53ms/step - loss: 0.9190 - accuracy: 0.7105 - val_loss: 0.8282 - val_accuracy: 0.7391
Epoch 75/100
2/2 [==============================] - 0s 46ms/step - loss: 0.9118 - accuracy: 0.7202 - val_loss: 0.8221 - val_accuracy: 0.7391
Epoch 76/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9215 - accuracy: 0.7019 - val_loss: 0.8162 - val_accuracy: 0.7391
Epoch 77/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8930 - accuracy: 0.7238 - val_loss: 0.8103 - val_accuracy: 0.7391
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9060 - accuracy: 0.7190 - val_loss: 0.8045 - val_accuracy: 0.7500
Epoch 79/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8927 - accuracy: 0.7190 - val_loss: 0.7987 - val_accuracy: 0.7500
Epoch 80/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8615 - accuracy: 0.7384 - val_loss: 0.7931 - val_accuracy: 0.7500
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8664 - accuracy: 0.7384 - val_loss: 0.7875 - val_accuracy: 0.7609
Epoch 82/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8652 - accuracy: 0.7567 - val_loss: 0.7820 - val_accuracy: 0.7717
Epoch 83/100
2/2 [==============================] - 0s 27ms/step - loss: 0.8219 - accuracy: 0.7798 - val_loss: 0.7766 - val_accuracy: 0.7717
Epoch 84/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8313 - accuracy: 0.7749 - val_loss: 0.7713 - val_accuracy: 0.7826
Epoch 85/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8356 - accuracy: 0.7591 - val_loss: 0.7660 - val_accuracy: 0.7826
Epoch 86/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8595 - accuracy: 0.7567 - val_loss: 0.7608 - val_accuracy: 0.7826
Epoch 87/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8189 - accuracy: 0.7713 - val_loss: 0.7556 - val_accuracy: 0.7935
Epoch 88/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8354 - accuracy: 0.7628 - val_loss: 0.7506 - val_accuracy: 0.7935
Epoch 89/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8415 - accuracy: 0.7579 - val_loss: 0.7455 - val_accuracy: 0.7826
Epoch 90/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8161 - accuracy: 0.7859 - val_loss: 0.7406 - val_accuracy: 0.7717
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7966 - accuracy: 0.7883 - val_loss: 0.7358 - val_accuracy: 0.7717
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7762 - accuracy: 0.7981 - val_loss: 0.7310 - val_accuracy: 0.7826
Epoch 93/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7764 - accuracy: 0.7798 - val_loss: 0.7263 - val_accuracy: 0.7826
Epoch 94/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7788 - accuracy: 0.7883 - val_loss: 0.7217 - val_accuracy: 0.7826
Epoch 95/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7805 - accuracy: 0.7932 - val_loss: 0.7171 - val_accuracy: 0.7826
Epoch 96/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7560 - accuracy: 0.8114 - val_loss: 0.7126 - val_accuracy: 0.7826
Epoch 97/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7647 - accuracy: 0.8041 - val_loss: 0.7082 - val_accuracy: 0.7826
Epoch 98/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7483 - accuracy: 0.8102 - val_loss: 0.7039 - val_accuracy: 0.7826
Epoch 99/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7425 - accuracy: 0.7871 - val_loss: 0.6996 - val_accuracy: 0.7826
Epoch 100/100
2/2 [==============================] - 0s 46ms/step - loss: 0.7273 - accuracy: 0.8212 - val_loss: 0.6954 - val_accuracy: 0.7935
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 5ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 246ms/step - loss: 1.6091 - accuracy: 0.2117 - val_loss: 1.0757 - val_accuracy: 0.5870
Epoch 2/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6312 - accuracy: 0.1959 - val_loss: 1.0779 - val_accuracy: 0.5761
Epoch 3/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6073 - accuracy: 0.2482 - val_loss: 1.0798 - val_accuracy: 0.5761
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5992 - accuracy: 0.2129 - val_loss: 1.0816 - val_accuracy: 0.5761
Epoch 5/100
2/2 [==============================] - 0s 28ms/step - loss: 1.6191 - accuracy: 0.2238 - val_loss: 1.0831 - val_accuracy: 0.5761
Epoch 6/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6004 - accuracy: 0.2311 - val_loss: 1.0845 - val_accuracy: 0.5761
Epoch 7/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6461 - accuracy: 0.1922 - val_loss: 1.0856 - val_accuracy: 0.5761
Epoch 8/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6058 - accuracy: 0.2214 - val_loss: 1.0864 - val_accuracy: 0.5761
Epoch 9/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6124 - accuracy: 0.2226 - val_loss: 1.0870 - val_accuracy: 0.5870
Epoch 10/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5513 - accuracy: 0.2178 - val_loss: 1.0874 - val_accuracy: 0.5870
Epoch 11/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5840 - accuracy: 0.2251 - val_loss: 1.0875 - val_accuracy: 0.5870
Epoch 12/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5517 - accuracy: 0.2336 - val_loss: 1.0873 - val_accuracy: 0.5870
Epoch 13/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5779 - accuracy: 0.2360 - val_loss: 1.0870 - val_accuracy: 0.5978
Epoch 14/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5516 - accuracy: 0.2457 - val_loss: 1.0865 - val_accuracy: 0.5978
Epoch 15/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5552 - accuracy: 0.2336 - val_loss: 1.0857 - val_accuracy: 0.5978
Epoch 16/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5505 - accuracy: 0.2433 - val_loss: 1.0846 - val_accuracy: 0.6087
Epoch 17/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5502 - accuracy: 0.2311 - val_loss: 1.0835 - val_accuracy: 0.6196
Epoch 18/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5303 - accuracy: 0.2591 - val_loss: 1.0821 - val_accuracy: 0.6196
Epoch 19/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5487 - accuracy: 0.2555 - val_loss: 1.0804 - val_accuracy: 0.6196
Epoch 20/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5165 - accuracy: 0.2397 - val_loss: 1.0786 - val_accuracy: 0.6196
Epoch 21/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4882 - accuracy: 0.2530 - val_loss: 1.0765 - val_accuracy: 0.6304
Epoch 22/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5366 - accuracy: 0.2421 - val_loss: 1.0743 - val_accuracy: 0.6304
Epoch 23/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5026 - accuracy: 0.2567 - val_loss: 1.0719 - val_accuracy: 0.6413
Epoch 24/100
2/2 [==============================] - 0s 37ms/step - loss: 1.4660 - accuracy: 0.2689 - val_loss: 1.0693 - val_accuracy: 0.6522
Epoch 25/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4999 - accuracy: 0.2543 - val_loss: 1.0665 - val_accuracy: 0.6739
Epoch 26/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4736 - accuracy: 0.2591 - val_loss: 1.0636 - val_accuracy: 0.6739
Epoch 27/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4506 - accuracy: 0.2737 - val_loss: 1.0604 - val_accuracy: 0.6739
Epoch 28/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4759 - accuracy: 0.2616 - val_loss: 1.0571 - val_accuracy: 0.6848
Epoch 29/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4276 - accuracy: 0.2920 - val_loss: 1.0538 - val_accuracy: 0.6848
Epoch 30/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4129 - accuracy: 0.2944 - val_loss: 1.0502 - val_accuracy: 0.6848
Epoch 31/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4281 - accuracy: 0.2932 - val_loss: 1.0464 - val_accuracy: 0.6957
Epoch 32/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4036 - accuracy: 0.2993 - val_loss: 1.0426 - val_accuracy: 0.6957
Epoch 33/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3757 - accuracy: 0.3127 - val_loss: 1.0386 - val_accuracy: 0.7174
Epoch 34/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3696 - accuracy: 0.3090 - val_loss: 1.0344 - val_accuracy: 0.7283
Epoch 35/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3545 - accuracy: 0.3406 - val_loss: 1.0301 - val_accuracy: 0.7283
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3709 - accuracy: 0.3273 - val_loss: 1.0257 - val_accuracy: 0.7391
Epoch 37/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3739 - accuracy: 0.3212 - val_loss: 1.0212 - val_accuracy: 0.7391
Epoch 38/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3550 - accuracy: 0.3382 - val_loss: 1.0165 - val_accuracy: 0.7500
Epoch 39/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3183 - accuracy: 0.3589 - val_loss: 1.0118 - val_accuracy: 0.7500
Epoch 40/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3072 - accuracy: 0.3771 - val_loss: 1.0070 - val_accuracy: 0.7500
Epoch 41/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2894 - accuracy: 0.3613 - val_loss: 1.0022 - val_accuracy: 0.7500
Epoch 42/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3085 - accuracy: 0.3808 - val_loss: 0.9972 - val_accuracy: 0.7500
Epoch 43/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2612 - accuracy: 0.3966 - val_loss: 0.9922 - val_accuracy: 0.7500
Epoch 44/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2630 - accuracy: 0.4027 - val_loss: 0.9871 - val_accuracy: 0.7500
Epoch 45/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2643 - accuracy: 0.4063 - val_loss: 0.9820 - val_accuracy: 0.7609
Epoch 46/100
2/2 [==============================] - 0s 34ms/step - loss: 1.2422 - accuracy: 0.4051 - val_loss: 0.9768 - val_accuracy: 0.7717
Epoch 47/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2510 - accuracy: 0.4197 - val_loss: 0.9716 - val_accuracy: 0.7717
Epoch 48/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2225 - accuracy: 0.4209 - val_loss: 0.9662 - val_accuracy: 0.7717
Epoch 49/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2394 - accuracy: 0.4611 - val_loss: 0.9609 - val_accuracy: 0.7717
Epoch 50/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1936 - accuracy: 0.4732 - val_loss: 0.9555 - val_accuracy: 0.7826
Epoch 51/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2122 - accuracy: 0.4501 - val_loss: 0.9501 - val_accuracy: 0.8043
Epoch 52/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1886 - accuracy: 0.4708 - val_loss: 0.9447 - val_accuracy: 0.8043
Epoch 53/100
2/2 [==============================] - 0s 33ms/step - loss: 1.1812 - accuracy: 0.4805 - val_loss: 0.9392 - val_accuracy: 0.8043
Epoch 54/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1815 - accuracy: 0.4647 - val_loss: 0.9338 - val_accuracy: 0.8043
Epoch 55/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1333 - accuracy: 0.4964 - val_loss: 0.9283 - val_accuracy: 0.8043
Epoch 56/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1526 - accuracy: 0.4781 - val_loss: 0.9228 - val_accuracy: 0.8043
Epoch 57/100
2/2 [==============================] - 0s 44ms/step - loss: 1.1574 - accuracy: 0.4866 - val_loss: 0.9174 - val_accuracy: 0.8043
Epoch 58/100
2/2 [==============================] - 0s 45ms/step - loss: 1.1301 - accuracy: 0.5170 - val_loss: 0.9119 - val_accuracy: 0.8043
Epoch 59/100
2/2 [==============================] - 0s 35ms/step - loss: 1.1274 - accuracy: 0.5389 - val_loss: 0.9064 - val_accuracy: 0.8152
Epoch 60/100
2/2 [==============================] - 0s 35ms/step - loss: 1.1031 - accuracy: 0.5255 - val_loss: 0.9009 - val_accuracy: 0.8152
Epoch 61/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1312 - accuracy: 0.5341 - val_loss: 0.8954 - val_accuracy: 0.8152
Epoch 62/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0891 - accuracy: 0.5657 - val_loss: 0.8899 - val_accuracy: 0.8152
Epoch 63/100
2/2 [==============================] - 0s 33ms/step - loss: 1.0737 - accuracy: 0.5730 - val_loss: 0.8845 - val_accuracy: 0.8152
Epoch 64/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0784 - accuracy: 0.5852 - val_loss: 0.8791 - val_accuracy: 0.8370
Epoch 65/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0731 - accuracy: 0.5900 - val_loss: 0.8737 - val_accuracy: 0.8370
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0720 - accuracy: 0.6083 - val_loss: 0.8683 - val_accuracy: 0.8478
Epoch 67/100
2/2 [==============================] - 0s 44ms/step - loss: 1.0526 - accuracy: 0.5803 - val_loss: 0.8630 - val_accuracy: 0.8478
Epoch 68/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0360 - accuracy: 0.6387 - val_loss: 0.8577 - val_accuracy: 0.8478
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0381 - accuracy: 0.6277 - val_loss: 0.8525 - val_accuracy: 0.8478
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0112 - accuracy: 0.6338 - val_loss: 0.8473 - val_accuracy: 0.8478
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0252 - accuracy: 0.6290 - val_loss: 0.8421 - val_accuracy: 0.8478
Epoch 72/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9913 - accuracy: 0.6630 - val_loss: 0.8370 - val_accuracy: 0.8478
Epoch 73/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9880 - accuracy: 0.6448 - val_loss: 0.8319 - val_accuracy: 0.8478
Epoch 74/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9892 - accuracy: 0.6375 - val_loss: 0.8269 - val_accuracy: 0.8478
Epoch 75/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9749 - accuracy: 0.6460 - val_loss: 0.8218 - val_accuracy: 0.8478
Epoch 76/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9939 - accuracy: 0.6642 - val_loss: 0.8169 - val_accuracy: 0.8478
Epoch 77/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9564 - accuracy: 0.6849 - val_loss: 0.8120 - val_accuracy: 0.8478
Epoch 78/100
2/2 [==============================] - 0s 46ms/step - loss: 0.9601 - accuracy: 0.6898 - val_loss: 0.8072 - val_accuracy: 0.8370
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9716 - accuracy: 0.6630 - val_loss: 0.8024 - val_accuracy: 0.8261
Epoch 80/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9363 - accuracy: 0.6946 - val_loss: 0.7976 - val_accuracy: 0.8261
Epoch 81/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9431 - accuracy: 0.6715 - val_loss: 0.7929 - val_accuracy: 0.8261
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9332 - accuracy: 0.7056 - val_loss: 0.7883 - val_accuracy: 0.8261
Epoch 83/100
2/2 [==============================] - 0s 44ms/step - loss: 0.9121 - accuracy: 0.7214 - val_loss: 0.7838 - val_accuracy: 0.8261
Epoch 84/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9122 - accuracy: 0.7044 - val_loss: 0.7792 - val_accuracy: 0.8261
Epoch 85/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8771 - accuracy: 0.7311 - val_loss: 0.7748 - val_accuracy: 0.8261
Epoch 86/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8803 - accuracy: 0.7202 - val_loss: 0.7705 - val_accuracy: 0.8261
Epoch 87/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8914 - accuracy: 0.7482 - val_loss: 0.7661 - val_accuracy: 0.8261
Epoch 88/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9039 - accuracy: 0.7141 - val_loss: 0.7618 - val_accuracy: 0.8261
Epoch 89/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8532 - accuracy: 0.7433 - val_loss: 0.7576 - val_accuracy: 0.8261
Epoch 90/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8652 - accuracy: 0.7409 - val_loss: 0.7534 - val_accuracy: 0.8152
Epoch 91/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8537 - accuracy: 0.7579 - val_loss: 0.7493 - val_accuracy: 0.8043
Epoch 92/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8864 - accuracy: 0.7372 - val_loss: 0.7453 - val_accuracy: 0.8152
Epoch 93/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8478 - accuracy: 0.7652 - val_loss: 0.7414 - val_accuracy: 0.8152
Epoch 94/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8491 - accuracy: 0.7664 - val_loss: 0.7375 - val_accuracy: 0.8152
Epoch 95/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8337 - accuracy: 0.7835 - val_loss: 0.7337 - val_accuracy: 0.8152
Epoch 96/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8229 - accuracy: 0.7798 - val_loss: 0.7299 - val_accuracy: 0.8152
Epoch 97/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8176 - accuracy: 0.7810 - val_loss: 0.7262 - val_accuracy: 0.8152
Epoch 98/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8007 - accuracy: 0.7859 - val_loss: 0.7226 - val_accuracy: 0.8152
Epoch 99/100
2/2 [==============================] - 0s 48ms/step - loss: 0.7999 - accuracy: 0.7762 - val_loss: 0.7190 - val_accuracy: 0.8152
Epoch 100/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8136 - accuracy: 0.7871 - val_loss: 0.7155 - val_accuracy: 0.8152
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
2/2 [==============================] - 1s 235ms/step - loss: 1.7047 - accuracy: 0.3491 - val_loss: 1.5946 - val_accuracy: 0.2283
Epoch 2/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6907 - accuracy: 0.3163 - val_loss: 1.5892 - val_accuracy: 0.2391
Epoch 3/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7032 - accuracy: 0.3394 - val_loss: 1.5838 - val_accuracy: 0.2391
Epoch 4/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6811 - accuracy: 0.3650 - val_loss: 1.5774 - val_accuracy: 0.2500
Epoch 5/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6786 - accuracy: 0.3771 - val_loss: 1.5710 - val_accuracy: 0.2609
Epoch 6/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7121 - accuracy: 0.3540 - val_loss: 1.5643 - val_accuracy: 0.2609
Epoch 7/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7436 - accuracy: 0.3601 - val_loss: 1.5571 - val_accuracy: 0.2609
Epoch 8/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7708 - accuracy: 0.3491 - val_loss: 1.5494 - val_accuracy: 0.2609
Epoch 9/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6516 - accuracy: 0.3504 - val_loss: 1.5414 - val_accuracy: 0.2609
Epoch 10/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7025 - accuracy: 0.3625 - val_loss: 1.5331 - val_accuracy: 0.2717
Epoch 11/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6896 - accuracy: 0.3431 - val_loss: 1.5245 - val_accuracy: 0.2826
Epoch 12/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6485 - accuracy: 0.3613 - val_loss: 1.5155 - val_accuracy: 0.3043
Epoch 13/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6661 - accuracy: 0.3577 - val_loss: 1.5061 - val_accuracy: 0.3043
Epoch 14/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6635 - accuracy: 0.3516 - val_loss: 1.4964 - val_accuracy: 0.3043
Epoch 15/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6289 - accuracy: 0.3516 - val_loss: 1.4866 - val_accuracy: 0.3370
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6720 - accuracy: 0.3564 - val_loss: 1.4765 - val_accuracy: 0.3370
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6762 - accuracy: 0.3723 - val_loss: 1.4659 - val_accuracy: 0.3478
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6084 - accuracy: 0.3723 - val_loss: 1.4552 - val_accuracy: 0.3478
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6230 - accuracy: 0.4100 - val_loss: 1.4441 - val_accuracy: 0.3587
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6117 - accuracy: 0.4039 - val_loss: 1.4327 - val_accuracy: 0.3696
Epoch 21/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5927 - accuracy: 0.3893 - val_loss: 1.4211 - val_accuracy: 0.3804
Epoch 22/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6092 - accuracy: 0.3540 - val_loss: 1.4095 - val_accuracy: 0.3913
Epoch 23/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5484 - accuracy: 0.3783 - val_loss: 1.3975 - val_accuracy: 0.4130
Epoch 24/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5632 - accuracy: 0.3978 - val_loss: 1.3855 - val_accuracy: 0.4130
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6068 - accuracy: 0.4051 - val_loss: 1.3732 - val_accuracy: 0.4348
Epoch 26/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5704 - accuracy: 0.4258 - val_loss: 1.3606 - val_accuracy: 0.4674
Epoch 27/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5151 - accuracy: 0.4136 - val_loss: 1.3480 - val_accuracy: 0.4674
Epoch 28/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5222 - accuracy: 0.4367 - val_loss: 1.3352 - val_accuracy: 0.4674
Epoch 29/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5186 - accuracy: 0.4173 - val_loss: 1.3224 - val_accuracy: 0.4674
Epoch 30/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4653 - accuracy: 0.4416 - val_loss: 1.3093 - val_accuracy: 0.4674
Epoch 31/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4683 - accuracy: 0.4440 - val_loss: 1.2962 - val_accuracy: 0.4674
Epoch 32/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4053 - accuracy: 0.4465 - val_loss: 1.2828 - val_accuracy: 0.4783
Epoch 33/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4680 - accuracy: 0.4526 - val_loss: 1.2693 - val_accuracy: 0.4783
Epoch 34/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4344 - accuracy: 0.4659 - val_loss: 1.2558 - val_accuracy: 0.4783
Epoch 35/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4753 - accuracy: 0.4477 - val_loss: 1.2423 - val_accuracy: 0.5109
Epoch 36/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3775 - accuracy: 0.4635 - val_loss: 1.2288 - val_accuracy: 0.5109
Epoch 37/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3535 - accuracy: 0.4745 - val_loss: 1.2154 - val_accuracy: 0.5326
Epoch 38/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3390 - accuracy: 0.4915 - val_loss: 1.2020 - val_accuracy: 0.5543
Epoch 39/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3646 - accuracy: 0.4915 - val_loss: 1.1886 - val_accuracy: 0.5761
Epoch 40/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3955 - accuracy: 0.4696 - val_loss: 1.1749 - val_accuracy: 0.5870
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2852 - accuracy: 0.5122 - val_loss: 1.1612 - val_accuracy: 0.5870
Epoch 42/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3151 - accuracy: 0.4988 - val_loss: 1.1477 - val_accuracy: 0.6087
Epoch 43/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3113 - accuracy: 0.4903 - val_loss: 1.1344 - val_accuracy: 0.6196
Epoch 44/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2685 - accuracy: 0.5316 - val_loss: 1.1210 - val_accuracy: 0.6522
Epoch 45/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2498 - accuracy: 0.5426 - val_loss: 1.1076 - val_accuracy: 0.6522
Epoch 46/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2711 - accuracy: 0.5414 - val_loss: 1.0943 - val_accuracy: 0.6630
Epoch 47/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2757 - accuracy: 0.5328 - val_loss: 1.0808 - val_accuracy: 0.6848
Epoch 48/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2555 - accuracy: 0.5341 - val_loss: 1.0677 - val_accuracy: 0.6848
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2387 - accuracy: 0.5535 - val_loss: 1.0546 - val_accuracy: 0.6848
Epoch 50/100
2/2 [==============================] - 0s 42ms/step - loss: 1.1916 - accuracy: 0.5669 - val_loss: 1.0417 - val_accuracy: 0.7065
Epoch 51/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1892 - accuracy: 0.5657 - val_loss: 1.0287 - val_accuracy: 0.7174
Epoch 52/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2143 - accuracy: 0.6034 - val_loss: 1.0160 - val_accuracy: 0.7283
Epoch 53/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1759 - accuracy: 0.5925 - val_loss: 1.0033 - val_accuracy: 0.7391
Epoch 54/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1395 - accuracy: 0.6010 - val_loss: 0.9907 - val_accuracy: 0.7500
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1841 - accuracy: 0.5925 - val_loss: 0.9784 - val_accuracy: 0.7609
Epoch 56/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1596 - accuracy: 0.6010 - val_loss: 0.9662 - val_accuracy: 0.7609
Epoch 57/100
2/2 [==============================] - 0s 45ms/step - loss: 1.1480 - accuracy: 0.6253 - val_loss: 0.9539 - val_accuracy: 0.7717
Epoch 58/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1351 - accuracy: 0.6180 - val_loss: 0.9417 - val_accuracy: 0.7935
Epoch 59/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1137 - accuracy: 0.6594 - val_loss: 0.9298 - val_accuracy: 0.8043
Epoch 60/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0898 - accuracy: 0.6350 - val_loss: 0.9179 - val_accuracy: 0.8152
Epoch 61/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1218 - accuracy: 0.6387 - val_loss: 0.9063 - val_accuracy: 0.8152
Epoch 62/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0846 - accuracy: 0.6582 - val_loss: 0.8948 - val_accuracy: 0.8152
Epoch 63/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0665 - accuracy: 0.6703 - val_loss: 0.8834 - val_accuracy: 0.8152
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0472 - accuracy: 0.6788 - val_loss: 0.8722 - val_accuracy: 0.8261
Epoch 65/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0448 - accuracy: 0.6800 - val_loss: 0.8611 - val_accuracy: 0.8261
Epoch 66/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0163 - accuracy: 0.6898 - val_loss: 0.8502 - val_accuracy: 0.8370
Epoch 67/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9899 - accuracy: 0.7105 - val_loss: 0.8394 - val_accuracy: 0.8370
Epoch 68/100
2/2 [==============================] - 0s 49ms/step - loss: 1.0333 - accuracy: 0.6995 - val_loss: 0.8289 - val_accuracy: 0.8478
Epoch 69/100
2/2 [==============================] - 0s 29ms/step - loss: 1.0093 - accuracy: 0.7092 - val_loss: 0.8185 - val_accuracy: 0.8478
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9724 - accuracy: 0.7141 - val_loss: 0.8085 - val_accuracy: 0.8478
Epoch 71/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9769 - accuracy: 0.7324 - val_loss: 0.7986 - val_accuracy: 0.8478
Epoch 72/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9783 - accuracy: 0.7178 - val_loss: 0.7887 - val_accuracy: 0.8478
Epoch 73/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9417 - accuracy: 0.7324 - val_loss: 0.7790 - val_accuracy: 0.8478
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9149 - accuracy: 0.7518 - val_loss: 0.7697 - val_accuracy: 0.8370
Epoch 75/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9591 - accuracy: 0.7178 - val_loss: 0.7605 - val_accuracy: 0.8370
Epoch 76/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9583 - accuracy: 0.7226 - val_loss: 0.7515 - val_accuracy: 0.8370
Epoch 77/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9118 - accuracy: 0.7409 - val_loss: 0.7426 - val_accuracy: 0.8478
Epoch 78/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9054 - accuracy: 0.7433 - val_loss: 0.7339 - val_accuracy: 0.8478
Epoch 79/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9090 - accuracy: 0.7506 - val_loss: 0.7253 - val_accuracy: 0.8478
Epoch 80/100
2/2 [==============================] - 0s 86ms/step - loss: 0.8975 - accuracy: 0.7482 - val_loss: 0.7170 - val_accuracy: 0.8478
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8818 - accuracy: 0.7591 - val_loss: 0.7086 - val_accuracy: 0.8478
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9017 - accuracy: 0.7701 - val_loss: 0.7006 - val_accuracy: 0.8587
Epoch 83/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8673 - accuracy: 0.7494 - val_loss: 0.6927 - val_accuracy: 0.8587
Epoch 84/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8514 - accuracy: 0.7713 - val_loss: 0.6850 - val_accuracy: 0.8587
Epoch 85/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8679 - accuracy: 0.7506 - val_loss: 0.6775 - val_accuracy: 0.8587
Epoch 86/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8436 - accuracy: 0.7920 - val_loss: 0.6703 - val_accuracy: 0.8696
Epoch 87/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8407 - accuracy: 0.7689 - val_loss: 0.6632 - val_accuracy: 0.8696
Epoch 88/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8325 - accuracy: 0.7859 - val_loss: 0.6562 - val_accuracy: 0.8696
Epoch 89/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8470 - accuracy: 0.7798 - val_loss: 0.6494 - val_accuracy: 0.8696
Epoch 90/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8414 - accuracy: 0.7762 - val_loss: 0.6427 - val_accuracy: 0.8913
Epoch 91/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8519 - accuracy: 0.7822 - val_loss: 0.6363 - val_accuracy: 0.8913
Epoch 92/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8051 - accuracy: 0.7895 - val_loss: 0.6299 - val_accuracy: 0.8913
Epoch 93/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8481 - accuracy: 0.7798 - val_loss: 0.6237 - val_accuracy: 0.8913
Epoch 94/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7912 - accuracy: 0.7908 - val_loss: 0.6177 - val_accuracy: 0.8913
Epoch 95/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7833 - accuracy: 0.8029 - val_loss: 0.6118 - val_accuracy: 0.8913
Epoch 96/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7814 - accuracy: 0.8066 - val_loss: 0.6061 - val_accuracy: 0.9022
Epoch 97/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7778 - accuracy: 0.8005 - val_loss: 0.6006 - val_accuracy: 0.9022
Epoch 98/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7895 - accuracy: 0.8054 - val_loss: 0.5951 - val_accuracy: 0.9022
Epoch 99/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7703 - accuracy: 0.8090 - val_loss: 0.5899 - val_accuracy: 0.9022
Epoch 100/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7785 - accuracy: 0.7993 - val_loss: 0.5846 - val_accuracy: 0.9022
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 7ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 329ms/step - loss: 1.8361 - accuracy: 0.2989 - val_loss: 1.4369 - val_accuracy: 0.2527
Epoch 2/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7888 - accuracy: 0.2928 - val_loss: 1.4372 - val_accuracy: 0.2637
Epoch 3/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7836 - accuracy: 0.2953 - val_loss: 1.4368 - val_accuracy: 0.2637
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7655 - accuracy: 0.2953 - val_loss: 1.4361 - val_accuracy: 0.2637
Epoch 5/100
2/2 [==============================] - 0s 45ms/step - loss: 1.7837 - accuracy: 0.3038 - val_loss: 1.4349 - val_accuracy: 0.2637
Epoch 6/100
2/2 [==============================] - 0s 57ms/step - loss: 1.7771 - accuracy: 0.2953 - val_loss: 1.4333 - val_accuracy: 0.2637
Epoch 7/100
2/2 [==============================] - 0s 46ms/step - loss: 1.8027 - accuracy: 0.3147 - val_loss: 1.4311 - val_accuracy: 0.2747
Epoch 8/100
2/2 [==============================] - 0s 59ms/step - loss: 1.8099 - accuracy: 0.3038 - val_loss: 1.4285 - val_accuracy: 0.2747
Epoch 9/100
2/2 [==============================] - 0s 50ms/step - loss: 1.7743 - accuracy: 0.3001 - val_loss: 1.4255 - val_accuracy: 0.2747
Epoch 10/100
2/2 [==============================] - 0s 51ms/step - loss: 1.7781 - accuracy: 0.3232 - val_loss: 1.4220 - val_accuracy: 0.2747
Epoch 11/100
2/2 [==============================] - 0s 65ms/step - loss: 1.7404 - accuracy: 0.3159 - val_loss: 1.4180 - val_accuracy: 0.2747
Epoch 12/100
2/2 [==============================] - 0s 49ms/step - loss: 1.7223 - accuracy: 0.3123 - val_loss: 1.4136 - val_accuracy: 0.2747
Epoch 13/100
2/2 [==============================] - 0s 46ms/step - loss: 1.7364 - accuracy: 0.3123 - val_loss: 1.4087 - val_accuracy: 0.2747
Epoch 14/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7301 - accuracy: 0.3147 - val_loss: 1.4035 - val_accuracy: 0.2857
Epoch 15/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6829 - accuracy: 0.3244 - val_loss: 1.3979 - val_accuracy: 0.2857
Epoch 16/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7307 - accuracy: 0.3329 - val_loss: 1.3918 - val_accuracy: 0.2857
Epoch 17/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6175 - accuracy: 0.3524 - val_loss: 1.3854 - val_accuracy: 0.2857
Epoch 18/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6463 - accuracy: 0.3451 - val_loss: 1.3786 - val_accuracy: 0.2967
Epoch 19/100
2/2 [==============================] - 0s 58ms/step - loss: 1.6596 - accuracy: 0.3390 - val_loss: 1.3715 - val_accuracy: 0.2967
Epoch 20/100
2/2 [==============================] - 0s 53ms/step - loss: 1.6635 - accuracy: 0.3475 - val_loss: 1.3642 - val_accuracy: 0.3077
Epoch 21/100
2/2 [==============================] - 0s 57ms/step - loss: 1.6582 - accuracy: 0.3548 - val_loss: 1.3564 - val_accuracy: 0.3077
Epoch 22/100
2/2 [==============================] - 0s 49ms/step - loss: 1.6123 - accuracy: 0.3609 - val_loss: 1.3482 - val_accuracy: 0.3077
Epoch 23/100
2/2 [==============================] - 0s 51ms/step - loss: 1.6181 - accuracy: 0.3706 - val_loss: 1.3399 - val_accuracy: 0.3187
Epoch 24/100
2/2 [==============================] - 0s 59ms/step - loss: 1.6279 - accuracy: 0.3633 - val_loss: 1.3311 - val_accuracy: 0.3297
Epoch 25/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5831 - accuracy: 0.3791 - val_loss: 1.3222 - val_accuracy: 0.3297
Epoch 26/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5921 - accuracy: 0.3670 - val_loss: 1.3130 - val_accuracy: 0.3297
Epoch 27/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5412 - accuracy: 0.4022 - val_loss: 1.3035 - val_accuracy: 0.3297
Epoch 28/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5209 - accuracy: 0.4058 - val_loss: 1.2938 - val_accuracy: 0.3516
Epoch 29/100
2/2 [==============================] - 0s 49ms/step - loss: 1.5200 - accuracy: 0.4228 - val_loss: 1.2839 - val_accuracy: 0.3736
Epoch 30/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5330 - accuracy: 0.4046 - val_loss: 1.2739 - val_accuracy: 0.3736
Epoch 31/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4993 - accuracy: 0.4046 - val_loss: 1.2638 - val_accuracy: 0.3956
Epoch 32/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4741 - accuracy: 0.4119 - val_loss: 1.2534 - val_accuracy: 0.4505
Epoch 33/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4829 - accuracy: 0.4277 - val_loss: 1.2429 - val_accuracy: 0.4505
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4606 - accuracy: 0.4313 - val_loss: 1.2323 - val_accuracy: 0.4835
Epoch 35/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4238 - accuracy: 0.4629 - val_loss: 1.2213 - val_accuracy: 0.4945
Epoch 36/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4094 - accuracy: 0.4739 - val_loss: 1.2104 - val_accuracy: 0.5055
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4746 - accuracy: 0.4459 - val_loss: 1.1993 - val_accuracy: 0.5055
Epoch 38/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3797 - accuracy: 0.4727 - val_loss: 1.1883 - val_accuracy: 0.5385
Epoch 39/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3772 - accuracy: 0.4945 - val_loss: 1.1771 - val_accuracy: 0.5495
Epoch 40/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3877 - accuracy: 0.4800 - val_loss: 1.1658 - val_accuracy: 0.5714
Epoch 41/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3761 - accuracy: 0.4775 - val_loss: 1.1545 - val_accuracy: 0.5824
Epoch 42/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3122 - accuracy: 0.4982 - val_loss: 1.1430 - val_accuracy: 0.6154
Epoch 43/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3497 - accuracy: 0.5043 - val_loss: 1.1317 - val_accuracy: 0.6374
Epoch 44/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3118 - accuracy: 0.5213 - val_loss: 1.1202 - val_accuracy: 0.6374
Epoch 45/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2841 - accuracy: 0.5419 - val_loss: 1.1090 - val_accuracy: 0.6374
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3120 - accuracy: 0.5480 - val_loss: 1.0977 - val_accuracy: 0.6374
Epoch 47/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2751 - accuracy: 0.5456 - val_loss: 1.0864 - val_accuracy: 0.6374
Epoch 48/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2565 - accuracy: 0.5601 - val_loss: 1.0752 - val_accuracy: 0.6484
Epoch 49/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2438 - accuracy: 0.5565 - val_loss: 1.0641 - val_accuracy: 0.6593
Epoch 50/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2542 - accuracy: 0.5735 - val_loss: 1.0530 - val_accuracy: 0.6813
Epoch 51/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2533 - accuracy: 0.5699 - val_loss: 1.0420 - val_accuracy: 0.6923
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2123 - accuracy: 0.5942 - val_loss: 1.0310 - val_accuracy: 0.6923
Epoch 53/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1470 - accuracy: 0.6258 - val_loss: 1.0202 - val_accuracy: 0.6923
Epoch 54/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1645 - accuracy: 0.5869 - val_loss: 1.0095 - val_accuracy: 0.7033
Epoch 55/100
2/2 [==============================] - 0s 29ms/step - loss: 1.2123 - accuracy: 0.5990 - val_loss: 0.9989 - val_accuracy: 0.7033
Epoch 56/100
2/2 [==============================] - 0s 42ms/step - loss: 1.1377 - accuracy: 0.6245 - val_loss: 0.9885 - val_accuracy: 0.7143
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1043 - accuracy: 0.6428 - val_loss: 0.9783 - val_accuracy: 0.7363
Epoch 58/100
2/2 [==============================] - 0s 34ms/step - loss: 1.1439 - accuracy: 0.6136 - val_loss: 0.9680 - val_accuracy: 0.7363
Epoch 59/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1653 - accuracy: 0.6221 - val_loss: 0.9579 - val_accuracy: 0.7363
Epoch 60/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1512 - accuracy: 0.6245 - val_loss: 0.9482 - val_accuracy: 0.7363
Epoch 61/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1370 - accuracy: 0.6209 - val_loss: 0.9384 - val_accuracy: 0.7473
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 1.1289 - accuracy: 0.6355 - val_loss: 0.9287 - val_accuracy: 0.7582
Epoch 63/100
2/2 [==============================] - 0s 46ms/step - loss: 1.1083 - accuracy: 0.6574 - val_loss: 0.9192 - val_accuracy: 0.7582
Epoch 64/100
2/2 [==============================] - 0s 50ms/step - loss: 1.0432 - accuracy: 0.6671 - val_loss: 0.9099 - val_accuracy: 0.7582
Epoch 65/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0266 - accuracy: 0.7047 - val_loss: 0.9007 - val_accuracy: 0.7582
Epoch 66/100
2/2 [==============================] - 0s 27ms/step - loss: 1.0250 - accuracy: 0.7023 - val_loss: 0.8917 - val_accuracy: 0.7692
Epoch 67/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0550 - accuracy: 0.6974 - val_loss: 0.8829 - val_accuracy: 0.7692
Epoch 68/100
2/2 [==============================] - 0s 50ms/step - loss: 1.0472 - accuracy: 0.6817 - val_loss: 0.8743 - val_accuracy: 0.7692
Epoch 69/100
2/2 [==============================] - 0s 28ms/step - loss: 1.0392 - accuracy: 0.6902 - val_loss: 0.8657 - val_accuracy: 0.7912
Epoch 70/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0072 - accuracy: 0.6926 - val_loss: 0.8574 - val_accuracy: 0.8022
Epoch 71/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0056 - accuracy: 0.7084 - val_loss: 0.8492 - val_accuracy: 0.8022
Epoch 72/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0256 - accuracy: 0.6938 - val_loss: 0.8412 - val_accuracy: 0.8022
Epoch 73/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9726 - accuracy: 0.7266 - val_loss: 0.8334 - val_accuracy: 0.8022
Epoch 74/100
2/2 [==============================] - 0s 48ms/step - loss: 0.9874 - accuracy: 0.7278 - val_loss: 0.8257 - val_accuracy: 0.8242
Epoch 75/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9447 - accuracy: 0.7363 - val_loss: 0.8181 - val_accuracy: 0.8242
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9872 - accuracy: 0.7217 - val_loss: 0.8107 - val_accuracy: 0.8242
Epoch 77/100
2/2 [==============================] - 0s 30ms/step - loss: 0.9548 - accuracy: 0.7303 - val_loss: 0.8034 - val_accuracy: 0.8242
Epoch 78/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9361 - accuracy: 0.7448 - val_loss: 0.7964 - val_accuracy: 0.8242
Epoch 79/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9313 - accuracy: 0.7278 - val_loss: 0.7895 - val_accuracy: 0.8352
Epoch 80/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9485 - accuracy: 0.7254 - val_loss: 0.7827 - val_accuracy: 0.8352
Epoch 81/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9606 - accuracy: 0.7157 - val_loss: 0.7759 - val_accuracy: 0.8352
Epoch 82/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9144 - accuracy: 0.7582 - val_loss: 0.7695 - val_accuracy: 0.8352
Epoch 83/100
2/2 [==============================] - 0s 51ms/step - loss: 0.9344 - accuracy: 0.7388 - val_loss: 0.7632 - val_accuracy: 0.8352
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9299 - accuracy: 0.7448 - val_loss: 0.7571 - val_accuracy: 0.8352
Epoch 85/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9083 - accuracy: 0.7497 - val_loss: 0.7509 - val_accuracy: 0.8462
Epoch 86/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8979 - accuracy: 0.7631 - val_loss: 0.7450 - val_accuracy: 0.8462
Epoch 87/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9126 - accuracy: 0.7655 - val_loss: 0.7391 - val_accuracy: 0.8462
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8365 - accuracy: 0.7874 - val_loss: 0.7335 - val_accuracy: 0.8571
Epoch 89/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8779 - accuracy: 0.7643 - val_loss: 0.7279 - val_accuracy: 0.8681
Epoch 90/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8583 - accuracy: 0.7704 - val_loss: 0.7224 - val_accuracy: 0.8681
Epoch 91/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8587 - accuracy: 0.7776 - val_loss: 0.7171 - val_accuracy: 0.8681
Epoch 92/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8584 - accuracy: 0.7740 - val_loss: 0.7119 - val_accuracy: 0.8681
Epoch 93/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8757 - accuracy: 0.7655 - val_loss: 0.7068 - val_accuracy: 0.8681
Epoch 94/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8815 - accuracy: 0.7655 - val_loss: 0.7018 - val_accuracy: 0.8681
Epoch 95/100
2/2 [==============================] - 0s 29ms/step - loss: 0.8589 - accuracy: 0.7691 - val_loss: 0.6969 - val_accuracy: 0.8681
Epoch 96/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8307 - accuracy: 0.7983 - val_loss: 0.6921 - val_accuracy: 0.8681
Epoch 97/100
2/2 [==============================] - 0s 27ms/step - loss: 0.8468 - accuracy: 0.7898 - val_loss: 0.6874 - val_accuracy: 0.8681
Epoch 98/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8299 - accuracy: 0.7861 - val_loss: 0.6828 - val_accuracy: 0.8681
Epoch 99/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8115 - accuracy: 0.7971 - val_loss: 0.6783 - val_accuracy: 0.8681
Epoch 100/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8187 - accuracy: 0.7947 - val_loss: 0.6740 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 250ms/step - loss: 1.8431 - accuracy: 0.2880 - val_loss: 1.1962 - val_accuracy: 0.5275
Epoch 2/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7923 - accuracy: 0.2904 - val_loss: 1.1991 - val_accuracy: 0.5275
Epoch 3/100
2/2 [==============================] - 0s 49ms/step - loss: 1.8788 - accuracy: 0.2819 - val_loss: 1.2015 - val_accuracy: 0.5275
Epoch 4/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8351 - accuracy: 0.2783 - val_loss: 1.2035 - val_accuracy: 0.5055
Epoch 5/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7981 - accuracy: 0.2770 - val_loss: 1.2051 - val_accuracy: 0.5055
Epoch 6/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8011 - accuracy: 0.2989 - val_loss: 1.2062 - val_accuracy: 0.4945
Epoch 7/100
2/2 [==============================] - 0s 49ms/step - loss: 1.8350 - accuracy: 0.2953 - val_loss: 1.2069 - val_accuracy: 0.4945
Epoch 8/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8111 - accuracy: 0.3013 - val_loss: 1.2071 - val_accuracy: 0.4945
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7817 - accuracy: 0.2843 - val_loss: 1.2070 - val_accuracy: 0.5055
Epoch 10/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7529 - accuracy: 0.3135 - val_loss: 1.2065 - val_accuracy: 0.5055
Epoch 11/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7584 - accuracy: 0.3159 - val_loss: 1.2055 - val_accuracy: 0.5165
Epoch 12/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8066 - accuracy: 0.2989 - val_loss: 1.2041 - val_accuracy: 0.5165
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7883 - accuracy: 0.3050 - val_loss: 1.2024 - val_accuracy: 0.5165
Epoch 14/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7252 - accuracy: 0.3366 - val_loss: 1.2003 - val_accuracy: 0.5165
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7188 - accuracy: 0.3183 - val_loss: 1.1980 - val_accuracy: 0.5275
Epoch 16/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7480 - accuracy: 0.3244 - val_loss: 1.1951 - val_accuracy: 0.5385
Epoch 17/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6936 - accuracy: 0.3256 - val_loss: 1.1920 - val_accuracy: 0.5385
Epoch 18/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7506 - accuracy: 0.3244 - val_loss: 1.1886 - val_accuracy: 0.5385
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7138 - accuracy: 0.3244 - val_loss: 1.1850 - val_accuracy: 0.5385
Epoch 20/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7043 - accuracy: 0.3402 - val_loss: 1.1810 - val_accuracy: 0.5385
Epoch 21/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6529 - accuracy: 0.3499 - val_loss: 1.1767 - val_accuracy: 0.5495
Epoch 22/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6892 - accuracy: 0.3621 - val_loss: 1.1722 - val_accuracy: 0.5495
Epoch 23/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6160 - accuracy: 0.3536 - val_loss: 1.1674 - val_accuracy: 0.5604
Epoch 24/100
2/2 [==============================] - 0s 48ms/step - loss: 1.6274 - accuracy: 0.3572 - val_loss: 1.1624 - val_accuracy: 0.5604
Epoch 25/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6613 - accuracy: 0.3414 - val_loss: 1.1571 - val_accuracy: 0.5714
Epoch 26/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6114 - accuracy: 0.3597 - val_loss: 1.1516 - val_accuracy: 0.5934
Epoch 27/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6429 - accuracy: 0.3682 - val_loss: 1.1459 - val_accuracy: 0.5934
Epoch 28/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6021 - accuracy: 0.3864 - val_loss: 1.1400 - val_accuracy: 0.5934
Epoch 29/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5914 - accuracy: 0.3755 - val_loss: 1.1340 - val_accuracy: 0.5934
Epoch 30/100
2/2 [==============================] - 0s 36ms/step - loss: 1.5562 - accuracy: 0.3864 - val_loss: 1.1278 - val_accuracy: 0.5934
Epoch 31/100
2/2 [==============================] - 0s 39ms/step - loss: 1.5429 - accuracy: 0.4034 - val_loss: 1.1214 - val_accuracy: 0.6154
Epoch 32/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5344 - accuracy: 0.3633 - val_loss: 1.1149 - val_accuracy: 0.6154
Epoch 33/100
2/2 [==============================] - 0s 50ms/step - loss: 1.5214 - accuracy: 0.3998 - val_loss: 1.1082 - val_accuracy: 0.6374
Epoch 34/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4957 - accuracy: 0.4168 - val_loss: 1.1013 - val_accuracy: 0.6484
Epoch 35/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4826 - accuracy: 0.4350 - val_loss: 1.0943 - val_accuracy: 0.6593
Epoch 36/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4500 - accuracy: 0.4386 - val_loss: 1.0873 - val_accuracy: 0.6593
Epoch 37/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4866 - accuracy: 0.4241 - val_loss: 1.0803 - val_accuracy: 0.6703
Epoch 38/100
2/2 [==============================] - 0s 34ms/step - loss: 1.4838 - accuracy: 0.4228 - val_loss: 1.0731 - val_accuracy: 0.6703
Epoch 39/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4091 - accuracy: 0.4496 - val_loss: 1.0659 - val_accuracy: 0.6703
Epoch 40/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3753 - accuracy: 0.4714 - val_loss: 1.0586 - val_accuracy: 0.6813
Epoch 41/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4029 - accuracy: 0.4739 - val_loss: 1.0512 - val_accuracy: 0.6813
Epoch 42/100
2/2 [==============================] - 0s 35ms/step - loss: 1.3855 - accuracy: 0.4787 - val_loss: 1.0438 - val_accuracy: 0.6813
Epoch 43/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3458 - accuracy: 0.4800 - val_loss: 1.0363 - val_accuracy: 0.6813
Epoch 44/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3796 - accuracy: 0.4666 - val_loss: 1.0289 - val_accuracy: 0.6813
Epoch 45/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3278 - accuracy: 0.4933 - val_loss: 1.0215 - val_accuracy: 0.6813
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3047 - accuracy: 0.4982 - val_loss: 1.0140 - val_accuracy: 0.6813
Epoch 47/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3106 - accuracy: 0.4982 - val_loss: 1.0066 - val_accuracy: 0.6813
Epoch 48/100
2/2 [==============================] - 0s 50ms/step - loss: 1.2865 - accuracy: 0.5419 - val_loss: 0.9991 - val_accuracy: 0.6813
Epoch 49/100
2/2 [==============================] - 0s 34ms/step - loss: 1.2840 - accuracy: 0.5079 - val_loss: 0.9917 - val_accuracy: 0.6923
Epoch 50/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2509 - accuracy: 0.5358 - val_loss: 0.9842 - val_accuracy: 0.7033
Epoch 51/100
2/2 [==============================] - 0s 34ms/step - loss: 1.2470 - accuracy: 0.5286 - val_loss: 0.9769 - val_accuracy: 0.7143
Epoch 52/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2231 - accuracy: 0.5395 - val_loss: 0.9696 - val_accuracy: 0.7143
Epoch 53/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1923 - accuracy: 0.5504 - val_loss: 0.9624 - val_accuracy: 0.7253
Epoch 54/100
2/2 [==============================] - 0s 46ms/step - loss: 1.2055 - accuracy: 0.5759 - val_loss: 0.9552 - val_accuracy: 0.7363
Epoch 55/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1978 - accuracy: 0.5711 - val_loss: 0.9481 - val_accuracy: 0.7363
Epoch 56/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2011 - accuracy: 0.5626 - val_loss: 0.9410 - val_accuracy: 0.7363
Epoch 57/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1629 - accuracy: 0.5759 - val_loss: 0.9340 - val_accuracy: 0.7473
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 1.1430 - accuracy: 0.6015 - val_loss: 0.9270 - val_accuracy: 0.7473
Epoch 59/100
2/2 [==============================] - 0s 73ms/step - loss: 1.1545 - accuracy: 0.6027 - val_loss: 0.9201 - val_accuracy: 0.7473
Epoch 60/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1207 - accuracy: 0.5893 - val_loss: 0.9132 - val_accuracy: 0.7473
Epoch 61/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1210 - accuracy: 0.6148 - val_loss: 0.9065 - val_accuracy: 0.7582
Epoch 62/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0910 - accuracy: 0.6185 - val_loss: 0.8998 - val_accuracy: 0.7692
Epoch 63/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1121 - accuracy: 0.6136 - val_loss: 0.8932 - val_accuracy: 0.7692
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0737 - accuracy: 0.6306 - val_loss: 0.8867 - val_accuracy: 0.7692
Epoch 65/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0789 - accuracy: 0.6318 - val_loss: 0.8802 - val_accuracy: 0.7692
Epoch 66/100
2/2 [==============================] - 0s 49ms/step - loss: 1.0525 - accuracy: 0.6561 - val_loss: 0.8738 - val_accuracy: 0.7802
Epoch 67/100
2/2 [==============================] - 0s 46ms/step - loss: 1.0650 - accuracy: 0.6452 - val_loss: 0.8675 - val_accuracy: 0.7912
Epoch 68/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0262 - accuracy: 0.6549 - val_loss: 0.8613 - val_accuracy: 0.7912
Epoch 69/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0477 - accuracy: 0.6634 - val_loss: 0.8552 - val_accuracy: 0.7912
Epoch 70/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0226 - accuracy: 0.6598 - val_loss: 0.8492 - val_accuracy: 0.7912
Epoch 71/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9984 - accuracy: 0.6744 - val_loss: 0.8432 - val_accuracy: 0.7912
Epoch 72/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0247 - accuracy: 0.6634 - val_loss: 0.8373 - val_accuracy: 0.7912
Epoch 73/100
2/2 [==============================] - 0s 85ms/step - loss: 0.9828 - accuracy: 0.6829 - val_loss: 0.8315 - val_accuracy: 0.7912
Epoch 74/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9781 - accuracy: 0.6865 - val_loss: 0.8257 - val_accuracy: 0.7912
Epoch 75/100
2/2 [==============================] - 0s 48ms/step - loss: 0.9628 - accuracy: 0.6914 - val_loss: 0.8201 - val_accuracy: 0.7912
Epoch 76/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9758 - accuracy: 0.6914 - val_loss: 0.8145 - val_accuracy: 0.7912
Epoch 77/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9588 - accuracy: 0.7047 - val_loss: 0.8092 - val_accuracy: 0.7912
Epoch 78/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9655 - accuracy: 0.7060 - val_loss: 0.8038 - val_accuracy: 0.7912
Epoch 79/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8993 - accuracy: 0.7145 - val_loss: 0.7985 - val_accuracy: 0.7912
Epoch 80/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9352 - accuracy: 0.7084 - val_loss: 0.7934 - val_accuracy: 0.7912
Epoch 81/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9146 - accuracy: 0.7181 - val_loss: 0.7883 - val_accuracy: 0.7912
Epoch 82/100
2/2 [==============================] - 0s 49ms/step - loss: 0.9034 - accuracy: 0.7169 - val_loss: 0.7833 - val_accuracy: 0.7912
Epoch 83/100
2/2 [==============================] - 0s 52ms/step - loss: 0.8863 - accuracy: 0.7132 - val_loss: 0.7784 - val_accuracy: 0.7912
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8617 - accuracy: 0.7412 - val_loss: 0.7736 - val_accuracy: 0.7912
Epoch 85/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8752 - accuracy: 0.7400 - val_loss: 0.7688 - val_accuracy: 0.7912
Epoch 86/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8388 - accuracy: 0.7473 - val_loss: 0.7642 - val_accuracy: 0.7912
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8591 - accuracy: 0.7533 - val_loss: 0.7597 - val_accuracy: 0.7912
Epoch 88/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8390 - accuracy: 0.7704 - val_loss: 0.7553 - val_accuracy: 0.7912
Epoch 89/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8430 - accuracy: 0.7436 - val_loss: 0.7509 - val_accuracy: 0.8132
Epoch 90/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8368 - accuracy: 0.7448 - val_loss: 0.7466 - val_accuracy: 0.8132
Epoch 91/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8366 - accuracy: 0.7667 - val_loss: 0.7424 - val_accuracy: 0.8132
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8369 - accuracy: 0.7594 - val_loss: 0.7383 - val_accuracy: 0.8132
Epoch 93/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8126 - accuracy: 0.7667 - val_loss: 0.7342 - val_accuracy: 0.8132
Epoch 94/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8143 - accuracy: 0.7582 - val_loss: 0.7303 - val_accuracy: 0.8242
Epoch 95/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8115 - accuracy: 0.7728 - val_loss: 0.7264 - val_accuracy: 0.8242
Epoch 96/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8082 - accuracy: 0.7667 - val_loss: 0.7226 - val_accuracy: 0.8242
Epoch 97/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8131 - accuracy: 0.7533 - val_loss: 0.7189 - val_accuracy: 0.8242
Epoch 98/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8039 - accuracy: 0.7716 - val_loss: 0.7152 - val_accuracy: 0.8242
Epoch 99/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7653 - accuracy: 0.7947 - val_loss: 0.7116 - val_accuracy: 0.8242
Epoch 100/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7740 - accuracy: 0.7789 - val_loss: 0.7080 - val_accuracy: 0.8242
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 262us/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 265ms/step - loss: 2.2521 - accuracy: 0.2977 - val_loss: 1.0946 - val_accuracy: 0.6044
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 2.2106 - accuracy: 0.3026 - val_loss: 1.1007 - val_accuracy: 0.6044
Epoch 3/100
2/2 [==============================] - 0s 33ms/step - loss: 2.2567 - accuracy: 0.2953 - val_loss: 1.1061 - val_accuracy: 0.6044
Epoch 4/100
2/2 [==============================] - 0s 32ms/step - loss: 2.2387 - accuracy: 0.3001 - val_loss: 1.1109 - val_accuracy: 0.6044
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 2.2585 - accuracy: 0.2953 - val_loss: 1.1147 - val_accuracy: 0.6044
Epoch 6/100
2/2 [==============================] - 0s 39ms/step - loss: 2.2673 - accuracy: 0.2928 - val_loss: 1.1173 - val_accuracy: 0.6044
Epoch 7/100
2/2 [==============================] - 0s 48ms/step - loss: 2.2023 - accuracy: 0.3098 - val_loss: 1.1197 - val_accuracy: 0.6044
Epoch 8/100
2/2 [==============================] - 0s 35ms/step - loss: 2.2088 - accuracy: 0.3098 - val_loss: 1.1210 - val_accuracy: 0.6044
Epoch 9/100
2/2 [==============================] - 0s 33ms/step - loss: 2.1663 - accuracy: 0.2904 - val_loss: 1.1215 - val_accuracy: 0.6044
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 2.2308 - accuracy: 0.2795 - val_loss: 1.1214 - val_accuracy: 0.6044
Epoch 11/100
2/2 [==============================] - 0s 49ms/step - loss: 2.0966 - accuracy: 0.3171 - val_loss: 1.1203 - val_accuracy: 0.6044
Epoch 12/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1662 - accuracy: 0.3098 - val_loss: 1.1185 - val_accuracy: 0.6044
Epoch 13/100
2/2 [==============================] - 0s 27ms/step - loss: 2.1418 - accuracy: 0.3208 - val_loss: 1.1160 - val_accuracy: 0.6044
Epoch 14/100
2/2 [==============================] - 0s 33ms/step - loss: 2.1367 - accuracy: 0.3171 - val_loss: 1.1125 - val_accuracy: 0.6044
Epoch 15/100
2/2 [==============================] - 0s 34ms/step - loss: 2.1006 - accuracy: 0.3111 - val_loss: 1.1086 - val_accuracy: 0.6154
Epoch 16/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0632 - accuracy: 0.3256 - val_loss: 1.1038 - val_accuracy: 0.6154
Epoch 17/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0375 - accuracy: 0.3232 - val_loss: 1.0983 - val_accuracy: 0.6264
Epoch 18/100
2/2 [==============================] - 0s 50ms/step - loss: 2.0518 - accuracy: 0.3269 - val_loss: 1.0924 - val_accuracy: 0.6264
Epoch 19/100
2/2 [==============================] - 0s 48ms/step - loss: 2.0087 - accuracy: 0.3244 - val_loss: 1.0857 - val_accuracy: 0.6264
Epoch 20/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9685 - accuracy: 0.3196 - val_loss: 1.0782 - val_accuracy: 0.6264
Epoch 21/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9328 - accuracy: 0.3293 - val_loss: 1.0704 - val_accuracy: 0.6374
Epoch 22/100
2/2 [==============================] - 0s 34ms/step - loss: 1.8987 - accuracy: 0.3354 - val_loss: 1.0618 - val_accuracy: 0.6374
Epoch 23/100
2/2 [==============================] - 0s 40ms/step - loss: 1.9135 - accuracy: 0.3572 - val_loss: 1.0526 - val_accuracy: 0.6593
Epoch 24/100
2/2 [==============================] - 0s 42ms/step - loss: 1.8834 - accuracy: 0.3439 - val_loss: 1.0431 - val_accuracy: 0.6593
Epoch 25/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8178 - accuracy: 0.3439 - val_loss: 1.0329 - val_accuracy: 0.6593
Epoch 26/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7882 - accuracy: 0.3487 - val_loss: 1.0224 - val_accuracy: 0.6593
Epoch 27/100
2/2 [==============================] - 0s 33ms/step - loss: 1.7931 - accuracy: 0.3560 - val_loss: 1.0116 - val_accuracy: 0.6593
Epoch 28/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7733 - accuracy: 0.3499 - val_loss: 1.0004 - val_accuracy: 0.6703
Epoch 29/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6977 - accuracy: 0.3730 - val_loss: 0.9890 - val_accuracy: 0.6813
Epoch 30/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6922 - accuracy: 0.3840 - val_loss: 0.9774 - val_accuracy: 0.7033
Epoch 31/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6000 - accuracy: 0.4010 - val_loss: 0.9656 - val_accuracy: 0.7143
Epoch 32/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6384 - accuracy: 0.3730 - val_loss: 0.9535 - val_accuracy: 0.7143
Epoch 33/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5738 - accuracy: 0.4228 - val_loss: 0.9412 - val_accuracy: 0.7253
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5575 - accuracy: 0.3876 - val_loss: 0.9288 - val_accuracy: 0.7473
Epoch 35/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5691 - accuracy: 0.4301 - val_loss: 0.9165 - val_accuracy: 0.7802
Epoch 36/100
2/2 [==============================] - 0s 37ms/step - loss: 1.5097 - accuracy: 0.4083 - val_loss: 0.9043 - val_accuracy: 0.8022
Epoch 37/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5055 - accuracy: 0.4471 - val_loss: 0.8922 - val_accuracy: 0.8022
Epoch 38/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4602 - accuracy: 0.4301 - val_loss: 0.8803 - val_accuracy: 0.8022
Epoch 39/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4169 - accuracy: 0.4581 - val_loss: 0.8686 - val_accuracy: 0.8242
Epoch 40/100
2/2 [==============================] - 0s 49ms/step - loss: 1.4314 - accuracy: 0.4204 - val_loss: 0.8570 - val_accuracy: 0.8462
Epoch 41/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4151 - accuracy: 0.4532 - val_loss: 0.8456 - val_accuracy: 0.8462
Epoch 42/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3570 - accuracy: 0.4678 - val_loss: 0.8342 - val_accuracy: 0.8462
Epoch 43/100
2/2 [==============================] - 0s 29ms/step - loss: 1.3334 - accuracy: 0.4970 - val_loss: 0.8229 - val_accuracy: 0.8571
Epoch 44/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2797 - accuracy: 0.4982 - val_loss: 0.8119 - val_accuracy: 0.8571
Epoch 45/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3009 - accuracy: 0.5055 - val_loss: 0.8014 - val_accuracy: 0.8571
Epoch 46/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2686 - accuracy: 0.5213 - val_loss: 0.7912 - val_accuracy: 0.8462
Epoch 47/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2947 - accuracy: 0.5055 - val_loss: 0.7814 - val_accuracy: 0.8462
Epoch 48/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2619 - accuracy: 0.5298 - val_loss: 0.7720 - val_accuracy: 0.8571
Epoch 49/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2271 - accuracy: 0.5419 - val_loss: 0.7629 - val_accuracy: 0.8791
Epoch 50/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2042 - accuracy: 0.5419 - val_loss: 0.7540 - val_accuracy: 0.8791
Epoch 51/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1520 - accuracy: 0.5735 - val_loss: 0.7454 - val_accuracy: 0.8791
Epoch 52/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1791 - accuracy: 0.5638 - val_loss: 0.7371 - val_accuracy: 0.8901
Epoch 53/100
2/2 [==============================] - 0s 32ms/step - loss: 1.1762 - accuracy: 0.5626 - val_loss: 0.7292 - val_accuracy: 0.8901
Epoch 54/100
2/2 [==============================] - 0s 32ms/step - loss: 1.1132 - accuracy: 0.5978 - val_loss: 0.7216 - val_accuracy: 0.8901
Epoch 55/100
2/2 [==============================] - 0s 32ms/step - loss: 1.1062 - accuracy: 0.5917 - val_loss: 0.7143 - val_accuracy: 0.8901
Epoch 56/100
2/2 [==============================] - 0s 45ms/step - loss: 1.1060 - accuracy: 0.5954 - val_loss: 0.7073 - val_accuracy: 0.8901
Epoch 57/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1232 - accuracy: 0.6124 - val_loss: 0.7007 - val_accuracy: 0.8901
Epoch 58/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1168 - accuracy: 0.6136 - val_loss: 0.6945 - val_accuracy: 0.8901
Epoch 59/100
2/2 [==============================] - 0s 28ms/step - loss: 1.0713 - accuracy: 0.6002 - val_loss: 0.6886 - val_accuracy: 0.8901
Epoch 60/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0496 - accuracy: 0.6343 - val_loss: 0.6830 - val_accuracy: 0.8901
Epoch 61/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0182 - accuracy: 0.6403 - val_loss: 0.6777 - val_accuracy: 0.8901
Epoch 62/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0431 - accuracy: 0.6282 - val_loss: 0.6727 - val_accuracy: 0.8901
Epoch 63/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0192 - accuracy: 0.6598 - val_loss: 0.6679 - val_accuracy: 0.8901
Epoch 64/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9949 - accuracy: 0.6695 - val_loss: 0.6633 - val_accuracy: 0.8901
Epoch 65/100
2/2 [==============================] - 0s 28ms/step - loss: 0.9881 - accuracy: 0.6671 - val_loss: 0.6587 - val_accuracy: 0.8901
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0282 - accuracy: 0.6428 - val_loss: 0.6544 - val_accuracy: 0.8901
Epoch 67/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9342 - accuracy: 0.7023 - val_loss: 0.6502 - val_accuracy: 0.8901
Epoch 68/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9504 - accuracy: 0.6889 - val_loss: 0.6462 - val_accuracy: 0.8901
Epoch 69/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9294 - accuracy: 0.6695 - val_loss: 0.6424 - val_accuracy: 0.8901
Epoch 70/100
2/2 [==============================] - 0s 52ms/step - loss: 0.9496 - accuracy: 0.6780 - val_loss: 0.6387 - val_accuracy: 0.9011
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8912 - accuracy: 0.7023 - val_loss: 0.6352 - val_accuracy: 0.9011
Epoch 72/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9249 - accuracy: 0.7011 - val_loss: 0.6319 - val_accuracy: 0.9011
Epoch 73/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9057 - accuracy: 0.7217 - val_loss: 0.6286 - val_accuracy: 0.9011
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9424 - accuracy: 0.6926 - val_loss: 0.6255 - val_accuracy: 0.9011
Epoch 75/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8856 - accuracy: 0.7132 - val_loss: 0.6225 - val_accuracy: 0.9011
Epoch 76/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9198 - accuracy: 0.7047 - val_loss: 0.6196 - val_accuracy: 0.8901
Epoch 77/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8771 - accuracy: 0.7363 - val_loss: 0.6168 - val_accuracy: 0.8901
Epoch 78/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8944 - accuracy: 0.7254 - val_loss: 0.6141 - val_accuracy: 0.8901
Epoch 79/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8897 - accuracy: 0.7193 - val_loss: 0.6114 - val_accuracy: 0.8901
Epoch 80/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8757 - accuracy: 0.7193 - val_loss: 0.6088 - val_accuracy: 0.8901
Epoch 81/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8807 - accuracy: 0.7169 - val_loss: 0.6062 - val_accuracy: 0.8901
Epoch 82/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8859 - accuracy: 0.7120 - val_loss: 0.6036 - val_accuracy: 0.8901
Epoch 83/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8626 - accuracy: 0.7303 - val_loss: 0.6012 - val_accuracy: 0.8901
Epoch 84/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8320 - accuracy: 0.7351 - val_loss: 0.5988 - val_accuracy: 0.8901
Epoch 85/100
2/2 [==============================] - 0s 54ms/step - loss: 0.8447 - accuracy: 0.7436 - val_loss: 0.5965 - val_accuracy: 0.8901
Epoch 86/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8531 - accuracy: 0.7339 - val_loss: 0.5943 - val_accuracy: 0.8901
Epoch 87/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8318 - accuracy: 0.7303 - val_loss: 0.5919 - val_accuracy: 0.8901
Epoch 88/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8360 - accuracy: 0.7412 - val_loss: 0.5896 - val_accuracy: 0.8901
Epoch 89/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8157 - accuracy: 0.7691 - val_loss: 0.5874 - val_accuracy: 0.8901
Epoch 90/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7829 - accuracy: 0.7594 - val_loss: 0.5851 - val_accuracy: 0.8901
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8255 - accuracy: 0.7521 - val_loss: 0.5829 - val_accuracy: 0.9011
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8065 - accuracy: 0.7570 - val_loss: 0.5806 - val_accuracy: 0.8901
Epoch 93/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7698 - accuracy: 0.7655 - val_loss: 0.5784 - val_accuracy: 0.8901
Epoch 94/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7875 - accuracy: 0.7594 - val_loss: 0.5762 - val_accuracy: 0.8901
Epoch 95/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7912 - accuracy: 0.7485 - val_loss: 0.5740 - val_accuracy: 0.8901
Epoch 96/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7941 - accuracy: 0.7473 - val_loss: 0.5718 - val_accuracy: 0.8901
Epoch 97/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7862 - accuracy: 0.7631 - val_loss: 0.5697 - val_accuracy: 0.8901
Epoch 98/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8114 - accuracy: 0.7546 - val_loss: 0.5675 - val_accuracy: 0.8901
Epoch 99/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7849 - accuracy: 0.7497 - val_loss: 0.5654 - val_accuracy: 0.8901
Epoch 100/100
2/2 [==============================] - 0s 46ms/step - loss: 0.7982 - accuracy: 0.7631 - val_loss: 0.5632 - val_accuracy: 0.8901
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 247ms/step - loss: 1.6852 - accuracy: 0.3584 - val_loss: 1.3981 - val_accuracy: 0.2967
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6602 - accuracy: 0.3524 - val_loss: 1.3975 - val_accuracy: 0.2967
Epoch 3/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6931 - accuracy: 0.3560 - val_loss: 1.3968 - val_accuracy: 0.2967
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6131 - accuracy: 0.3694 - val_loss: 1.3953 - val_accuracy: 0.2967
Epoch 5/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6899 - accuracy: 0.3487 - val_loss: 1.3934 - val_accuracy: 0.3077
Epoch 6/100
2/2 [==============================] - 0s 48ms/step - loss: 1.6519 - accuracy: 0.3864 - val_loss: 1.3911 - val_accuracy: 0.3077
Epoch 7/100
2/2 [==============================] - 0s 48ms/step - loss: 1.6460 - accuracy: 0.3657 - val_loss: 1.3883 - val_accuracy: 0.3077
Epoch 8/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6499 - accuracy: 0.3597 - val_loss: 1.3852 - val_accuracy: 0.3077
Epoch 9/100
2/2 [==============================] - 0s 48ms/step - loss: 1.6632 - accuracy: 0.3572 - val_loss: 1.3815 - val_accuracy: 0.3077
Epoch 10/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5946 - accuracy: 0.3791 - val_loss: 1.3775 - val_accuracy: 0.3187
Epoch 11/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6514 - accuracy: 0.3548 - val_loss: 1.3731 - val_accuracy: 0.3187
Epoch 12/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6352 - accuracy: 0.3645 - val_loss: 1.3683 - val_accuracy: 0.3187
Epoch 13/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6315 - accuracy: 0.3682 - val_loss: 1.3631 - val_accuracy: 0.3407
Epoch 14/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6231 - accuracy: 0.3937 - val_loss: 1.3576 - val_accuracy: 0.3516
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6247 - accuracy: 0.3730 - val_loss: 1.3517 - val_accuracy: 0.3736
Epoch 16/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5751 - accuracy: 0.3791 - val_loss: 1.3455 - val_accuracy: 0.3736
Epoch 17/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5929 - accuracy: 0.3670 - val_loss: 1.3389 - val_accuracy: 0.3736
Epoch 18/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5993 - accuracy: 0.3706 - val_loss: 1.3321 - val_accuracy: 0.3736
Epoch 19/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5380 - accuracy: 0.3815 - val_loss: 1.3250 - val_accuracy: 0.3736
Epoch 20/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5504 - accuracy: 0.3913 - val_loss: 1.3177 - val_accuracy: 0.3736
Epoch 21/100
2/2 [==============================] - 0s 30ms/step - loss: 1.5241 - accuracy: 0.3791 - val_loss: 1.3102 - val_accuracy: 0.3846
Epoch 22/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5418 - accuracy: 0.3913 - val_loss: 1.3023 - val_accuracy: 0.3846
Epoch 23/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5017 - accuracy: 0.3840 - val_loss: 1.2943 - val_accuracy: 0.3846
Epoch 24/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5051 - accuracy: 0.4070 - val_loss: 1.2861 - val_accuracy: 0.3846
Epoch 25/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4972 - accuracy: 0.4046 - val_loss: 1.2775 - val_accuracy: 0.3846
Epoch 26/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4482 - accuracy: 0.4046 - val_loss: 1.2688 - val_accuracy: 0.3846
Epoch 27/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4385 - accuracy: 0.4265 - val_loss: 1.2600 - val_accuracy: 0.4066
Epoch 28/100
2/2 [==============================] - 0s 51ms/step - loss: 1.4685 - accuracy: 0.4119 - val_loss: 1.2510 - val_accuracy: 0.4066
Epoch 29/100
2/2 [==============================] - 0s 30ms/step - loss: 1.4170 - accuracy: 0.4070 - val_loss: 1.2418 - val_accuracy: 0.4176
Epoch 30/100
2/2 [==============================] - 0s 31ms/step - loss: 1.4296 - accuracy: 0.4423 - val_loss: 1.2323 - val_accuracy: 0.4176
Epoch 31/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3994 - accuracy: 0.4399 - val_loss: 1.2229 - val_accuracy: 0.4176
Epoch 32/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3906 - accuracy: 0.4399 - val_loss: 1.2133 - val_accuracy: 0.4396
Epoch 33/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3921 - accuracy: 0.4508 - val_loss: 1.2036 - val_accuracy: 0.4396
Epoch 34/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3560 - accuracy: 0.4447 - val_loss: 1.1939 - val_accuracy: 0.4505
Epoch 35/100
2/2 [==============================] - 0s 64ms/step - loss: 1.3758 - accuracy: 0.4617 - val_loss: 1.1839 - val_accuracy: 0.4615
Epoch 36/100
2/2 [==============================] - 0s 28ms/step - loss: 1.3035 - accuracy: 0.4739 - val_loss: 1.1740 - val_accuracy: 0.4615
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3346 - accuracy: 0.4459 - val_loss: 1.1640 - val_accuracy: 0.4615
Epoch 38/100
2/2 [==============================] - 0s 45ms/step - loss: 1.3515 - accuracy: 0.4617 - val_loss: 1.1541 - val_accuracy: 0.5055
Epoch 39/100
2/2 [==============================] - 0s 46ms/step - loss: 1.2782 - accuracy: 0.4812 - val_loss: 1.1440 - val_accuracy: 0.5165
Epoch 40/100
2/2 [==============================] - 0s 54ms/step - loss: 1.2482 - accuracy: 0.4872 - val_loss: 1.1339 - val_accuracy: 0.5165
Epoch 41/100
2/2 [==============================] - 0s 23ms/step - loss: 1.2588 - accuracy: 0.4957 - val_loss: 1.1239 - val_accuracy: 0.5275
Epoch 42/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2441 - accuracy: 0.5006 - val_loss: 1.1139 - val_accuracy: 0.5495
Epoch 43/100
2/2 [==============================] - 0s 29ms/step - loss: 1.2282 - accuracy: 0.5103 - val_loss: 1.1039 - val_accuracy: 0.5495
Epoch 44/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2027 - accuracy: 0.5298 - val_loss: 1.0940 - val_accuracy: 0.5604
Epoch 45/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2077 - accuracy: 0.5225 - val_loss: 1.0840 - val_accuracy: 0.5604
Epoch 46/100
2/2 [==============================] - 0s 53ms/step - loss: 1.2146 - accuracy: 0.5200 - val_loss: 1.0740 - val_accuracy: 0.5604
Epoch 47/100
2/2 [==============================] - 0s 27ms/step - loss: 1.1955 - accuracy: 0.5213 - val_loss: 1.0642 - val_accuracy: 0.5714
Epoch 48/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1349 - accuracy: 0.5516 - val_loss: 1.0544 - val_accuracy: 0.5934
Epoch 49/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1299 - accuracy: 0.5529 - val_loss: 1.0447 - val_accuracy: 0.5934
Epoch 50/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1402 - accuracy: 0.5419 - val_loss: 1.0351 - val_accuracy: 0.6154
Epoch 51/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1318 - accuracy: 0.5565 - val_loss: 1.0256 - val_accuracy: 0.6264
Epoch 52/100
2/2 [==============================] - 0s 32ms/step - loss: 1.1115 - accuracy: 0.5905 - val_loss: 1.0163 - val_accuracy: 0.6264
Epoch 53/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0699 - accuracy: 0.5723 - val_loss: 1.0070 - val_accuracy: 0.6264
Epoch 54/100
2/2 [==============================] - 0s 44ms/step - loss: 1.0572 - accuracy: 0.6063 - val_loss: 0.9978 - val_accuracy: 0.6374
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0565 - accuracy: 0.5978 - val_loss: 0.9887 - val_accuracy: 0.6593
Epoch 56/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0336 - accuracy: 0.6015 - val_loss: 0.9797 - val_accuracy: 0.6813
Epoch 57/100
2/2 [==============================] - 0s 28ms/step - loss: 1.0448 - accuracy: 0.6015 - val_loss: 0.9708 - val_accuracy: 0.6923
Epoch 58/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0162 - accuracy: 0.6197 - val_loss: 0.9621 - val_accuracy: 0.6923
Epoch 59/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0161 - accuracy: 0.6476 - val_loss: 0.9534 - val_accuracy: 0.7033
Epoch 60/100
2/2 [==============================] - 0s 49ms/step - loss: 0.9618 - accuracy: 0.6634 - val_loss: 0.9448 - val_accuracy: 0.7143
Epoch 61/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9810 - accuracy: 0.6574 - val_loss: 0.9364 - val_accuracy: 0.7363
Epoch 62/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9875 - accuracy: 0.6416 - val_loss: 0.9281 - val_accuracy: 0.7363
Epoch 63/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9920 - accuracy: 0.6622 - val_loss: 0.9200 - val_accuracy: 0.7363
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9397 - accuracy: 0.6780 - val_loss: 0.9120 - val_accuracy: 0.7363
Epoch 65/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9559 - accuracy: 0.6768 - val_loss: 0.9041 - val_accuracy: 0.7363
Epoch 66/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9589 - accuracy: 0.6731 - val_loss: 0.8964 - val_accuracy: 0.7473
Epoch 67/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9286 - accuracy: 0.6950 - val_loss: 0.8887 - val_accuracy: 0.7473
Epoch 68/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9385 - accuracy: 0.6780 - val_loss: 0.8812 - val_accuracy: 0.7473
Epoch 69/100
2/2 [==============================] - 0s 46ms/step - loss: 0.9283 - accuracy: 0.6938 - val_loss: 0.8739 - val_accuracy: 0.7473
Epoch 70/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9090 - accuracy: 0.6841 - val_loss: 0.8666 - val_accuracy: 0.7473
Epoch 71/100
2/2 [==============================] - 0s 29ms/step - loss: 0.9354 - accuracy: 0.6877 - val_loss: 0.8597 - val_accuracy: 0.7582
Epoch 72/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8804 - accuracy: 0.6974 - val_loss: 0.8526 - val_accuracy: 0.7582
Epoch 73/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8770 - accuracy: 0.7120 - val_loss: 0.8458 - val_accuracy: 0.7802
Epoch 74/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8918 - accuracy: 0.7084 - val_loss: 0.8391 - val_accuracy: 0.7802
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8571 - accuracy: 0.7303 - val_loss: 0.8324 - val_accuracy: 0.7802
Epoch 76/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8518 - accuracy: 0.7339 - val_loss: 0.8260 - val_accuracy: 0.7802
Epoch 77/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8440 - accuracy: 0.7242 - val_loss: 0.8197 - val_accuracy: 0.7802
Epoch 78/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8435 - accuracy: 0.7315 - val_loss: 0.8135 - val_accuracy: 0.7802
Epoch 79/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8395 - accuracy: 0.7400 - val_loss: 0.8075 - val_accuracy: 0.7802
Epoch 80/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8517 - accuracy: 0.7339 - val_loss: 0.8016 - val_accuracy: 0.7802
Epoch 81/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8390 - accuracy: 0.7436 - val_loss: 0.7958 - val_accuracy: 0.7912
Epoch 82/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7850 - accuracy: 0.7643 - val_loss: 0.7901 - val_accuracy: 0.7912
Epoch 83/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8094 - accuracy: 0.7533 - val_loss: 0.7846 - val_accuracy: 0.8022
Epoch 84/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8294 - accuracy: 0.7594 - val_loss: 0.7790 - val_accuracy: 0.8022
Epoch 85/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7878 - accuracy: 0.7861 - val_loss: 0.7737 - val_accuracy: 0.8022
Epoch 86/100
2/2 [==============================] - 0s 52ms/step - loss: 0.7723 - accuracy: 0.7606 - val_loss: 0.7684 - val_accuracy: 0.8022
Epoch 87/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7900 - accuracy: 0.7716 - val_loss: 0.7633 - val_accuracy: 0.8022
Epoch 88/100
2/2 [==============================] - 0s 45ms/step - loss: 0.7480 - accuracy: 0.7837 - val_loss: 0.7583 - val_accuracy: 0.8132
Epoch 89/100
2/2 [==============================] - 0s 30ms/step - loss: 0.7800 - accuracy: 0.7861 - val_loss: 0.7533 - val_accuracy: 0.8132
Epoch 90/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7719 - accuracy: 0.7728 - val_loss: 0.7486 - val_accuracy: 0.8022
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7455 - accuracy: 0.7789 - val_loss: 0.7439 - val_accuracy: 0.8022
Epoch 92/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7631 - accuracy: 0.7886 - val_loss: 0.7392 - val_accuracy: 0.8022
Epoch 93/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7294 - accuracy: 0.8068 - val_loss: 0.7348 - val_accuracy: 0.8022
Epoch 94/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7535 - accuracy: 0.7801 - val_loss: 0.7304 - val_accuracy: 0.7912
Epoch 95/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7368 - accuracy: 0.7947 - val_loss: 0.7261 - val_accuracy: 0.7912
Epoch 96/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7288 - accuracy: 0.8007 - val_loss: 0.7220 - val_accuracy: 0.7912
Epoch 97/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7084 - accuracy: 0.8056 - val_loss: 0.7180 - val_accuracy: 0.7912
Epoch 98/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7102 - accuracy: 0.7971 - val_loss: 0.7140 - val_accuracy: 0.7802
Epoch 99/100
2/2 [==============================] - 0s 49ms/step - loss: 0.7181 - accuracy: 0.7922 - val_loss: 0.7101 - val_accuracy: 0.7912
Epoch 100/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7014 - accuracy: 0.8080 - val_loss: 0.7062 - val_accuracy: 0.7912
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 249ms/step - loss: 2.1760 - accuracy: 0.3366 - val_loss: 2.1115 - val_accuracy: 0.0549
Epoch 2/100
2/2 [==============================] - 0s 54ms/step - loss: 2.1544 - accuracy: 0.3597 - val_loss: 2.1046 - val_accuracy: 0.0659
Epoch 3/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2286 - accuracy: 0.3354 - val_loss: 2.0970 - val_accuracy: 0.0659
Epoch 4/100
2/2 [==============================] - 0s 52ms/step - loss: 2.1932 - accuracy: 0.3463 - val_loss: 2.0884 - val_accuracy: 0.0769
Epoch 5/100
2/2 [==============================] - 0s 35ms/step - loss: 2.1661 - accuracy: 0.3354 - val_loss: 2.0790 - val_accuracy: 0.0769
Epoch 6/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1267 - accuracy: 0.3718 - val_loss: 2.0684 - val_accuracy: 0.0769
Epoch 7/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0315 - accuracy: 0.3621 - val_loss: 2.0569 - val_accuracy: 0.0769
Epoch 8/100
2/2 [==============================] - 0s 52ms/step - loss: 2.0765 - accuracy: 0.3706 - val_loss: 2.0449 - val_accuracy: 0.0769
Epoch 9/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1431 - accuracy: 0.3463 - val_loss: 2.0319 - val_accuracy: 0.0769
Epoch 10/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1275 - accuracy: 0.3682 - val_loss: 2.0180 - val_accuracy: 0.0769
Epoch 11/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1419 - accuracy: 0.3609 - val_loss: 2.0033 - val_accuracy: 0.0769
Epoch 12/100
2/2 [==============================] - 0s 55ms/step - loss: 2.1458 - accuracy: 0.3463 - val_loss: 1.9877 - val_accuracy: 0.0769
Epoch 13/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0808 - accuracy: 0.3220 - val_loss: 1.9714 - val_accuracy: 0.0769
Epoch 14/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0175 - accuracy: 0.3560 - val_loss: 1.9551 - val_accuracy: 0.0879
Epoch 15/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0404 - accuracy: 0.3451 - val_loss: 1.9377 - val_accuracy: 0.0879
Epoch 16/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0141 - accuracy: 0.3548 - val_loss: 1.9197 - val_accuracy: 0.1099
Epoch 17/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0464 - accuracy: 0.3633 - val_loss: 1.9013 - val_accuracy: 0.1099
Epoch 18/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0168 - accuracy: 0.3791 - val_loss: 1.8823 - val_accuracy: 0.1209
Epoch 19/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0162 - accuracy: 0.3645 - val_loss: 1.8633 - val_accuracy: 0.1209
Epoch 20/100
2/2 [==============================] - 0s 51ms/step - loss: 1.9865 - accuracy: 0.3645 - val_loss: 1.8440 - val_accuracy: 0.1209
Epoch 21/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9550 - accuracy: 0.3730 - val_loss: 1.8240 - val_accuracy: 0.1319
Epoch 22/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9149 - accuracy: 0.3584 - val_loss: 1.8035 - val_accuracy: 0.1319
Epoch 23/100
2/2 [==============================] - 0s 30ms/step - loss: 1.8977 - accuracy: 0.3876 - val_loss: 1.7829 - val_accuracy: 0.1538
Epoch 24/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9002 - accuracy: 0.3706 - val_loss: 1.7621 - val_accuracy: 0.1538
Epoch 25/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8744 - accuracy: 0.3670 - val_loss: 1.7411 - val_accuracy: 0.1648
Epoch 26/100
2/2 [==============================] - 0s 31ms/step - loss: 1.8543 - accuracy: 0.3876 - val_loss: 1.7199 - val_accuracy: 0.1648
Epoch 27/100
2/2 [==============================] - 0s 31ms/step - loss: 1.8556 - accuracy: 0.3779 - val_loss: 1.6985 - val_accuracy: 0.1868
Epoch 28/100
2/2 [==============================] - 0s 31ms/step - loss: 1.8175 - accuracy: 0.3998 - val_loss: 1.6766 - val_accuracy: 0.2088
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7865 - accuracy: 0.4119 - val_loss: 1.6549 - val_accuracy: 0.2308
Epoch 30/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7718 - accuracy: 0.3973 - val_loss: 1.6331 - val_accuracy: 0.2308
Epoch 31/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7192 - accuracy: 0.4143 - val_loss: 1.6113 - val_accuracy: 0.2308
Epoch 32/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7385 - accuracy: 0.4180 - val_loss: 1.5894 - val_accuracy: 0.2308
Epoch 33/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7055 - accuracy: 0.4119 - val_loss: 1.5676 - val_accuracy: 0.2527
Epoch 34/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6607 - accuracy: 0.4399 - val_loss: 1.5461 - val_accuracy: 0.2637
Epoch 35/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6693 - accuracy: 0.4362 - val_loss: 1.5244 - val_accuracy: 0.2747
Epoch 36/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6987 - accuracy: 0.4216 - val_loss: 1.5031 - val_accuracy: 0.2967
Epoch 37/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5980 - accuracy: 0.4374 - val_loss: 1.4819 - val_accuracy: 0.3187
Epoch 38/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5679 - accuracy: 0.4581 - val_loss: 1.4608 - val_accuracy: 0.3516
Epoch 39/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5991 - accuracy: 0.4399 - val_loss: 1.4400 - val_accuracy: 0.3516
Epoch 40/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5380 - accuracy: 0.4411 - val_loss: 1.4193 - val_accuracy: 0.3736
Epoch 41/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5188 - accuracy: 0.4642 - val_loss: 1.3988 - val_accuracy: 0.3846
Epoch 42/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4613 - accuracy: 0.4933 - val_loss: 1.3786 - val_accuracy: 0.4066
Epoch 43/100
2/2 [==============================] - 0s 52ms/step - loss: 1.5243 - accuracy: 0.4544 - val_loss: 1.3586 - val_accuracy: 0.4505
Epoch 44/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4520 - accuracy: 0.4763 - val_loss: 1.3386 - val_accuracy: 0.4725
Epoch 45/100
2/2 [==============================] - 0s 31ms/step - loss: 1.4581 - accuracy: 0.4982 - val_loss: 1.3191 - val_accuracy: 0.5055
Epoch 46/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4261 - accuracy: 0.4836 - val_loss: 1.2995 - val_accuracy: 0.5165
Epoch 47/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3696 - accuracy: 0.5018 - val_loss: 1.2805 - val_accuracy: 0.5165
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3755 - accuracy: 0.5128 - val_loss: 1.2615 - val_accuracy: 0.5165
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3879 - accuracy: 0.5152 - val_loss: 1.2428 - val_accuracy: 0.5275
Epoch 50/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3393 - accuracy: 0.5480 - val_loss: 1.2244 - val_accuracy: 0.5714
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3163 - accuracy: 0.5322 - val_loss: 1.2064 - val_accuracy: 0.5714
Epoch 52/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2646 - accuracy: 0.5407 - val_loss: 1.1887 - val_accuracy: 0.5824
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2876 - accuracy: 0.5334 - val_loss: 1.1713 - val_accuracy: 0.6044
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3048 - accuracy: 0.5334 - val_loss: 1.1543 - val_accuracy: 0.6044
Epoch 55/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2711 - accuracy: 0.5298 - val_loss: 1.1376 - val_accuracy: 0.6264
Epoch 56/100
2/2 [==============================] - 0s 24ms/step - loss: 1.2431 - accuracy: 0.5601 - val_loss: 1.1213 - val_accuracy: 0.6484
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2487 - accuracy: 0.5784 - val_loss: 1.1053 - val_accuracy: 0.6484
Epoch 58/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2066 - accuracy: 0.5699 - val_loss: 1.0897 - val_accuracy: 0.6484
Epoch 59/100
2/2 [==============================] - 0s 44ms/step - loss: 1.1569 - accuracy: 0.5808 - val_loss: 1.0742 - val_accuracy: 0.6484
Epoch 60/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1636 - accuracy: 0.5832 - val_loss: 1.0592 - val_accuracy: 0.6484
Epoch 61/100
2/2 [==============================] - 0s 35ms/step - loss: 1.1057 - accuracy: 0.6330 - val_loss: 1.0444 - val_accuracy: 0.6593
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1590 - accuracy: 0.6100 - val_loss: 1.0300 - val_accuracy: 0.6593
Epoch 63/100
2/2 [==============================] - 0s 35ms/step - loss: 1.1442 - accuracy: 0.5893 - val_loss: 1.0158 - val_accuracy: 0.6593
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1129 - accuracy: 0.6282 - val_loss: 1.0020 - val_accuracy: 0.6593
Epoch 65/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0731 - accuracy: 0.6306 - val_loss: 0.9886 - val_accuracy: 0.7033
Epoch 66/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0683 - accuracy: 0.6391 - val_loss: 0.9756 - val_accuracy: 0.7033
Epoch 67/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0436 - accuracy: 0.6428 - val_loss: 0.9630 - val_accuracy: 0.7143
Epoch 68/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1196 - accuracy: 0.6087 - val_loss: 0.9506 - val_accuracy: 0.7253
Epoch 69/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0169 - accuracy: 0.6525 - val_loss: 0.9385 - val_accuracy: 0.7253
Epoch 70/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0198 - accuracy: 0.6586 - val_loss: 0.9269 - val_accuracy: 0.7473
Epoch 71/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0173 - accuracy: 0.6646 - val_loss: 0.9155 - val_accuracy: 0.7473
Epoch 72/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9989 - accuracy: 0.6974 - val_loss: 0.9043 - val_accuracy: 0.7473
Epoch 73/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9878 - accuracy: 0.6756 - val_loss: 0.8935 - val_accuracy: 0.7473
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0028 - accuracy: 0.6622 - val_loss: 0.8830 - val_accuracy: 0.7473
Epoch 75/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9987 - accuracy: 0.6804 - val_loss: 0.8730 - val_accuracy: 0.7473
Epoch 76/100
2/2 [==============================] - 0s 44ms/step - loss: 0.9706 - accuracy: 0.6841 - val_loss: 0.8630 - val_accuracy: 0.7582
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9399 - accuracy: 0.7047 - val_loss: 0.8534 - val_accuracy: 0.7582
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9293 - accuracy: 0.7108 - val_loss: 0.8439 - val_accuracy: 0.7692
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9371 - accuracy: 0.6999 - val_loss: 0.8348 - val_accuracy: 0.7802
Epoch 80/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9002 - accuracy: 0.7132 - val_loss: 0.8259 - val_accuracy: 0.7802
Epoch 81/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9134 - accuracy: 0.6962 - val_loss: 0.8174 - val_accuracy: 0.7802
Epoch 82/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9154 - accuracy: 0.6877 - val_loss: 0.8091 - val_accuracy: 0.7912
Epoch 83/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8780 - accuracy: 0.7193 - val_loss: 0.8010 - val_accuracy: 0.7912
Epoch 84/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9247 - accuracy: 0.6829 - val_loss: 0.7931 - val_accuracy: 0.8022
Epoch 85/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8821 - accuracy: 0.7290 - val_loss: 0.7854 - val_accuracy: 0.8352
Epoch 86/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8492 - accuracy: 0.7424 - val_loss: 0.7780 - val_accuracy: 0.8352
Epoch 87/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8540 - accuracy: 0.7339 - val_loss: 0.7707 - val_accuracy: 0.8352
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8675 - accuracy: 0.7388 - val_loss: 0.7637 - val_accuracy: 0.8352
Epoch 89/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8511 - accuracy: 0.7400 - val_loss: 0.7567 - val_accuracy: 0.8352
Epoch 90/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8151 - accuracy: 0.7521 - val_loss: 0.7500 - val_accuracy: 0.8352
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7998 - accuracy: 0.7764 - val_loss: 0.7435 - val_accuracy: 0.8352
Epoch 92/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8047 - accuracy: 0.7618 - val_loss: 0.7372 - val_accuracy: 0.8352
Epoch 93/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8300 - accuracy: 0.7533 - val_loss: 0.7312 - val_accuracy: 0.8352
Epoch 94/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8302 - accuracy: 0.7485 - val_loss: 0.7254 - val_accuracy: 0.8352
Epoch 95/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8203 - accuracy: 0.7606 - val_loss: 0.7196 - val_accuracy: 0.8462
Epoch 96/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8123 - accuracy: 0.7704 - val_loss: 0.7140 - val_accuracy: 0.8462
Epoch 97/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7946 - accuracy: 0.7776 - val_loss: 0.7087 - val_accuracy: 0.8462
Epoch 98/100
2/2 [==============================] - 0s 24ms/step - loss: 0.7897 - accuracy: 0.7679 - val_loss: 0.7033 - val_accuracy: 0.8462
Epoch 99/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7821 - accuracy: 0.7728 - val_loss: 0.6982 - val_accuracy: 0.8462
Epoch 100/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7724 - accuracy: 0.7837 - val_loss: 0.6932 - val_accuracy: 0.8462
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 512
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
2/2 [==============================] - 1s 250ms/step - loss: 1.7702 - accuracy: 0.3062 - val_loss: 1.3022 - val_accuracy: 0.3846
Epoch 2/100
2/2 [==============================] - 0s 46ms/step - loss: 1.7390 - accuracy: 0.3329 - val_loss: 1.3045 - val_accuracy: 0.3846
Epoch 3/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7226 - accuracy: 0.3293 - val_loss: 1.3061 - val_accuracy: 0.3846
Epoch 4/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7421 - accuracy: 0.3305 - val_loss: 1.3074 - val_accuracy: 0.3846
Epoch 5/100
2/2 [==============================] - 0s 34ms/step - loss: 1.7184 - accuracy: 0.3123 - val_loss: 1.3082 - val_accuracy: 0.3846
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7143 - accuracy: 0.3281 - val_loss: 1.3087 - val_accuracy: 0.3846
Epoch 7/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7291 - accuracy: 0.3463 - val_loss: 1.3088 - val_accuracy: 0.3846
Epoch 8/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7009 - accuracy: 0.3366 - val_loss: 1.3086 - val_accuracy: 0.3846
Epoch 9/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7377 - accuracy: 0.3147 - val_loss: 1.3079 - val_accuracy: 0.3956
Epoch 10/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7325 - accuracy: 0.3244 - val_loss: 1.3067 - val_accuracy: 0.3956
Epoch 11/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7058 - accuracy: 0.3281 - val_loss: 1.3053 - val_accuracy: 0.3956
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7116 - accuracy: 0.3256 - val_loss: 1.3035 - val_accuracy: 0.3956
Epoch 13/100
2/2 [==============================] - 0s 46ms/step - loss: 1.6662 - accuracy: 0.3220 - val_loss: 1.3016 - val_accuracy: 0.3956
Epoch 14/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7150 - accuracy: 0.3208 - val_loss: 1.2989 - val_accuracy: 0.3956
Epoch 15/100
2/2 [==============================] - 0s 32ms/step - loss: 1.6694 - accuracy: 0.3256 - val_loss: 1.2962 - val_accuracy: 0.3956
Epoch 16/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6957 - accuracy: 0.3463 - val_loss: 1.2931 - val_accuracy: 0.3956
Epoch 17/100
2/2 [==============================] - 0s 32ms/step - loss: 1.6807 - accuracy: 0.3390 - val_loss: 1.2899 - val_accuracy: 0.3956
Epoch 18/100
2/2 [==============================] - 0s 32ms/step - loss: 1.6504 - accuracy: 0.3524 - val_loss: 1.2864 - val_accuracy: 0.3956
Epoch 19/100
2/2 [==============================] - 0s 53ms/step - loss: 1.6287 - accuracy: 0.3463 - val_loss: 1.2823 - val_accuracy: 0.4066
Epoch 20/100
2/2 [==============================] - 0s 30ms/step - loss: 1.6889 - accuracy: 0.3390 - val_loss: 1.2783 - val_accuracy: 0.3956
Epoch 21/100
2/2 [==============================] - 0s 44ms/step - loss: 1.6622 - accuracy: 0.3281 - val_loss: 1.2739 - val_accuracy: 0.3956
Epoch 22/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6257 - accuracy: 0.3499 - val_loss: 1.2693 - val_accuracy: 0.4066
Epoch 23/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5841 - accuracy: 0.3524 - val_loss: 1.2643 - val_accuracy: 0.4176
Epoch 24/100
2/2 [==============================] - 0s 33ms/step - loss: 1.5834 - accuracy: 0.3499 - val_loss: 1.2589 - val_accuracy: 0.4396
Epoch 25/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5743 - accuracy: 0.3730 - val_loss: 1.2535 - val_accuracy: 0.4396
Epoch 26/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5774 - accuracy: 0.3341 - val_loss: 1.2477 - val_accuracy: 0.4396
Epoch 27/100
2/2 [==============================] - 0s 46ms/step - loss: 1.5758 - accuracy: 0.3876 - val_loss: 1.2418 - val_accuracy: 0.4396
Epoch 28/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5620 - accuracy: 0.3633 - val_loss: 1.2355 - val_accuracy: 0.4725
Epoch 29/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4890 - accuracy: 0.4022 - val_loss: 1.2291 - val_accuracy: 0.4725
Epoch 30/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5290 - accuracy: 0.3694 - val_loss: 1.2227 - val_accuracy: 0.4835
Epoch 31/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5140 - accuracy: 0.3791 - val_loss: 1.2162 - val_accuracy: 0.4945
Epoch 32/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4575 - accuracy: 0.4119 - val_loss: 1.2094 - val_accuracy: 0.5055
Epoch 33/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4621 - accuracy: 0.3888 - val_loss: 1.2026 - val_accuracy: 0.5165
Epoch 34/100
2/2 [==============================] - 0s 29ms/step - loss: 1.4773 - accuracy: 0.4070 - val_loss: 1.1956 - val_accuracy: 0.5495
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4412 - accuracy: 0.4143 - val_loss: 1.1884 - val_accuracy: 0.5495
Epoch 36/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4476 - accuracy: 0.4143 - val_loss: 1.1811 - val_accuracy: 0.5495
Epoch 37/100
2/2 [==============================] - 0s 31ms/step - loss: 1.4261 - accuracy: 0.4204 - val_loss: 1.1737 - val_accuracy: 0.5604
Epoch 38/100
2/2 [==============================] - 0s 31ms/step - loss: 1.4258 - accuracy: 0.4459 - val_loss: 1.1663 - val_accuracy: 0.5604
Epoch 39/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4151 - accuracy: 0.4277 - val_loss: 1.1586 - val_accuracy: 0.5604
Epoch 40/100
2/2 [==============================] - 0s 36ms/step - loss: 1.3901 - accuracy: 0.4289 - val_loss: 1.1511 - val_accuracy: 0.5714
Epoch 41/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3831 - accuracy: 0.4459 - val_loss: 1.1434 - val_accuracy: 0.5824
Epoch 42/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3718 - accuracy: 0.4386 - val_loss: 1.1357 - val_accuracy: 0.5824
Epoch 43/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3823 - accuracy: 0.4241 - val_loss: 1.1281 - val_accuracy: 0.5824
Epoch 44/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3419 - accuracy: 0.4593 - val_loss: 1.1205 - val_accuracy: 0.6154
Epoch 45/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3174 - accuracy: 0.4557 - val_loss: 1.1128 - val_accuracy: 0.6154
Epoch 46/100
2/2 [==============================] - 0s 43ms/step - loss: 1.3430 - accuracy: 0.4690 - val_loss: 1.1051 - val_accuracy: 0.6264
Epoch 47/100
2/2 [==============================] - 0s 43ms/step - loss: 1.2943 - accuracy: 0.4642 - val_loss: 1.0975 - val_accuracy: 0.6593
Epoch 48/100
2/2 [==============================] - 0s 48ms/step - loss: 1.2850 - accuracy: 0.4751 - val_loss: 1.0898 - val_accuracy: 0.6703
Epoch 49/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2575 - accuracy: 0.5091 - val_loss: 1.0820 - val_accuracy: 0.6813
Epoch 50/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2497 - accuracy: 0.4860 - val_loss: 1.0743 - val_accuracy: 0.6923
Epoch 51/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2596 - accuracy: 0.5055 - val_loss: 1.0667 - val_accuracy: 0.6923
Epoch 52/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2134 - accuracy: 0.5225 - val_loss: 1.0591 - val_accuracy: 0.6923
Epoch 53/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2504 - accuracy: 0.5091 - val_loss: 1.0516 - val_accuracy: 0.6923
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2262 - accuracy: 0.5164 - val_loss: 1.0439 - val_accuracy: 0.6923
Epoch 55/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1993 - accuracy: 0.5152 - val_loss: 1.0364 - val_accuracy: 0.7033
Epoch 56/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1881 - accuracy: 0.5322 - val_loss: 1.0288 - val_accuracy: 0.7143
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1510 - accuracy: 0.5577 - val_loss: 1.0214 - val_accuracy: 0.7253
Epoch 58/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1742 - accuracy: 0.5529 - val_loss: 1.0140 - val_accuracy: 0.7363
Epoch 59/100
2/2 [==============================] - 0s 42ms/step - loss: 1.1460 - accuracy: 0.5735 - val_loss: 1.0067 - val_accuracy: 0.7363
Epoch 60/100
2/2 [==============================] - 0s 43ms/step - loss: 1.1238 - accuracy: 0.5589 - val_loss: 0.9994 - val_accuracy: 0.7363
Epoch 61/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1311 - accuracy: 0.5844 - val_loss: 0.9922 - val_accuracy: 0.7473
Epoch 62/100
2/2 [==============================] - 0s 49ms/step - loss: 1.1158 - accuracy: 0.5711 - val_loss: 0.9851 - val_accuracy: 0.7473
Epoch 63/100
2/2 [==============================] - 0s 44ms/step - loss: 1.1169 - accuracy: 0.5881 - val_loss: 0.9781 - val_accuracy: 0.7473
Epoch 64/100
2/2 [==============================] - 0s 45ms/step - loss: 1.1103 - accuracy: 0.5711 - val_loss: 0.9712 - val_accuracy: 0.7582
Epoch 65/100
2/2 [==============================] - 0s 30ms/step - loss: 1.0677 - accuracy: 0.6112 - val_loss: 0.9643 - val_accuracy: 0.7692
Epoch 66/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0715 - accuracy: 0.6197 - val_loss: 0.9576 - val_accuracy: 0.7802
Epoch 67/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0446 - accuracy: 0.6221 - val_loss: 0.9510 - val_accuracy: 0.7802
Epoch 68/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0701 - accuracy: 0.6233 - val_loss: 0.9445 - val_accuracy: 0.7802
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0329 - accuracy: 0.6537 - val_loss: 0.9380 - val_accuracy: 0.7802
Epoch 70/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0208 - accuracy: 0.6282 - val_loss: 0.9316 - val_accuracy: 0.7802
Epoch 71/100
2/2 [==============================] - 0s 44ms/step - loss: 1.0214 - accuracy: 0.6403 - val_loss: 0.9253 - val_accuracy: 0.7802
Epoch 72/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0083 - accuracy: 0.6598 - val_loss: 0.9191 - val_accuracy: 0.7912
Epoch 73/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0205 - accuracy: 0.6537 - val_loss: 0.9130 - val_accuracy: 0.7912
Epoch 74/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9888 - accuracy: 0.6792 - val_loss: 0.9070 - val_accuracy: 0.7912
Epoch 75/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9903 - accuracy: 0.6683 - val_loss: 0.9011 - val_accuracy: 0.8022
Epoch 76/100
2/2 [==============================] - 0s 51ms/step - loss: 0.9894 - accuracy: 0.6671 - val_loss: 0.8953 - val_accuracy: 0.8022
Epoch 77/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9600 - accuracy: 0.6950 - val_loss: 0.8897 - val_accuracy: 0.8022
Epoch 78/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9786 - accuracy: 0.6695 - val_loss: 0.8842 - val_accuracy: 0.8022
Epoch 79/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9280 - accuracy: 0.7157 - val_loss: 0.8787 - val_accuracy: 0.8132
Epoch 80/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9384 - accuracy: 0.7060 - val_loss: 0.8735 - val_accuracy: 0.8132
Epoch 81/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9260 - accuracy: 0.7145 - val_loss: 0.8682 - val_accuracy: 0.8132
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9309 - accuracy: 0.7181 - val_loss: 0.8631 - val_accuracy: 0.8132
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9110 - accuracy: 0.7363 - val_loss: 0.8580 - val_accuracy: 0.8132
Epoch 84/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9109 - accuracy: 0.7242 - val_loss: 0.8531 - val_accuracy: 0.8132
Epoch 85/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9047 - accuracy: 0.7266 - val_loss: 0.8482 - val_accuracy: 0.8132
Epoch 86/100
2/2 [==============================] - 0s 28ms/step - loss: 0.9023 - accuracy: 0.7400 - val_loss: 0.8436 - val_accuracy: 0.8132
Epoch 87/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8933 - accuracy: 0.7339 - val_loss: 0.8389 - val_accuracy: 0.8132
Epoch 88/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8680 - accuracy: 0.7509 - val_loss: 0.8343 - val_accuracy: 0.8132
Epoch 89/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8600 - accuracy: 0.7461 - val_loss: 0.8298 - val_accuracy: 0.8242
Epoch 90/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8500 - accuracy: 0.7327 - val_loss: 0.8255 - val_accuracy: 0.8242
Epoch 91/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8648 - accuracy: 0.7582 - val_loss: 0.8212 - val_accuracy: 0.8242
Epoch 92/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8792 - accuracy: 0.7351 - val_loss: 0.8170 - val_accuracy: 0.8242
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8586 - accuracy: 0.7594 - val_loss: 0.8128 - val_accuracy: 0.8242
Epoch 94/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8317 - accuracy: 0.7728 - val_loss: 0.8089 - val_accuracy: 0.8242
Epoch 95/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8351 - accuracy: 0.7655 - val_loss: 0.8049 - val_accuracy: 0.8132
Epoch 96/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8191 - accuracy: 0.7959 - val_loss: 0.8011 - val_accuracy: 0.8132
Epoch 97/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8191 - accuracy: 0.7861 - val_loss: 0.7973 - val_accuracy: 0.8132
Epoch 98/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7908 - accuracy: 0.7934 - val_loss: 0.7936 - val_accuracy: 0.8132
Epoch 99/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8266 - accuracy: 0.7776 - val_loss: 0.7899 - val_accuracy: 0.8132
Epoch 100/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8310 - accuracy: 0.7691 - val_loss: 0.7864 - val_accuracy: 0.8132
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Experiment number: 9
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 10.6647 - accuracy: 0.6375 - val_loss: 8.8109 - val_accuracy: 0.8370
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 8.0621 - accuracy: 0.8443 - val_loss: 5.2377 - val_accuracy: 0.8370
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 5.4273 - accuracy: 0.8248 - val_loss: 4.6497 - val_accuracy: 0.8370
Epoch 4/100
7/7 [==============================] - 0s 10ms/step - loss: 4.5528 - accuracy: 0.8321 - val_loss: 4.6285 - val_accuracy: 0.8370
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 4.1991 - accuracy: 0.8418 - val_loss: 4.0538 - val_accuracy: 0.8370
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6600 - accuracy: 0.8564 - val_loss: 3.4313 - val_accuracy: 0.8370
Epoch 7/100
7/7 [==============================] - 0s 9ms/step - loss: 3.4778 - accuracy: 0.8418 - val_loss: 3.4827 - val_accuracy: 0.8370
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2100 - accuracy: 0.8455 - val_loss: 3.2993 - val_accuracy: 0.8370
Epoch 9/100
7/7 [==============================] - 0s 7ms/step - loss: 3.0514 - accuracy: 0.8601 - val_loss: 3.1513 - val_accuracy: 0.8370
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1000 - accuracy: 0.8467 - val_loss: 3.2024 - val_accuracy: 0.8370
Epoch 11/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0724 - accuracy: 0.8260 - val_loss: 3.2595 - val_accuracy: 0.8370
Epoch 12/100
7/7 [==============================] - 0s 7ms/step - loss: 3.0942 - accuracy: 0.8491 - val_loss: 3.2574 - val_accuracy: 0.8370
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0521 - accuracy: 0.8273 - val_loss: 2.9333 - val_accuracy: 0.8370
Epoch 14/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8733 - accuracy: 0.8394 - val_loss: 2.8617 - val_accuracy: 0.8370
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7185 - accuracy: 0.8358 - val_loss: 2.8889 - val_accuracy: 0.8370
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7539 - accuracy: 0.8504 - val_loss: 2.9185 - val_accuracy: 0.8370
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8032 - accuracy: 0.8479 - val_loss: 2.9625 - val_accuracy: 0.8370
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7423 - accuracy: 0.8455 - val_loss: 2.9371 - val_accuracy: 0.8370
Epoch 19/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8068 - accuracy: 0.8443 - val_loss: 2.8945 - val_accuracy: 0.8370
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7242 - accuracy: 0.8394 - val_loss: 2.8733 - val_accuracy: 0.8370
Epoch 21/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7594 - accuracy: 0.8504 - val_loss: 2.7813 - val_accuracy: 0.8370
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7662 - accuracy: 0.8309 - val_loss: 2.8953 - val_accuracy: 0.8370
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7435 - accuracy: 0.8479 - val_loss: 2.8350 - val_accuracy: 0.8370
Epoch 24/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7309 - accuracy: 0.8358 - val_loss: 2.9236 - val_accuracy: 0.8370
Epoch 25/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6693 - accuracy: 0.8516 - val_loss: 2.7284 - val_accuracy: 0.8370
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5486 - accuracy: 0.8540 - val_loss: 2.7165 - val_accuracy: 0.8370
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5787 - accuracy: 0.8479 - val_loss: 2.6961 - val_accuracy: 0.8370
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6115 - accuracy: 0.8455 - val_loss: 2.6448 - val_accuracy: 0.8370
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5263 - accuracy: 0.8406 - val_loss: 2.7095 - val_accuracy: 0.8370
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5772 - accuracy: 0.8504 - val_loss: 2.5812 - val_accuracy: 0.8370
Epoch 31/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6004 - accuracy: 0.8443 - val_loss: 2.6207 - val_accuracy: 0.8370
Epoch 32/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4890 - accuracy: 0.8516 - val_loss: 2.6214 - val_accuracy: 0.8370
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5876 - accuracy: 0.8406 - val_loss: 2.5615 - val_accuracy: 0.8370
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4244 - accuracy: 0.8625 - val_loss: 2.6119 - val_accuracy: 0.8370
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4247 - accuracy: 0.8552 - val_loss: 2.5139 - val_accuracy: 0.8370
Epoch 36/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4581 - accuracy: 0.8564 - val_loss: 2.5539 - val_accuracy: 0.8370
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4541 - accuracy: 0.8516 - val_loss: 2.5953 - val_accuracy: 0.8370
Epoch 38/100
7/7 [==============================] - 0s 11ms/step - loss: 2.4482 - accuracy: 0.8552 - val_loss: 2.5553 - val_accuracy: 0.8370
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4159 - accuracy: 0.8552 - val_loss: 2.4695 - val_accuracy: 0.8370
Epoch 40/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3790 - accuracy: 0.8577 - val_loss: 2.4520 - val_accuracy: 0.8370
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2912 - accuracy: 0.8491 - val_loss: 2.4730 - val_accuracy: 0.8370
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4675 - accuracy: 0.8443 - val_loss: 2.5163 - val_accuracy: 0.8152
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4694 - accuracy: 0.8504 - val_loss: 2.5781 - val_accuracy: 0.8370
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4694 - accuracy: 0.8516 - val_loss: 2.4993 - val_accuracy: 0.8370
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4062 - accuracy: 0.8406 - val_loss: 2.5215 - val_accuracy: 0.8261
Epoch 46/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3898 - accuracy: 0.8698 - val_loss: 2.4888 - val_accuracy: 0.8370
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3689 - accuracy: 0.8540 - val_loss: 2.3667 - val_accuracy: 0.8370
Epoch 48/100
7/7 [==============================] - 0s 11ms/step - loss: 2.4246 - accuracy: 0.8479 - val_loss: 2.4579 - val_accuracy: 0.8370
Epoch 49/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5040 - accuracy: 0.8345 - val_loss: 2.7238 - val_accuracy: 0.8370
Epoch 50/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5092 - accuracy: 0.8577 - val_loss: 2.5029 - val_accuracy: 0.8370
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4922 - accuracy: 0.8479 - val_loss: 2.5619 - val_accuracy: 0.8261
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5696 - accuracy: 0.8528 - val_loss: 2.6714 - val_accuracy: 0.8370
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5133 - accuracy: 0.8577 - val_loss: 2.5339 - val_accuracy: 0.8370
Epoch 54/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5930 - accuracy: 0.8613 - val_loss: 2.4843 - val_accuracy: 0.8370
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4303 - accuracy: 0.8516 - val_loss: 2.4708 - val_accuracy: 0.8370
Epoch 56/100
7/7 [==============================] - 0s 11ms/step - loss: 2.3744 - accuracy: 0.8540 - val_loss: 2.4967 - val_accuracy: 0.8370
Epoch 57/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4252 - accuracy: 0.8516 - val_loss: 2.4709 - val_accuracy: 0.8261
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3073 - accuracy: 0.8528 - val_loss: 2.3316 - val_accuracy: 0.8370
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3313 - accuracy: 0.8516 - val_loss: 2.4536 - val_accuracy: 0.8261
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4293 - accuracy: 0.8637 - val_loss: 2.5828 - val_accuracy: 0.7717
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4176 - accuracy: 0.8528 - val_loss: 2.4093 - val_accuracy: 0.8261
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3533 - accuracy: 0.8467 - val_loss: 2.4575 - val_accuracy: 0.8370
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3474 - accuracy: 0.8589 - val_loss: 2.4451 - val_accuracy: 0.8370
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3419 - accuracy: 0.8625 - val_loss: 2.4750 - val_accuracy: 0.8370
Epoch 65/100
7/7 [==============================] - 0s 11ms/step - loss: 2.3760 - accuracy: 0.8528 - val_loss: 2.4369 - val_accuracy: 0.8261
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4178 - accuracy: 0.8613 - val_loss: 2.4388 - val_accuracy: 0.8370
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3469 - accuracy: 0.8528 - val_loss: 2.3558 - val_accuracy: 0.8370
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3412 - accuracy: 0.8382 - val_loss: 2.3113 - val_accuracy: 0.8587
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5563 - accuracy: 0.8577 - val_loss: 2.5097 - val_accuracy: 0.8261
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5138 - accuracy: 0.8321 - val_loss: 2.4937 - val_accuracy: 0.8370
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4164 - accuracy: 0.8443 - val_loss: 2.3670 - val_accuracy: 0.8152
Epoch 72/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3869 - accuracy: 0.8528 - val_loss: 2.4882 - val_accuracy: 0.8370
Epoch 73/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3835 - accuracy: 0.8528 - val_loss: 2.3744 - val_accuracy: 0.8261
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3825 - accuracy: 0.8564 - val_loss: 2.4225 - val_accuracy: 0.8261
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3503 - accuracy: 0.8564 - val_loss: 2.4030 - val_accuracy: 0.8370
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3434 - accuracy: 0.8504 - val_loss: 2.4110 - val_accuracy: 0.8478
Epoch 77/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3095 - accuracy: 0.8491 - val_loss: 2.3533 - val_accuracy: 0.8370
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3022 - accuracy: 0.8479 - val_loss: 2.2349 - val_accuracy: 0.8587
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2277 - accuracy: 0.8443 - val_loss: 2.2708 - val_accuracy: 0.8261
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3109 - accuracy: 0.8443 - val_loss: 2.3685 - val_accuracy: 0.8478
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3103 - accuracy: 0.8540 - val_loss: 2.4603 - val_accuracy: 0.8261
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3344 - accuracy: 0.8479 - val_loss: 2.3496 - val_accuracy: 0.8261
Epoch 83/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3170 - accuracy: 0.8516 - val_loss: 2.2813 - val_accuracy: 0.8587
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2544 - accuracy: 0.8491 - val_loss: 2.5635 - val_accuracy: 0.7826
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2835 - accuracy: 0.8491 - val_loss: 2.2996 - val_accuracy: 0.8261
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2726 - accuracy: 0.8528 - val_loss: 2.2761 - val_accuracy: 0.8696
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2561 - accuracy: 0.8577 - val_loss: 2.3611 - val_accuracy: 0.8370
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2510 - accuracy: 0.8528 - val_loss: 2.2778 - val_accuracy: 0.8696
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2421 - accuracy: 0.8601 - val_loss: 2.2562 - val_accuracy: 0.8587
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2706 - accuracy: 0.8504 - val_loss: 2.2330 - val_accuracy: 0.8261
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2529 - accuracy: 0.8564 - val_loss: 2.2597 - val_accuracy: 0.8478
Epoch 92/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2693 - accuracy: 0.8516 - val_loss: 2.2816 - val_accuracy: 0.8370
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3343 - accuracy: 0.8418 - val_loss: 2.3034 - val_accuracy: 0.8261
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2538 - accuracy: 0.8589 - val_loss: 2.2781 - val_accuracy: 0.8370
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2335 - accuracy: 0.8467 - val_loss: 2.3147 - val_accuracy: 0.8261
Epoch 96/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2008 - accuracy: 0.8577 - val_loss: 2.3323 - val_accuracy: 0.8478
Epoch 97/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3239 - accuracy: 0.8504 - val_loss: 2.3063 - val_accuracy: 0.8370
Epoch 98/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2940 - accuracy: 0.8491 - val_loss: 2.2657 - val_accuracy: 0.8478
Epoch 99/100
7/7 [==============================] - 0s 14ms/step - loss: 2.2561 - accuracy: 0.8528 - val_loss: 2.3291 - val_accuracy: 0.8261
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2648 - accuracy: 0.8577 - val_loss: 2.2773 - val_accuracy: 0.8261
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 44ms/step - loss: 10.8149 - accuracy: 0.5900 - val_loss: 8.9593 - val_accuracy: 0.7935
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 7.9730 - accuracy: 0.8358 - val_loss: 5.3568 - val_accuracy: 0.7935
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 5.6049 - accuracy: 0.8224 - val_loss: 4.9858 - val_accuracy: 0.7935
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 4.7065 - accuracy: 0.8212 - val_loss: 4.7175 - val_accuracy: 0.7935
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 4.3262 - accuracy: 0.8504 - val_loss: 4.0892 - val_accuracy: 0.7935
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5789 - accuracy: 0.8601 - val_loss: 3.5220 - val_accuracy: 0.7935
Epoch 7/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3951 - accuracy: 0.8443 - val_loss: 3.5429 - val_accuracy: 0.7935
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2534 - accuracy: 0.8418 - val_loss: 3.4043 - val_accuracy: 0.7935
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3041 - accuracy: 0.8516 - val_loss: 3.3779 - val_accuracy: 0.7935
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2138 - accuracy: 0.8224 - val_loss: 3.1139 - val_accuracy: 0.7935
Epoch 11/100
7/7 [==============================] - 0s 7ms/step - loss: 3.0455 - accuracy: 0.8504 - val_loss: 3.0264 - val_accuracy: 0.7935
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8301 - accuracy: 0.8504 - val_loss: 2.9433 - val_accuracy: 0.7935
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7259 - accuracy: 0.8577 - val_loss: 2.8755 - val_accuracy: 0.7935
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7278 - accuracy: 0.8431 - val_loss: 2.7864 - val_accuracy: 0.7935
Epoch 15/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6221 - accuracy: 0.8431 - val_loss: 2.8976 - val_accuracy: 0.7935
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6298 - accuracy: 0.8552 - val_loss: 2.6890 - val_accuracy: 0.7935
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5859 - accuracy: 0.8577 - val_loss: 2.8017 - val_accuracy: 0.7935
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5990 - accuracy: 0.8443 - val_loss: 2.7379 - val_accuracy: 0.7935
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7266 - accuracy: 0.8382 - val_loss: 2.7067 - val_accuracy: 0.7935
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5744 - accuracy: 0.8516 - val_loss: 2.6520 - val_accuracy: 0.7935
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5315 - accuracy: 0.8625 - val_loss: 2.6424 - val_accuracy: 0.7935
Epoch 22/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6029 - accuracy: 0.8491 - val_loss: 2.7783 - val_accuracy: 0.7935
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6575 - accuracy: 0.8613 - val_loss: 2.5889 - val_accuracy: 0.7935
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5993 - accuracy: 0.8443 - val_loss: 2.6632 - val_accuracy: 0.7935
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4789 - accuracy: 0.8552 - val_loss: 2.5911 - val_accuracy: 0.7935
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5938 - accuracy: 0.8613 - val_loss: 2.5715 - val_accuracy: 0.7935
Epoch 27/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4949 - accuracy: 0.8394 - val_loss: 2.6582 - val_accuracy: 0.7935
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4730 - accuracy: 0.8564 - val_loss: 2.4978 - val_accuracy: 0.7935
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4458 - accuracy: 0.8455 - val_loss: 2.5780 - val_accuracy: 0.7935
Epoch 30/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4719 - accuracy: 0.8467 - val_loss: 2.6614 - val_accuracy: 0.7935
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4857 - accuracy: 0.8394 - val_loss: 2.6307 - val_accuracy: 0.7935
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4833 - accuracy: 0.8589 - val_loss: 2.6954 - val_accuracy: 0.7935
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4785 - accuracy: 0.8504 - val_loss: 2.5886 - val_accuracy: 0.7935
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4671 - accuracy: 0.8552 - val_loss: 2.5231 - val_accuracy: 0.7935
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3613 - accuracy: 0.8637 - val_loss: 2.4839 - val_accuracy: 0.7935
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4672 - accuracy: 0.8418 - val_loss: 2.5704 - val_accuracy: 0.7935
Epoch 37/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4278 - accuracy: 0.8577 - val_loss: 2.5911 - val_accuracy: 0.7935
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3666 - accuracy: 0.8625 - val_loss: 2.5031 - val_accuracy: 0.7935
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4510 - accuracy: 0.8455 - val_loss: 2.4897 - val_accuracy: 0.7935
Epoch 40/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3689 - accuracy: 0.8528 - val_loss: 2.4647 - val_accuracy: 0.7935
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3335 - accuracy: 0.8540 - val_loss: 2.5046 - val_accuracy: 0.7935
Epoch 42/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3880 - accuracy: 0.8552 - val_loss: 2.5374 - val_accuracy: 0.7935
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3982 - accuracy: 0.8491 - val_loss: 2.4431 - val_accuracy: 0.7935
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3859 - accuracy: 0.8504 - val_loss: 2.5291 - val_accuracy: 0.7935
Epoch 45/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3993 - accuracy: 0.8504 - val_loss: 2.4951 - val_accuracy: 0.7935
Epoch 46/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3047 - accuracy: 0.8552 - val_loss: 2.5513 - val_accuracy: 0.7935
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4216 - accuracy: 0.8382 - val_loss: 2.7138 - val_accuracy: 0.7935
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4404 - accuracy: 0.8564 - val_loss: 2.4596 - val_accuracy: 0.7935
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3697 - accuracy: 0.8516 - val_loss: 2.4801 - val_accuracy: 0.7935
Epoch 50/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4109 - accuracy: 0.8455 - val_loss: 2.5473 - val_accuracy: 0.7935
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4002 - accuracy: 0.8491 - val_loss: 2.5744 - val_accuracy: 0.7935
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4221 - accuracy: 0.8443 - val_loss: 2.3711 - val_accuracy: 0.7935
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3056 - accuracy: 0.8491 - val_loss: 2.4536 - val_accuracy: 0.7935
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2664 - accuracy: 0.8589 - val_loss: 2.3583 - val_accuracy: 0.7935
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3281 - accuracy: 0.8491 - val_loss: 2.3590 - val_accuracy: 0.7935
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3132 - accuracy: 0.8443 - val_loss: 2.4352 - val_accuracy: 0.8043
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3649 - accuracy: 0.8552 - val_loss: 2.3240 - val_accuracy: 0.8043
Epoch 58/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3838 - accuracy: 0.8479 - val_loss: 2.3974 - val_accuracy: 0.7935
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3589 - accuracy: 0.8589 - val_loss: 2.3275 - val_accuracy: 0.7935
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3100 - accuracy: 0.8504 - val_loss: 2.4567 - val_accuracy: 0.7935
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3375 - accuracy: 0.8516 - val_loss: 2.5125 - val_accuracy: 0.7935
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3122 - accuracy: 0.8601 - val_loss: 2.3381 - val_accuracy: 0.7935
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2520 - accuracy: 0.8662 - val_loss: 2.4467 - val_accuracy: 0.7826
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3662 - accuracy: 0.8479 - val_loss: 2.3353 - val_accuracy: 0.7935
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3216 - accuracy: 0.8650 - val_loss: 2.4001 - val_accuracy: 0.7935
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3448 - accuracy: 0.8394 - val_loss: 2.2917 - val_accuracy: 0.7935
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3120 - accuracy: 0.8613 - val_loss: 2.2472 - val_accuracy: 0.7935
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2503 - accuracy: 0.8504 - val_loss: 2.3667 - val_accuracy: 0.7935
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3002 - accuracy: 0.8540 - val_loss: 2.3432 - val_accuracy: 0.7935
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2594 - accuracy: 0.8564 - val_loss: 2.4290 - val_accuracy: 0.7935
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3091 - accuracy: 0.8552 - val_loss: 2.2613 - val_accuracy: 0.8370
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4152 - accuracy: 0.8540 - val_loss: 2.4324 - val_accuracy: 0.7935
Epoch 73/100
7/7 [==============================] - 0s 12ms/step - loss: 2.3726 - accuracy: 0.8552 - val_loss: 2.5811 - val_accuracy: 0.7935
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4030 - accuracy: 0.8577 - val_loss: 2.3578 - val_accuracy: 0.8261
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3602 - accuracy: 0.8637 - val_loss: 2.2712 - val_accuracy: 0.8152
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3930 - accuracy: 0.8504 - val_loss: 2.2883 - val_accuracy: 0.8478
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 2.2835 - accuracy: 0.8467 - val_loss: 2.1931 - val_accuracy: 0.8696
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3121 - accuracy: 0.8479 - val_loss: 2.2654 - val_accuracy: 0.8043
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3213 - accuracy: 0.8577 - val_loss: 2.3350 - val_accuracy: 0.8152
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3235 - accuracy: 0.8552 - val_loss: 2.2258 - val_accuracy: 0.8478
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2569 - accuracy: 0.8516 - val_loss: 2.3464 - val_accuracy: 0.7935
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2537 - accuracy: 0.8564 - val_loss: 2.2510 - val_accuracy: 0.8478
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2483 - accuracy: 0.8491 - val_loss: 2.3221 - val_accuracy: 0.7826
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2535 - accuracy: 0.8686 - val_loss: 2.4264 - val_accuracy: 0.7826
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3002 - accuracy: 0.8491 - val_loss: 2.5174 - val_accuracy: 0.7935
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2833 - accuracy: 0.8601 - val_loss: 2.2777 - val_accuracy: 0.8804
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2358 - accuracy: 0.8577 - val_loss: 2.2901 - val_accuracy: 0.7935
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2372 - accuracy: 0.8564 - val_loss: 2.2991 - val_accuracy: 0.7935
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2079 - accuracy: 0.8504 - val_loss: 2.2644 - val_accuracy: 0.7935
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2719 - accuracy: 0.8455 - val_loss: 2.2119 - val_accuracy: 0.8370
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2034 - accuracy: 0.8491 - val_loss: 2.2081 - val_accuracy: 0.7935
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 2.1741 - accuracy: 0.8577 - val_loss: 2.2572 - val_accuracy: 0.8152
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2144 - accuracy: 0.8552 - val_loss: 2.3007 - val_accuracy: 0.8152
Epoch 94/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2659 - accuracy: 0.8504 - val_loss: 2.2561 - val_accuracy: 0.8152
Epoch 95/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2342 - accuracy: 0.8528 - val_loss: 2.1877 - val_accuracy: 0.7935
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 2.1987 - accuracy: 0.8540 - val_loss: 2.2658 - val_accuracy: 0.8152
Epoch 97/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2765 - accuracy: 0.8528 - val_loss: 2.1917 - val_accuracy: 0.8804
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2337 - accuracy: 0.8613 - val_loss: 2.1611 - val_accuracy: 0.8478
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.1876 - accuracy: 0.8674 - val_loss: 2.1746 - val_accuracy: 0.8261
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2259 - accuracy: 0.8589 - val_loss: 2.2590 - val_accuracy: 0.7935
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 2s 131ms/step - loss: 10.8341 - accuracy: 0.5791 - val_loss: 9.0507 - val_accuracy: 0.8152
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 8.4503 - accuracy: 0.8285 - val_loss: 5.5821 - val_accuracy: 0.8152
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 5.6891 - accuracy: 0.8187 - val_loss: 5.1974 - val_accuracy: 0.8152
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 4.7125 - accuracy: 0.8431 - val_loss: 4.7360 - val_accuracy: 0.8152
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 4.2618 - accuracy: 0.8345 - val_loss: 4.0117 - val_accuracy: 0.8152
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8994 - accuracy: 0.8345 - val_loss: 3.7837 - val_accuracy: 0.8152
Epoch 7/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5221 - accuracy: 0.8467 - val_loss: 3.6874 - val_accuracy: 0.8152
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2773 - accuracy: 0.8528 - val_loss: 3.3274 - val_accuracy: 0.8152
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9760 - accuracy: 0.8540 - val_loss: 3.1264 - val_accuracy: 0.8152
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9609 - accuracy: 0.8479 - val_loss: 3.0265 - val_accuracy: 0.8152
Epoch 11/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7214 - accuracy: 0.8564 - val_loss: 2.9971 - val_accuracy: 0.8152
Epoch 12/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8301 - accuracy: 0.8406 - val_loss: 2.8661 - val_accuracy: 0.8152
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6873 - accuracy: 0.8552 - val_loss: 2.7036 - val_accuracy: 0.8152
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5925 - accuracy: 0.8504 - val_loss: 2.7624 - val_accuracy: 0.8152
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5401 - accuracy: 0.8504 - val_loss: 2.8152 - val_accuracy: 0.8152
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5461 - accuracy: 0.8601 - val_loss: 2.6607 - val_accuracy: 0.8152
Epoch 17/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6376 - accuracy: 0.8370 - val_loss: 2.9373 - val_accuracy: 0.8152
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6581 - accuracy: 0.8601 - val_loss: 2.7156 - val_accuracy: 0.8152
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8182 - accuracy: 0.8200 - val_loss: 2.8524 - val_accuracy: 0.8152
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7444 - accuracy: 0.8455 - val_loss: 2.8839 - val_accuracy: 0.8152
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6300 - accuracy: 0.8650 - val_loss: 2.7400 - val_accuracy: 0.8152
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6774 - accuracy: 0.8394 - val_loss: 2.7541 - val_accuracy: 0.8152
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6566 - accuracy: 0.8528 - val_loss: 2.7075 - val_accuracy: 0.8152
Epoch 24/100
7/7 [==============================] - 0s 11ms/step - loss: 2.5586 - accuracy: 0.8370 - val_loss: 2.7196 - val_accuracy: 0.8152
Epoch 25/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5454 - accuracy: 0.8601 - val_loss: 2.5906 - val_accuracy: 0.8152
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5257 - accuracy: 0.8406 - val_loss: 2.6740 - val_accuracy: 0.8152
Epoch 27/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5280 - accuracy: 0.8577 - val_loss: 2.6089 - val_accuracy: 0.8152
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5196 - accuracy: 0.8698 - val_loss: 2.7523 - val_accuracy: 0.8152
Epoch 29/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4986 - accuracy: 0.8674 - val_loss: 2.8101 - val_accuracy: 0.8152
Epoch 30/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5838 - accuracy: 0.8516 - val_loss: 2.5992 - val_accuracy: 0.8152
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4937 - accuracy: 0.8491 - val_loss: 2.6478 - val_accuracy: 0.8152
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5474 - accuracy: 0.8540 - val_loss: 2.6687 - val_accuracy: 0.8152
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4631 - accuracy: 0.8650 - val_loss: 2.5702 - val_accuracy: 0.8152
Epoch 34/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4595 - accuracy: 0.8370 - val_loss: 2.6049 - val_accuracy: 0.8152
Epoch 35/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5194 - accuracy: 0.8491 - val_loss: 2.6328 - val_accuracy: 0.8152
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4617 - accuracy: 0.8637 - val_loss: 2.6061 - val_accuracy: 0.8152
Epoch 37/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4486 - accuracy: 0.8406 - val_loss: 2.6349 - val_accuracy: 0.8152
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4229 - accuracy: 0.8662 - val_loss: 2.5243 - val_accuracy: 0.8152
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5325 - accuracy: 0.8358 - val_loss: 2.6554 - val_accuracy: 0.8152
Epoch 40/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5033 - accuracy: 0.8589 - val_loss: 2.6435 - val_accuracy: 0.8152
Epoch 41/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4899 - accuracy: 0.8491 - val_loss: 2.6273 - val_accuracy: 0.8152
Epoch 42/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4155 - accuracy: 0.8601 - val_loss: 2.5737 - val_accuracy: 0.8152
Epoch 43/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4201 - accuracy: 0.8370 - val_loss: 2.6317 - val_accuracy: 0.8152
Epoch 44/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3758 - accuracy: 0.8516 - val_loss: 2.5218 - val_accuracy: 0.8152
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3354 - accuracy: 0.8479 - val_loss: 2.4956 - val_accuracy: 0.8152
Epoch 46/100
7/7 [==============================] - 0s 6ms/step - loss: 2.3897 - accuracy: 0.8382 - val_loss: 2.5758 - val_accuracy: 0.8152
Epoch 47/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4121 - accuracy: 0.8467 - val_loss: 2.4593 - val_accuracy: 0.8152
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3666 - accuracy: 0.8479 - val_loss: 2.4666 - val_accuracy: 0.8152
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3244 - accuracy: 0.8540 - val_loss: 2.4441 - val_accuracy: 0.8152
Epoch 50/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3567 - accuracy: 0.8491 - val_loss: 2.5109 - val_accuracy: 0.8152
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3765 - accuracy: 0.8601 - val_loss: 2.4558 - val_accuracy: 0.8152
Epoch 52/100
7/7 [==============================] - 0s 12ms/step - loss: 2.3980 - accuracy: 0.8552 - val_loss: 2.5886 - val_accuracy: 0.8152
Epoch 53/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3642 - accuracy: 0.8552 - val_loss: 2.4776 - val_accuracy: 0.8261
Epoch 54/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4092 - accuracy: 0.8528 - val_loss: 2.4601 - val_accuracy: 0.8152
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3425 - accuracy: 0.8528 - val_loss: 2.4672 - val_accuracy: 0.8043
Epoch 56/100
7/7 [==============================] - 0s 6ms/step - loss: 2.3581 - accuracy: 0.8528 - val_loss: 2.4100 - val_accuracy: 0.8152
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3244 - accuracy: 0.8625 - val_loss: 2.3628 - val_accuracy: 0.8152
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3195 - accuracy: 0.8467 - val_loss: 2.4381 - val_accuracy: 0.8152
Epoch 59/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2911 - accuracy: 0.8552 - val_loss: 2.4039 - val_accuracy: 0.8152
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3564 - accuracy: 0.8528 - val_loss: 2.3702 - val_accuracy: 0.8152
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2974 - accuracy: 0.8504 - val_loss: 2.3287 - val_accuracy: 0.8261
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2815 - accuracy: 0.8662 - val_loss: 2.4794 - val_accuracy: 0.8152
Epoch 63/100
7/7 [==============================] - 0s 11ms/step - loss: 2.3192 - accuracy: 0.8370 - val_loss: 2.4823 - val_accuracy: 0.8152
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3353 - accuracy: 0.8528 - val_loss: 2.3228 - val_accuracy: 0.8261
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2894 - accuracy: 0.8467 - val_loss: 2.3804 - val_accuracy: 0.8261
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2767 - accuracy: 0.8540 - val_loss: 2.4171 - val_accuracy: 0.8152
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2778 - accuracy: 0.8431 - val_loss: 2.3678 - val_accuracy: 0.8152
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2714 - accuracy: 0.8516 - val_loss: 2.5576 - val_accuracy: 0.8152
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3512 - accuracy: 0.8455 - val_loss: 2.4513 - val_accuracy: 0.8478
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4181 - accuracy: 0.8504 - val_loss: 2.4161 - val_accuracy: 0.8261
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3341 - accuracy: 0.8613 - val_loss: 2.3920 - val_accuracy: 0.8043
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3043 - accuracy: 0.8601 - val_loss: 2.4843 - val_accuracy: 0.7609
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3057 - accuracy: 0.8552 - val_loss: 2.3463 - val_accuracy: 0.8696
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2943 - accuracy: 0.8564 - val_loss: 2.4546 - val_accuracy: 0.8261
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2963 - accuracy: 0.8589 - val_loss: 2.4011 - val_accuracy: 0.8152
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2951 - accuracy: 0.8540 - val_loss: 2.3839 - val_accuracy: 0.8587
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3072 - accuracy: 0.8528 - val_loss: 2.4008 - val_accuracy: 0.8152
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2714 - accuracy: 0.8504 - val_loss: 2.3871 - val_accuracy: 0.8261
Epoch 79/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2501 - accuracy: 0.8516 - val_loss: 2.3710 - val_accuracy: 0.8043
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3456 - accuracy: 0.8637 - val_loss: 2.3883 - val_accuracy: 0.8261
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2863 - accuracy: 0.8552 - val_loss: 2.4254 - val_accuracy: 0.8370
Epoch 82/100
7/7 [==============================] - 0s 11ms/step - loss: 2.2649 - accuracy: 0.8504 - val_loss: 2.3525 - val_accuracy: 0.8261
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2790 - accuracy: 0.8564 - val_loss: 2.3532 - val_accuracy: 0.8261
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2841 - accuracy: 0.8577 - val_loss: 2.3741 - val_accuracy: 0.8370
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4701 - accuracy: 0.8650 - val_loss: 2.4770 - val_accuracy: 0.8152
Epoch 86/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3993 - accuracy: 0.8418 - val_loss: 2.4340 - val_accuracy: 0.8370
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3342 - accuracy: 0.8528 - val_loss: 2.3712 - val_accuracy: 0.8370
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3073 - accuracy: 0.8431 - val_loss: 2.3743 - val_accuracy: 0.8043
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2517 - accuracy: 0.8528 - val_loss: 2.3076 - val_accuracy: 0.8152
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2198 - accuracy: 0.8577 - val_loss: 2.2795 - val_accuracy: 0.8478
Epoch 91/100
7/7 [==============================] - 0s 6ms/step - loss: 2.2402 - accuracy: 0.8552 - val_loss: 2.2784 - val_accuracy: 0.8261
Epoch 92/100
7/7 [==============================] - 0s 15ms/step - loss: 2.2461 - accuracy: 0.8528 - val_loss: 2.2777 - val_accuracy: 0.8478
Epoch 93/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2155 - accuracy: 0.8516 - val_loss: 2.2908 - val_accuracy: 0.8370
Epoch 94/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2531 - accuracy: 0.8516 - val_loss: 2.3219 - val_accuracy: 0.8370
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2018 - accuracy: 0.8650 - val_loss: 2.3051 - val_accuracy: 0.8587
Epoch 96/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2492 - accuracy: 0.8491 - val_loss: 2.2973 - val_accuracy: 0.8152
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2410 - accuracy: 0.8528 - val_loss: 2.2545 - val_accuracy: 0.8261
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2342 - accuracy: 0.8418 - val_loss: 2.3036 - val_accuracy: 0.8152
Epoch 99/100
7/7 [==============================] - 0s 10ms/step - loss: 2.1687 - accuracy: 0.8589 - val_loss: 2.2253 - val_accuracy: 0.8261
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 2.1310 - accuracy: 0.8589 - val_loss: 2.2609 - val_accuracy: 0.8152
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 41ms/step - loss: 10.8698 - accuracy: 0.5937 - val_loss: 8.8273 - val_accuracy: 0.8587
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 8.0222 - accuracy: 0.8406 - val_loss: 5.2229 - val_accuracy: 0.8587
Epoch 3/100
7/7 [==============================] - 0s 7ms/step - loss: 5.5086 - accuracy: 0.8297 - val_loss: 4.6615 - val_accuracy: 0.8587
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 4.5688 - accuracy: 0.8345 - val_loss: 4.1422 - val_accuracy: 0.8587
Epoch 5/100
7/7 [==============================] - 0s 10ms/step - loss: 4.1013 - accuracy: 0.8151 - val_loss: 3.8921 - val_accuracy: 0.8587
Epoch 6/100
7/7 [==============================] - 0s 10ms/step - loss: 3.5522 - accuracy: 0.8345 - val_loss: 3.2006 - val_accuracy: 0.8587
Epoch 7/100
7/7 [==============================] - 0s 9ms/step - loss: 3.1975 - accuracy: 0.8406 - val_loss: 3.1161 - val_accuracy: 0.8587
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1640 - accuracy: 0.8297 - val_loss: 3.0996 - val_accuracy: 0.8587
Epoch 9/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0483 - accuracy: 0.8540 - val_loss: 3.0850 - val_accuracy: 0.8587
Epoch 10/100
7/7 [==============================] - 0s 10ms/step - loss: 3.0828 - accuracy: 0.8273 - val_loss: 2.9000 - val_accuracy: 0.8587
Epoch 11/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8093 - accuracy: 0.8443 - val_loss: 2.9553 - val_accuracy: 0.8587
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9582 - accuracy: 0.8455 - val_loss: 2.8032 - val_accuracy: 0.8587
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9163 - accuracy: 0.8260 - val_loss: 2.7302 - val_accuracy: 0.8587
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8217 - accuracy: 0.8443 - val_loss: 2.7720 - val_accuracy: 0.8587
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7848 - accuracy: 0.8358 - val_loss: 2.7711 - val_accuracy: 0.8587
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9634 - accuracy: 0.8418 - val_loss: 2.7733 - val_accuracy: 0.8587
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6677 - accuracy: 0.8516 - val_loss: 2.8024 - val_accuracy: 0.8587
Epoch 18/100
7/7 [==============================] - 0s 14ms/step - loss: 2.8426 - accuracy: 0.8418 - val_loss: 2.6213 - val_accuracy: 0.8587
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7421 - accuracy: 0.8455 - val_loss: 2.8645 - val_accuracy: 0.8587
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9928 - accuracy: 0.8333 - val_loss: 2.9071 - val_accuracy: 0.8587
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7920 - accuracy: 0.8491 - val_loss: 2.6608 - val_accuracy: 0.8587
Epoch 22/100
7/7 [==============================] - 0s 11ms/step - loss: 2.6368 - accuracy: 0.8358 - val_loss: 2.6138 - val_accuracy: 0.8587
Epoch 23/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5936 - accuracy: 0.8467 - val_loss: 2.5304 - val_accuracy: 0.8587
Epoch 24/100
7/7 [==============================] - 0s 11ms/step - loss: 2.7526 - accuracy: 0.8358 - val_loss: 2.6893 - val_accuracy: 0.8587
Epoch 25/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6471 - accuracy: 0.8552 - val_loss: 2.5776 - val_accuracy: 0.8587
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6089 - accuracy: 0.8443 - val_loss: 2.5971 - val_accuracy: 0.8587
Epoch 27/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6094 - accuracy: 0.8455 - val_loss: 2.5436 - val_accuracy: 0.8587
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5985 - accuracy: 0.8321 - val_loss: 2.6598 - val_accuracy: 0.8587
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7952 - accuracy: 0.8321 - val_loss: 2.7734 - val_accuracy: 0.8587
Epoch 30/100
7/7 [==============================] - 0s 11ms/step - loss: 2.7445 - accuracy: 0.8394 - val_loss: 2.6082 - val_accuracy: 0.8587
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7120 - accuracy: 0.8467 - val_loss: 2.7405 - val_accuracy: 0.8587
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6487 - accuracy: 0.8491 - val_loss: 2.6646 - val_accuracy: 0.8587
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6312 - accuracy: 0.8285 - val_loss: 2.4806 - val_accuracy: 0.8587
Epoch 34/100
7/7 [==============================] - 0s 11ms/step - loss: 2.5162 - accuracy: 0.8479 - val_loss: 2.5685 - val_accuracy: 0.8587
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5977 - accuracy: 0.8491 - val_loss: 2.5061 - val_accuracy: 0.8587
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5632 - accuracy: 0.8504 - val_loss: 2.6100 - val_accuracy: 0.8696
Epoch 37/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7370 - accuracy: 0.8309 - val_loss: 2.5867 - val_accuracy: 0.8587
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5616 - accuracy: 0.8345 - val_loss: 2.5078 - val_accuracy: 0.8587
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5694 - accuracy: 0.8358 - val_loss: 2.8222 - val_accuracy: 0.8587
Epoch 40/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6434 - accuracy: 0.8504 - val_loss: 2.5613 - val_accuracy: 0.8587
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5409 - accuracy: 0.8358 - val_loss: 2.3628 - val_accuracy: 0.8587
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4692 - accuracy: 0.8358 - val_loss: 2.5242 - val_accuracy: 0.8587
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5502 - accuracy: 0.8455 - val_loss: 2.3252 - val_accuracy: 0.8587
Epoch 44/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5186 - accuracy: 0.8577 - val_loss: 2.4867 - val_accuracy: 0.8587
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4696 - accuracy: 0.8406 - val_loss: 2.4866 - val_accuracy: 0.8587
Epoch 46/100
7/7 [==============================] - 0s 11ms/step - loss: 2.4449 - accuracy: 0.8467 - val_loss: 2.4547 - val_accuracy: 0.8587
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4778 - accuracy: 0.8418 - val_loss: 2.6308 - val_accuracy: 0.8587
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5728 - accuracy: 0.8431 - val_loss: 2.4460 - val_accuracy: 0.8587
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5162 - accuracy: 0.8406 - val_loss: 2.5257 - val_accuracy: 0.8587
Epoch 50/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5141 - accuracy: 0.8394 - val_loss: 2.4495 - val_accuracy: 0.8587
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4751 - accuracy: 0.8418 - val_loss: 2.5185 - val_accuracy: 0.8587
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5470 - accuracy: 0.8528 - val_loss: 2.5755 - val_accuracy: 0.8587
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5107 - accuracy: 0.8443 - val_loss: 2.3703 - val_accuracy: 0.8587
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4683 - accuracy: 0.8516 - val_loss: 2.5046 - val_accuracy: 0.8587
Epoch 55/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4566 - accuracy: 0.8406 - val_loss: 2.4180 - val_accuracy: 0.8587
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5100 - accuracy: 0.8394 - val_loss: 2.4086 - val_accuracy: 0.8587
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4915 - accuracy: 0.8491 - val_loss: 2.4100 - val_accuracy: 0.8587
Epoch 58/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4615 - accuracy: 0.8285 - val_loss: 2.4346 - val_accuracy: 0.8587
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5165 - accuracy: 0.8479 - val_loss: 2.3560 - val_accuracy: 0.8587
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4792 - accuracy: 0.8321 - val_loss: 2.4472 - val_accuracy: 0.8587
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4852 - accuracy: 0.8577 - val_loss: 2.2948 - val_accuracy: 0.8587
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3726 - accuracy: 0.8516 - val_loss: 2.2732 - val_accuracy: 0.8696
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3730 - accuracy: 0.8528 - val_loss: 2.3442 - val_accuracy: 0.8587
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4091 - accuracy: 0.8528 - val_loss: 2.4173 - val_accuracy: 0.8696
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5150 - accuracy: 0.8431 - val_loss: 2.4193 - val_accuracy: 0.8587
Epoch 66/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4262 - accuracy: 0.8552 - val_loss: 2.2994 - val_accuracy: 0.8587
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3852 - accuracy: 0.8528 - val_loss: 2.2798 - val_accuracy: 0.8587
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3895 - accuracy: 0.8345 - val_loss: 2.2245 - val_accuracy: 0.8696
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3488 - accuracy: 0.8516 - val_loss: 2.2853 - val_accuracy: 0.8587
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3409 - accuracy: 0.8358 - val_loss: 2.3015 - val_accuracy: 0.8587
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4522 - accuracy: 0.8418 - val_loss: 2.3862 - val_accuracy: 0.8587
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3970 - accuracy: 0.8601 - val_loss: 2.3005 - val_accuracy: 0.8696
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3871 - accuracy: 0.8394 - val_loss: 2.2641 - val_accuracy: 0.9022
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3787 - accuracy: 0.8467 - val_loss: 2.3315 - val_accuracy: 0.8587
Epoch 75/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4097 - accuracy: 0.8504 - val_loss: 2.3295 - val_accuracy: 0.8913
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3308 - accuracy: 0.8491 - val_loss: 2.2819 - val_accuracy: 0.8696
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3547 - accuracy: 0.8528 - val_loss: 2.4009 - val_accuracy: 0.8478
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4074 - accuracy: 0.8540 - val_loss: 2.3101 - val_accuracy: 0.8587
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3968 - accuracy: 0.8443 - val_loss: 2.3862 - val_accuracy: 0.8696
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3630 - accuracy: 0.8589 - val_loss: 2.4624 - val_accuracy: 0.8261
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3875 - accuracy: 0.8321 - val_loss: 2.2621 - val_accuracy: 0.8587
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3422 - accuracy: 0.8431 - val_loss: 2.2539 - val_accuracy: 0.8696
Epoch 83/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4200 - accuracy: 0.8260 - val_loss: 2.2200 - val_accuracy: 0.9022
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3186 - accuracy: 0.8504 - val_loss: 2.2914 - val_accuracy: 0.9022
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3416 - accuracy: 0.8431 - val_loss: 2.3289 - val_accuracy: 0.8587
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3501 - accuracy: 0.8455 - val_loss: 2.2756 - val_accuracy: 0.8696
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3077 - accuracy: 0.8467 - val_loss: 2.1462 - val_accuracy: 0.8587
Epoch 88/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3098 - accuracy: 0.8418 - val_loss: 2.2505 - val_accuracy: 0.9130
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3080 - accuracy: 0.8504 - val_loss: 2.1464 - val_accuracy: 0.9239
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3247 - accuracy: 0.8382 - val_loss: 2.1380 - val_accuracy: 0.8587
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2450 - accuracy: 0.8479 - val_loss: 2.1633 - val_accuracy: 0.8587
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2537 - accuracy: 0.8552 - val_loss: 2.1971 - val_accuracy: 0.8587
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2306 - accuracy: 0.8601 - val_loss: 2.1660 - val_accuracy: 0.9457
Epoch 94/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3320 - accuracy: 0.8321 - val_loss: 2.1954 - val_accuracy: 0.8913
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3527 - accuracy: 0.8504 - val_loss: 2.1778 - val_accuracy: 0.8587
Epoch 96/100
7/7 [==============================] - 0s 11ms/step - loss: 2.2756 - accuracy: 0.8406 - val_loss: 2.2522 - val_accuracy: 0.8587
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3606 - accuracy: 0.8491 - val_loss: 2.2252 - val_accuracy: 0.8587
Epoch 98/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2798 - accuracy: 0.8540 - val_loss: 2.2711 - val_accuracy: 0.8261
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2775 - accuracy: 0.8528 - val_loss: 2.1303 - val_accuracy: 0.8696
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3146 - accuracy: 0.8394 - val_loss: 2.2181 - val_accuracy: 0.8696
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 46ms/step - loss: 10.7068 - accuracy: 0.5759 - val_loss: 8.6389 - val_accuracy: 0.8352
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 8.0413 - accuracy: 0.8372 - val_loss: 5.0947 - val_accuracy: 0.8352
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 5.3187 - accuracy: 0.8299 - val_loss: 4.4631 - val_accuracy: 0.8352
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 4.2141 - accuracy: 0.8384 - val_loss: 3.8873 - val_accuracy: 0.8352
Epoch 5/100
7/7 [==============================] - 0s 9ms/step - loss: 3.8948 - accuracy: 0.8262 - val_loss: 3.7992 - val_accuracy: 0.8352
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5663 - accuracy: 0.8372 - val_loss: 3.4686 - val_accuracy: 0.8352
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2068 - accuracy: 0.8469 - val_loss: 3.2713 - val_accuracy: 0.8352
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2377 - accuracy: 0.8518 - val_loss: 3.2533 - val_accuracy: 0.8352
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1212 - accuracy: 0.8457 - val_loss: 3.0654 - val_accuracy: 0.8352
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0801 - accuracy: 0.8372 - val_loss: 3.1087 - val_accuracy: 0.8352
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0184 - accuracy: 0.8481 - val_loss: 3.2635 - val_accuracy: 0.8352
Epoch 12/100
7/7 [==============================] - 0s 10ms/step - loss: 2.9909 - accuracy: 0.8554 - val_loss: 2.8948 - val_accuracy: 0.8352
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9978 - accuracy: 0.8420 - val_loss: 2.9882 - val_accuracy: 0.8352
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9517 - accuracy: 0.8481 - val_loss: 2.8605 - val_accuracy: 0.8352
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9153 - accuracy: 0.8214 - val_loss: 2.8124 - val_accuracy: 0.8352
Epoch 16/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7925 - accuracy: 0.8591 - val_loss: 2.8196 - val_accuracy: 0.8352
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7628 - accuracy: 0.8384 - val_loss: 2.7552 - val_accuracy: 0.8352
Epoch 18/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7296 - accuracy: 0.8372 - val_loss: 2.7566 - val_accuracy: 0.8352
Epoch 19/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6782 - accuracy: 0.8505 - val_loss: 2.7416 - val_accuracy: 0.8352
Epoch 20/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6985 - accuracy: 0.8469 - val_loss: 2.7056 - val_accuracy: 0.8352
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5217 - accuracy: 0.8518 - val_loss: 2.6116 - val_accuracy: 0.8352
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5071 - accuracy: 0.8481 - val_loss: 2.5488 - val_accuracy: 0.8352
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5863 - accuracy: 0.8372 - val_loss: 2.5811 - val_accuracy: 0.8352
Epoch 24/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5146 - accuracy: 0.8433 - val_loss: 2.5883 - val_accuracy: 0.8352
Epoch 25/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6385 - accuracy: 0.8542 - val_loss: 2.7748 - val_accuracy: 0.8352
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7148 - accuracy: 0.8445 - val_loss: 2.5997 - val_accuracy: 0.8352
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6109 - accuracy: 0.8493 - val_loss: 2.6217 - val_accuracy: 0.8352
Epoch 28/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5629 - accuracy: 0.8566 - val_loss: 2.5013 - val_accuracy: 0.8352
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5859 - accuracy: 0.8348 - val_loss: 2.5382 - val_accuracy: 0.8352
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5387 - accuracy: 0.8530 - val_loss: 2.5458 - val_accuracy: 0.8352
Epoch 31/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5574 - accuracy: 0.8457 - val_loss: 2.4534 - val_accuracy: 0.8352
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4642 - accuracy: 0.8663 - val_loss: 2.5248 - val_accuracy: 0.8352
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4313 - accuracy: 0.8591 - val_loss: 2.5465 - val_accuracy: 0.8352
Epoch 34/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5372 - accuracy: 0.8433 - val_loss: 2.4964 - val_accuracy: 0.8352
Epoch 35/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5161 - accuracy: 0.8384 - val_loss: 2.4545 - val_accuracy: 0.8352
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4541 - accuracy: 0.8457 - val_loss: 2.3879 - val_accuracy: 0.8352
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3924 - accuracy: 0.8518 - val_loss: 2.4057 - val_accuracy: 0.8352
Epoch 38/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4513 - accuracy: 0.8457 - val_loss: 2.4745 - val_accuracy: 0.8352
Epoch 39/100
7/7 [==============================] - 0s 13ms/step - loss: 2.5012 - accuracy: 0.8396 - val_loss: 2.6062 - val_accuracy: 0.8352
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4909 - accuracy: 0.8554 - val_loss: 2.4531 - val_accuracy: 0.8352
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4502 - accuracy: 0.8518 - val_loss: 2.4318 - val_accuracy: 0.8352
Epoch 42/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4549 - accuracy: 0.8518 - val_loss: 2.5348 - val_accuracy: 0.8352
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4481 - accuracy: 0.8578 - val_loss: 2.4970 - val_accuracy: 0.8352
Epoch 44/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4567 - accuracy: 0.8578 - val_loss: 2.4533 - val_accuracy: 0.8352
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5305 - accuracy: 0.8420 - val_loss: 2.5583 - val_accuracy: 0.8352
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5680 - accuracy: 0.8372 - val_loss: 2.4577 - val_accuracy: 0.8352
Epoch 47/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4302 - accuracy: 0.8518 - val_loss: 2.3788 - val_accuracy: 0.8352
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3716 - accuracy: 0.8542 - val_loss: 2.3867 - val_accuracy: 0.8352
Epoch 49/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3902 - accuracy: 0.8445 - val_loss: 2.5075 - val_accuracy: 0.8352
Epoch 50/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5288 - accuracy: 0.8360 - val_loss: 2.3766 - val_accuracy: 0.8352
Epoch 51/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3948 - accuracy: 0.8615 - val_loss: 2.4462 - val_accuracy: 0.8352
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4465 - accuracy: 0.8469 - val_loss: 2.4531 - val_accuracy: 0.8352
Epoch 53/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4385 - accuracy: 0.8566 - val_loss: 2.4927 - val_accuracy: 0.8352
Epoch 54/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4223 - accuracy: 0.8566 - val_loss: 2.2822 - val_accuracy: 0.8352
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3351 - accuracy: 0.8408 - val_loss: 2.3005 - val_accuracy: 0.8352
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3228 - accuracy: 0.8518 - val_loss: 2.3122 - val_accuracy: 0.8352
Epoch 57/100
7/7 [==============================] - 0s 7ms/step - loss: 2.2836 - accuracy: 0.8493 - val_loss: 2.2979 - val_accuracy: 0.8352
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3756 - accuracy: 0.8457 - val_loss: 2.4533 - val_accuracy: 0.8352
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3860 - accuracy: 0.8639 - val_loss: 2.3220 - val_accuracy: 0.8352
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3601 - accuracy: 0.8530 - val_loss: 2.4169 - val_accuracy: 0.8352
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4260 - accuracy: 0.8481 - val_loss: 2.2708 - val_accuracy: 0.8352
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4105 - accuracy: 0.8493 - val_loss: 2.2675 - val_accuracy: 0.8901
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4281 - accuracy: 0.8445 - val_loss: 2.3108 - val_accuracy: 0.8571
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3386 - accuracy: 0.8566 - val_loss: 2.2311 - val_accuracy: 0.8352
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2899 - accuracy: 0.8493 - val_loss: 2.2702 - val_accuracy: 0.8352
Epoch 66/100
7/7 [==============================] - 0s 11ms/step - loss: 2.2427 - accuracy: 0.8457 - val_loss: 2.3251 - val_accuracy: 0.8352
Epoch 67/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2882 - accuracy: 0.8469 - val_loss: 2.3040 - val_accuracy: 0.8352
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3530 - accuracy: 0.8408 - val_loss: 2.3309 - val_accuracy: 0.8352
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2654 - accuracy: 0.8493 - val_loss: 2.3714 - val_accuracy: 0.8352
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2769 - accuracy: 0.8518 - val_loss: 2.1915 - val_accuracy: 0.8352
Epoch 71/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2567 - accuracy: 0.8518 - val_loss: 2.2821 - val_accuracy: 0.9011
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3416 - accuracy: 0.8566 - val_loss: 2.2879 - val_accuracy: 0.8462
Epoch 73/100
7/7 [==============================] - 0s 11ms/step - loss: 2.3678 - accuracy: 0.8518 - val_loss: 2.2961 - val_accuracy: 0.8352
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3320 - accuracy: 0.8542 - val_loss: 2.2771 - val_accuracy: 0.8352
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2600 - accuracy: 0.8663 - val_loss: 2.2482 - val_accuracy: 0.8352
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2615 - accuracy: 0.8505 - val_loss: 2.2001 - val_accuracy: 0.8681
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3424 - accuracy: 0.8493 - val_loss: 2.4011 - val_accuracy: 0.8462
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3449 - accuracy: 0.8445 - val_loss: 2.2581 - val_accuracy: 0.8681
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2948 - accuracy: 0.8566 - val_loss: 2.2616 - val_accuracy: 0.8352
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3920 - accuracy: 0.8433 - val_loss: 2.2468 - val_accuracy: 0.8791
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3389 - accuracy: 0.8481 - val_loss: 2.2731 - val_accuracy: 0.8571
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2943 - accuracy: 0.8493 - val_loss: 2.2614 - val_accuracy: 0.8352
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3558 - accuracy: 0.8323 - val_loss: 2.3016 - val_accuracy: 0.8571
Epoch 84/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3176 - accuracy: 0.8566 - val_loss: 2.2425 - val_accuracy: 0.8462
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2630 - accuracy: 0.8518 - val_loss: 2.2202 - val_accuracy: 0.8462
Epoch 86/100
7/7 [==============================] - 0s 11ms/step - loss: 2.2886 - accuracy: 0.8457 - val_loss: 2.2430 - val_accuracy: 0.8352
Epoch 87/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2099 - accuracy: 0.8554 - val_loss: 2.1579 - val_accuracy: 0.8571
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2348 - accuracy: 0.8396 - val_loss: 2.3139 - val_accuracy: 0.8022
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4030 - accuracy: 0.8323 - val_loss: 2.2422 - val_accuracy: 0.8242
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2613 - accuracy: 0.8542 - val_loss: 2.1616 - val_accuracy: 0.9011
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2931 - accuracy: 0.8420 - val_loss: 2.2965 - val_accuracy: 0.8901
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3155 - accuracy: 0.8518 - val_loss: 2.2491 - val_accuracy: 0.8681
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2931 - accuracy: 0.8493 - val_loss: 2.2094 - val_accuracy: 0.8352
Epoch 94/100
7/7 [==============================] - 0s 6ms/step - loss: 2.2491 - accuracy: 0.8384 - val_loss: 2.1910 - val_accuracy: 0.8681
Epoch 95/100
7/7 [==============================] - 0s 10ms/step - loss: 2.1971 - accuracy: 0.8591 - val_loss: 2.1678 - val_accuracy: 0.8791
Epoch 96/100
7/7 [==============================] - 0s 6ms/step - loss: 2.2092 - accuracy: 0.8578 - val_loss: 2.0703 - val_accuracy: 0.8791
Epoch 97/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2261 - accuracy: 0.8445 - val_loss: 2.2013 - val_accuracy: 0.8462
Epoch 98/100
7/7 [==============================] - 0s 7ms/step - loss: 2.2017 - accuracy: 0.8469 - val_loss: 2.2518 - val_accuracy: 0.8681
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2449 - accuracy: 0.8591 - val_loss: 2.2531 - val_accuracy: 0.8352
Epoch 100/100
7/7 [==============================] - 0s 7ms/step - loss: 2.2676 - accuracy: 0.8566 - val_loss: 2.2038 - val_accuracy: 0.8571
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 46ms/step - loss: 11.0741 - accuracy: 0.6233 - val_loss: 8.9819 - val_accuracy: 0.8681
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 8.3978 - accuracy: 0.8299 - val_loss: 5.1723 - val_accuracy: 0.8681
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 5.3096 - accuracy: 0.8348 - val_loss: 4.8248 - val_accuracy: 0.8681
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 4.8417 - accuracy: 0.8311 - val_loss: 4.2967 - val_accuracy: 0.8681
Epoch 5/100
7/7 [==============================] - 0s 10ms/step - loss: 4.0378 - accuracy: 0.8372 - val_loss: 3.7525 - val_accuracy: 0.8681
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 4.0679 - accuracy: 0.8396 - val_loss: 3.8874 - val_accuracy: 0.8681
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6414 - accuracy: 0.8335 - val_loss: 3.6752 - val_accuracy: 0.8681
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.5946 - accuracy: 0.8420 - val_loss: 3.3201 - val_accuracy: 0.8681
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2153 - accuracy: 0.8214 - val_loss: 3.1997 - val_accuracy: 0.8681
Epoch 10/100
7/7 [==============================] - 0s 11ms/step - loss: 3.0565 - accuracy: 0.8420 - val_loss: 3.0239 - val_accuracy: 0.8681
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8829 - accuracy: 0.8493 - val_loss: 2.8627 - val_accuracy: 0.8681
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7537 - accuracy: 0.8481 - val_loss: 2.8283 - val_accuracy: 0.8681
Epoch 13/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7746 - accuracy: 0.8433 - val_loss: 2.5953 - val_accuracy: 0.8681
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6220 - accuracy: 0.8408 - val_loss: 2.6084 - val_accuracy: 0.8681
Epoch 15/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6233 - accuracy: 0.8530 - val_loss: 2.6278 - val_accuracy: 0.8681
Epoch 16/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5031 - accuracy: 0.8542 - val_loss: 2.6378 - val_accuracy: 0.8681
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5980 - accuracy: 0.8518 - val_loss: 2.5680 - val_accuracy: 0.8681
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5971 - accuracy: 0.8360 - val_loss: 2.6499 - val_accuracy: 0.8681
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5705 - accuracy: 0.8457 - val_loss: 2.6801 - val_accuracy: 0.8681
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5529 - accuracy: 0.8469 - val_loss: 2.4891 - val_accuracy: 0.8681
Epoch 21/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4879 - accuracy: 0.8433 - val_loss: 2.6896 - val_accuracy: 0.8681
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6173 - accuracy: 0.8408 - val_loss: 2.5575 - val_accuracy: 0.8681
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5325 - accuracy: 0.8372 - val_loss: 2.4383 - val_accuracy: 0.8681
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4928 - accuracy: 0.8299 - val_loss: 2.5787 - val_accuracy: 0.8681
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5418 - accuracy: 0.8493 - val_loss: 2.5659 - val_accuracy: 0.8681
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5104 - accuracy: 0.8396 - val_loss: 2.6013 - val_accuracy: 0.8681
Epoch 27/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5840 - accuracy: 0.8493 - val_loss: 2.5242 - val_accuracy: 0.8681
Epoch 28/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5191 - accuracy: 0.8615 - val_loss: 2.5911 - val_accuracy: 0.8681
Epoch 29/100
7/7 [==============================] - 0s 11ms/step - loss: 2.5542 - accuracy: 0.8396 - val_loss: 2.5835 - val_accuracy: 0.8681
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5076 - accuracy: 0.8518 - val_loss: 2.5836 - val_accuracy: 0.8681
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4821 - accuracy: 0.8615 - val_loss: 2.4419 - val_accuracy: 0.8681
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4107 - accuracy: 0.8493 - val_loss: 2.4612 - val_accuracy: 0.8681
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4691 - accuracy: 0.8445 - val_loss: 2.5318 - val_accuracy: 0.8681
Epoch 34/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4237 - accuracy: 0.8542 - val_loss: 2.4429 - val_accuracy: 0.8681
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4336 - accuracy: 0.8518 - val_loss: 2.4428 - val_accuracy: 0.8681
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3687 - accuracy: 0.8591 - val_loss: 2.4673 - val_accuracy: 0.8681
Epoch 37/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5472 - accuracy: 0.8360 - val_loss: 2.5589 - val_accuracy: 0.8681
Epoch 38/100
7/7 [==============================] - 0s 11ms/step - loss: 2.4619 - accuracy: 0.8505 - val_loss: 2.4473 - val_accuracy: 0.8681
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4217 - accuracy: 0.8566 - val_loss: 2.5167 - val_accuracy: 0.8681
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4609 - accuracy: 0.8603 - val_loss: 2.4651 - val_accuracy: 0.8681
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4698 - accuracy: 0.8408 - val_loss: 2.5734 - val_accuracy: 0.8681
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4506 - accuracy: 0.8505 - val_loss: 2.4054 - val_accuracy: 0.8681
Epoch 43/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3884 - accuracy: 0.8518 - val_loss: 2.4208 - val_accuracy: 0.8681
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3311 - accuracy: 0.8615 - val_loss: 2.4185 - val_accuracy: 0.8681
Epoch 45/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4719 - accuracy: 0.8445 - val_loss: 2.6401 - val_accuracy: 0.8681
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5669 - accuracy: 0.8433 - val_loss: 2.5235 - val_accuracy: 0.8681
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4382 - accuracy: 0.8445 - val_loss: 2.3976 - val_accuracy: 0.8681
Epoch 48/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3859 - accuracy: 0.8481 - val_loss: 2.5096 - val_accuracy: 0.8681
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4369 - accuracy: 0.8420 - val_loss: 2.4139 - val_accuracy: 0.8681
Epoch 50/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3877 - accuracy: 0.8518 - val_loss: 2.4088 - val_accuracy: 0.8681
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3455 - accuracy: 0.8469 - val_loss: 2.3258 - val_accuracy: 0.8681
Epoch 52/100
7/7 [==============================] - 0s 6ms/step - loss: 2.3155 - accuracy: 0.8445 - val_loss: 2.3713 - val_accuracy: 0.8681
Epoch 53/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4039 - accuracy: 0.8433 - val_loss: 2.4367 - val_accuracy: 0.8571
Epoch 54/100
7/7 [==============================] - 0s 6ms/step - loss: 2.4529 - accuracy: 0.8457 - val_loss: 2.4398 - val_accuracy: 0.8681
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3863 - accuracy: 0.8335 - val_loss: 2.3948 - val_accuracy: 0.8681
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4090 - accuracy: 0.8433 - val_loss: 2.4040 - val_accuracy: 0.8681
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3890 - accuracy: 0.8639 - val_loss: 2.3467 - val_accuracy: 0.8681
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3154 - accuracy: 0.8505 - val_loss: 2.4131 - val_accuracy: 0.8681
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3736 - accuracy: 0.8469 - val_loss: 2.3876 - val_accuracy: 0.8571
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3583 - accuracy: 0.8360 - val_loss: 2.3756 - val_accuracy: 0.8681
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3521 - accuracy: 0.8408 - val_loss: 2.3595 - val_accuracy: 0.8681
Epoch 62/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3308 - accuracy: 0.8566 - val_loss: 2.3640 - val_accuracy: 0.8681
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3863 - accuracy: 0.8530 - val_loss: 2.3621 - val_accuracy: 0.8462
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3499 - accuracy: 0.8518 - val_loss: 2.3366 - val_accuracy: 0.8571
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3427 - accuracy: 0.8481 - val_loss: 2.4391 - val_accuracy: 0.8791
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3887 - accuracy: 0.8591 - val_loss: 2.4326 - val_accuracy: 0.8681
Epoch 67/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3675 - accuracy: 0.8505 - val_loss: 2.4129 - val_accuracy: 0.8681
Epoch 68/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3503 - accuracy: 0.8457 - val_loss: 2.2891 - val_accuracy: 0.8681
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3404 - accuracy: 0.8493 - val_loss: 2.4021 - val_accuracy: 0.8681
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3840 - accuracy: 0.8481 - val_loss: 2.4011 - val_accuracy: 0.8791
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4458 - accuracy: 0.8493 - val_loss: 2.3928 - val_accuracy: 0.8681
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3715 - accuracy: 0.8530 - val_loss: 2.3368 - val_accuracy: 0.8681
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3498 - accuracy: 0.8469 - val_loss: 2.3463 - val_accuracy: 0.8681
Epoch 74/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2932 - accuracy: 0.8457 - val_loss: 2.4032 - val_accuracy: 0.8571
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3577 - accuracy: 0.8505 - val_loss: 2.4265 - val_accuracy: 0.8681
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3706 - accuracy: 0.8542 - val_loss: 2.2940 - val_accuracy: 0.8681
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3388 - accuracy: 0.8420 - val_loss: 2.3865 - val_accuracy: 0.8352
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3216 - accuracy: 0.8651 - val_loss: 2.4153 - val_accuracy: 0.8681
Epoch 79/100
7/7 [==============================] - 0s 6ms/step - loss: 2.3543 - accuracy: 0.8469 - val_loss: 2.3749 - val_accuracy: 0.8681
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2940 - accuracy: 0.8578 - val_loss: 2.2755 - val_accuracy: 0.8681
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3477 - accuracy: 0.8542 - val_loss: 2.3927 - val_accuracy: 0.8681
Epoch 82/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3679 - accuracy: 0.8578 - val_loss: 2.2801 - val_accuracy: 0.8791
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3142 - accuracy: 0.8542 - val_loss: 2.3909 - val_accuracy: 0.8571
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3007 - accuracy: 0.8530 - val_loss: 2.3014 - val_accuracy: 0.8242
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3183 - accuracy: 0.8457 - val_loss: 2.2802 - val_accuracy: 0.8681
Epoch 86/100
7/7 [==============================] - 0s 7ms/step - loss: 2.2855 - accuracy: 0.8469 - val_loss: 2.2128 - val_accuracy: 0.8242
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2934 - accuracy: 0.8433 - val_loss: 2.3305 - val_accuracy: 0.8571
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3545 - accuracy: 0.8348 - val_loss: 2.2499 - val_accuracy: 0.8571
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2608 - accuracy: 0.8493 - val_loss: 2.2778 - val_accuracy: 0.8681
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2727 - accuracy: 0.8493 - val_loss: 2.2682 - val_accuracy: 0.8791
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2670 - accuracy: 0.8530 - val_loss: 2.2504 - val_accuracy: 0.8791
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3004 - accuracy: 0.8469 - val_loss: 2.2913 - val_accuracy: 0.8681
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2889 - accuracy: 0.8566 - val_loss: 2.3109 - val_accuracy: 0.8681
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3032 - accuracy: 0.8566 - val_loss: 2.4996 - val_accuracy: 0.8571
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4130 - accuracy: 0.8505 - val_loss: 2.3910 - val_accuracy: 0.8462
Epoch 96/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3558 - accuracy: 0.8518 - val_loss: 2.2620 - val_accuracy: 0.8901
Epoch 97/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3714 - accuracy: 0.8493 - val_loss: 2.4397 - val_accuracy: 0.8352
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3723 - accuracy: 0.8457 - val_loss: 2.3096 - val_accuracy: 0.8352
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2943 - accuracy: 0.8578 - val_loss: 2.4086 - val_accuracy: 0.7582
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3007 - accuracy: 0.8433 - val_loss: 2.3723 - val_accuracy: 0.8132
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 44ms/step - loss: 10.6542 - accuracy: 0.5930 - val_loss: 8.5768 - val_accuracy: 0.9011
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 7.8070 - accuracy: 0.8396 - val_loss: 4.8822 - val_accuracy: 0.9011
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 5.3838 - accuracy: 0.8335 - val_loss: 4.2565 - val_accuracy: 0.9011
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 4.5893 - accuracy: 0.8226 - val_loss: 4.0148 - val_accuracy: 0.9011
Epoch 5/100
7/7 [==============================] - 0s 10ms/step - loss: 4.1540 - accuracy: 0.8262 - val_loss: 3.9102 - val_accuracy: 0.9011
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 3.7277 - accuracy: 0.8420 - val_loss: 3.4818 - val_accuracy: 0.9011
Epoch 7/100
7/7 [==============================] - 0s 7ms/step - loss: 3.5365 - accuracy: 0.8335 - val_loss: 3.2230 - val_accuracy: 0.9011
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 3.2361 - accuracy: 0.8275 - val_loss: 3.0581 - val_accuracy: 0.9011
Epoch 9/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2426 - accuracy: 0.8250 - val_loss: 3.0349 - val_accuracy: 0.9011
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0599 - accuracy: 0.8335 - val_loss: 2.8956 - val_accuracy: 0.9011
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9033 - accuracy: 0.8408 - val_loss: 2.9666 - val_accuracy: 0.9011
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0666 - accuracy: 0.8481 - val_loss: 2.9026 - val_accuracy: 0.9011
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8671 - accuracy: 0.8396 - val_loss: 2.8376 - val_accuracy: 0.9011
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9430 - accuracy: 0.8481 - val_loss: 2.8202 - val_accuracy: 0.9011
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7814 - accuracy: 0.8372 - val_loss: 2.6922 - val_accuracy: 0.9011
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7838 - accuracy: 0.8323 - val_loss: 2.6085 - val_accuracy: 0.9011
Epoch 17/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6597 - accuracy: 0.8554 - val_loss: 2.5311 - val_accuracy: 0.9011
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7104 - accuracy: 0.8360 - val_loss: 2.8087 - val_accuracy: 0.9011
Epoch 19/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7244 - accuracy: 0.8542 - val_loss: 2.5802 - val_accuracy: 0.9011
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6850 - accuracy: 0.8408 - val_loss: 2.5443 - val_accuracy: 0.9011
Epoch 21/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5772 - accuracy: 0.8445 - val_loss: 2.4953 - val_accuracy: 0.9011
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5801 - accuracy: 0.8384 - val_loss: 2.5696 - val_accuracy: 0.9011
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5961 - accuracy: 0.8481 - val_loss: 2.4410 - val_accuracy: 0.9011
Epoch 24/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5448 - accuracy: 0.8360 - val_loss: 2.5709 - val_accuracy: 0.9011
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6548 - accuracy: 0.8335 - val_loss: 2.5701 - val_accuracy: 0.9011
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6749 - accuracy: 0.8408 - val_loss: 2.4476 - val_accuracy: 0.9011
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5383 - accuracy: 0.8457 - val_loss: 2.4540 - val_accuracy: 0.9011
Epoch 28/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5406 - accuracy: 0.8469 - val_loss: 2.4009 - val_accuracy: 0.9011
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4825 - accuracy: 0.8384 - val_loss: 2.5293 - val_accuracy: 0.9011
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5730 - accuracy: 0.8469 - val_loss: 2.4491 - val_accuracy: 0.9011
Epoch 31/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5311 - accuracy: 0.8469 - val_loss: 2.3377 - val_accuracy: 0.9011
Epoch 32/100
7/7 [==============================] - 0s 6ms/step - loss: 2.5521 - accuracy: 0.8190 - val_loss: 2.4796 - val_accuracy: 0.9011
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5811 - accuracy: 0.8445 - val_loss: 2.3501 - val_accuracy: 0.9011
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4457 - accuracy: 0.8505 - val_loss: 2.3701 - val_accuracy: 0.9011
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4652 - accuracy: 0.8384 - val_loss: 2.4022 - val_accuracy: 0.9011
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4582 - accuracy: 0.8457 - val_loss: 2.3396 - val_accuracy: 0.9011
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4017 - accuracy: 0.8445 - val_loss: 2.3534 - val_accuracy: 0.9011
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4246 - accuracy: 0.8457 - val_loss: 2.2599 - val_accuracy: 0.9011
Epoch 39/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3702 - accuracy: 0.8372 - val_loss: 2.3649 - val_accuracy: 0.9011
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4030 - accuracy: 0.8469 - val_loss: 2.3591 - val_accuracy: 0.9011
Epoch 41/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4546 - accuracy: 0.8420 - val_loss: 2.4049 - val_accuracy: 0.8901
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4109 - accuracy: 0.8323 - val_loss: 2.4214 - val_accuracy: 0.9011
Epoch 43/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4239 - accuracy: 0.8493 - val_loss: 2.2705 - val_accuracy: 0.9011
Epoch 44/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4711 - accuracy: 0.8360 - val_loss: 2.4573 - val_accuracy: 0.9011
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4830 - accuracy: 0.8445 - val_loss: 2.3718 - val_accuracy: 0.9011
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4713 - accuracy: 0.8396 - val_loss: 2.4419 - val_accuracy: 0.9011
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5121 - accuracy: 0.8445 - val_loss: 2.3633 - val_accuracy: 0.8901
Epoch 48/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5072 - accuracy: 0.8360 - val_loss: 2.5363 - val_accuracy: 0.9011
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5688 - accuracy: 0.8372 - val_loss: 2.4433 - val_accuracy: 0.9011
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4805 - accuracy: 0.8445 - val_loss: 2.3887 - val_accuracy: 0.9011
Epoch 51/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4261 - accuracy: 0.8615 - val_loss: 2.3744 - val_accuracy: 0.9011
Epoch 52/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3775 - accuracy: 0.8420 - val_loss: 2.3349 - val_accuracy: 0.8901
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3650 - accuracy: 0.8542 - val_loss: 2.2640 - val_accuracy: 0.9011
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3335 - accuracy: 0.8420 - val_loss: 2.3487 - val_accuracy: 0.9011
Epoch 55/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4317 - accuracy: 0.8493 - val_loss: 2.3954 - val_accuracy: 0.9011
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4270 - accuracy: 0.8469 - val_loss: 2.4526 - val_accuracy: 0.9011
Epoch 57/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3823 - accuracy: 0.8639 - val_loss: 2.2863 - val_accuracy: 0.9011
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3546 - accuracy: 0.8481 - val_loss: 2.1906 - val_accuracy: 0.9011
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3736 - accuracy: 0.8457 - val_loss: 2.3466 - val_accuracy: 0.8901
Epoch 60/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4505 - accuracy: 0.8384 - val_loss: 2.3913 - val_accuracy: 0.9011
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4504 - accuracy: 0.8481 - val_loss: 2.3046 - val_accuracy: 0.8901
Epoch 62/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3814 - accuracy: 0.8445 - val_loss: 2.3564 - val_accuracy: 0.9011
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3697 - accuracy: 0.8445 - val_loss: 2.3365 - val_accuracy: 0.9011
Epoch 64/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4463 - accuracy: 0.8420 - val_loss: 2.3257 - val_accuracy: 0.9011
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3837 - accuracy: 0.8433 - val_loss: 2.3432 - val_accuracy: 0.9011
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3541 - accuracy: 0.8554 - val_loss: 2.2929 - val_accuracy: 0.8901
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3356 - accuracy: 0.8469 - val_loss: 2.3590 - val_accuracy: 0.8791
Epoch 68/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4165 - accuracy: 0.8518 - val_loss: 2.3566 - val_accuracy: 0.9011
Epoch 69/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4009 - accuracy: 0.8457 - val_loss: 2.3326 - val_accuracy: 0.8901
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4029 - accuracy: 0.8481 - val_loss: 2.3649 - val_accuracy: 0.9121
Epoch 71/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3716 - accuracy: 0.8481 - val_loss: 2.3759 - val_accuracy: 0.8901
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4307 - accuracy: 0.8481 - val_loss: 2.3691 - val_accuracy: 0.9011
Epoch 73/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3844 - accuracy: 0.8481 - val_loss: 2.1877 - val_accuracy: 0.9231
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4043 - accuracy: 0.8493 - val_loss: 2.2430 - val_accuracy: 0.8901
Epoch 75/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3121 - accuracy: 0.8396 - val_loss: 2.2084 - val_accuracy: 0.8901
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3622 - accuracy: 0.8396 - val_loss: 2.2802 - val_accuracy: 0.8901
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3342 - accuracy: 0.8627 - val_loss: 2.2161 - val_accuracy: 0.8901
Epoch 78/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2379 - accuracy: 0.8554 - val_loss: 2.2011 - val_accuracy: 0.8791
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2981 - accuracy: 0.8481 - val_loss: 2.3450 - val_accuracy: 0.8352
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3965 - accuracy: 0.8348 - val_loss: 2.3816 - val_accuracy: 0.9011
Epoch 81/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3738 - accuracy: 0.8566 - val_loss: 2.3112 - val_accuracy: 0.9011
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3862 - accuracy: 0.8469 - val_loss: 2.2025 - val_accuracy: 0.9121
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2908 - accuracy: 0.8384 - val_loss: 2.3104 - val_accuracy: 0.9011
Epoch 84/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3188 - accuracy: 0.8566 - val_loss: 2.2049 - val_accuracy: 0.9121
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2953 - accuracy: 0.8481 - val_loss: 2.3296 - val_accuracy: 0.8681
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3631 - accuracy: 0.8299 - val_loss: 2.3292 - val_accuracy: 0.9121
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3474 - accuracy: 0.8554 - val_loss: 2.2237 - val_accuracy: 0.9011
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3294 - accuracy: 0.8348 - val_loss: 2.2481 - val_accuracy: 0.9011
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3117 - accuracy: 0.8481 - val_loss: 2.1899 - val_accuracy: 0.9011
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2867 - accuracy: 0.8433 - val_loss: 2.2607 - val_accuracy: 0.9011
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3189 - accuracy: 0.8433 - val_loss: 2.2713 - val_accuracy: 0.8901
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3156 - accuracy: 0.8493 - val_loss: 2.2641 - val_accuracy: 0.9011
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2692 - accuracy: 0.8493 - val_loss: 2.1473 - val_accuracy: 0.9011
Epoch 94/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2389 - accuracy: 0.8542 - val_loss: 2.1780 - val_accuracy: 0.8901
Epoch 95/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3009 - accuracy: 0.8360 - val_loss: 2.2836 - val_accuracy: 0.8791
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2989 - accuracy: 0.8530 - val_loss: 2.2177 - val_accuracy: 0.9011
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2496 - accuracy: 0.8457 - val_loss: 2.1890 - val_accuracy: 0.8681
Epoch 98/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2550 - accuracy: 0.8408 - val_loss: 2.1688 - val_accuracy: 0.9011
Epoch 99/100
7/7 [==============================] - 0s 11ms/step - loss: 2.2858 - accuracy: 0.8530 - val_loss: 2.2950 - val_accuracy: 0.8791
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3699 - accuracy: 0.8408 - val_loss: 2.2600 - val_accuracy: 0.8901
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 11.2799 - accuracy: 0.5808 - val_loss: 8.9633 - val_accuracy: 0.8681
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 8.3106 - accuracy: 0.8396 - val_loss: 5.3827 - val_accuracy: 0.8681
Epoch 3/100
7/7 [==============================] - 0s 10ms/step - loss: 5.5447 - accuracy: 0.8299 - val_loss: 4.7410 - val_accuracy: 0.8681
Epoch 4/100
7/7 [==============================] - 0s 10ms/step - loss: 4.6902 - accuracy: 0.8129 - val_loss: 4.3846 - val_accuracy: 0.8681
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 3.9889 - accuracy: 0.8542 - val_loss: 3.6526 - val_accuracy: 0.8681
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6718 - accuracy: 0.8335 - val_loss: 3.3887 - val_accuracy: 0.8681
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3160 - accuracy: 0.8469 - val_loss: 3.1468 - val_accuracy: 0.8681
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 3.1668 - accuracy: 0.8457 - val_loss: 2.9466 - val_accuracy: 0.8681
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8886 - accuracy: 0.8493 - val_loss: 2.8750 - val_accuracy: 0.8681
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 2.8010 - accuracy: 0.8542 - val_loss: 2.8575 - val_accuracy: 0.8681
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9302 - accuracy: 0.8360 - val_loss: 2.8696 - val_accuracy: 0.8681
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7653 - accuracy: 0.8566 - val_loss: 2.9417 - val_accuracy: 0.8681
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9335 - accuracy: 0.8566 - val_loss: 2.9420 - val_accuracy: 0.8681
Epoch 14/100
7/7 [==============================] - 0s 10ms/step - loss: 2.8148 - accuracy: 0.8591 - val_loss: 2.8942 - val_accuracy: 0.8681
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8735 - accuracy: 0.8384 - val_loss: 2.6816 - val_accuracy: 0.8681
Epoch 16/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6329 - accuracy: 0.8591 - val_loss: 2.5973 - val_accuracy: 0.8681
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5679 - accuracy: 0.8396 - val_loss: 2.5457 - val_accuracy: 0.8681
Epoch 18/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6016 - accuracy: 0.8372 - val_loss: 2.6580 - val_accuracy: 0.8681
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4886 - accuracy: 0.8591 - val_loss: 2.5031 - val_accuracy: 0.8681
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4914 - accuracy: 0.8420 - val_loss: 2.4931 - val_accuracy: 0.8681
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5299 - accuracy: 0.8335 - val_loss: 2.5185 - val_accuracy: 0.8681
Epoch 22/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4847 - accuracy: 0.8518 - val_loss: 2.5062 - val_accuracy: 0.8681
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5426 - accuracy: 0.8639 - val_loss: 2.5584 - val_accuracy: 0.8681
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6304 - accuracy: 0.8493 - val_loss: 2.5714 - val_accuracy: 0.8681
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6940 - accuracy: 0.8493 - val_loss: 2.6236 - val_accuracy: 0.8681
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6647 - accuracy: 0.8445 - val_loss: 2.6293 - val_accuracy: 0.8681
Epoch 27/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5745 - accuracy: 0.8481 - val_loss: 2.5732 - val_accuracy: 0.8681
Epoch 28/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4983 - accuracy: 0.8603 - val_loss: 2.5831 - val_accuracy: 0.8681
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5046 - accuracy: 0.8457 - val_loss: 2.5242 - val_accuracy: 0.8681
Epoch 30/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5937 - accuracy: 0.8469 - val_loss: 2.5426 - val_accuracy: 0.8681
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5100 - accuracy: 0.8530 - val_loss: 2.5293 - val_accuracy: 0.8681
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4824 - accuracy: 0.8384 - val_loss: 2.5528 - val_accuracy: 0.8681
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4608 - accuracy: 0.8518 - val_loss: 2.4052 - val_accuracy: 0.8681
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4180 - accuracy: 0.8493 - val_loss: 2.4763 - val_accuracy: 0.8681
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6240 - accuracy: 0.8518 - val_loss: 2.4663 - val_accuracy: 0.8681
Epoch 36/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4544 - accuracy: 0.8554 - val_loss: 2.5514 - val_accuracy: 0.8681
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4985 - accuracy: 0.8481 - val_loss: 2.4151 - val_accuracy: 0.8681
Epoch 38/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4298 - accuracy: 0.8566 - val_loss: 2.5470 - val_accuracy: 0.8571
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6911 - accuracy: 0.8360 - val_loss: 2.5099 - val_accuracy: 0.8462
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4800 - accuracy: 0.8420 - val_loss: 2.4403 - val_accuracy: 0.8681
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4475 - accuracy: 0.8348 - val_loss: 2.4841 - val_accuracy: 0.8681
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4583 - accuracy: 0.8445 - val_loss: 2.5125 - val_accuracy: 0.8681
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5042 - accuracy: 0.8518 - val_loss: 2.4550 - val_accuracy: 0.8681
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4515 - accuracy: 0.8505 - val_loss: 2.4241 - val_accuracy: 0.8681
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4178 - accuracy: 0.8505 - val_loss: 2.3670 - val_accuracy: 0.8681
Epoch 46/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3114 - accuracy: 0.8663 - val_loss: 2.3208 - val_accuracy: 0.8681
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3846 - accuracy: 0.8639 - val_loss: 2.4618 - val_accuracy: 0.8462
Epoch 48/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4373 - accuracy: 0.8566 - val_loss: 2.5626 - val_accuracy: 0.8681
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4391 - accuracy: 0.8542 - val_loss: 2.4805 - val_accuracy: 0.8681
Epoch 50/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4462 - accuracy: 0.8408 - val_loss: 2.3657 - val_accuracy: 0.8681
Epoch 51/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3609 - accuracy: 0.8554 - val_loss: 2.3922 - val_accuracy: 0.8352
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3220 - accuracy: 0.8700 - val_loss: 2.4140 - val_accuracy: 0.8681
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3949 - accuracy: 0.8445 - val_loss: 2.4315 - val_accuracy: 0.8681
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4784 - accuracy: 0.8505 - val_loss: 2.3994 - val_accuracy: 0.8571
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3980 - accuracy: 0.8408 - val_loss: 2.3748 - val_accuracy: 0.8571
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3868 - accuracy: 0.8542 - val_loss: 2.3342 - val_accuracy: 0.8681
Epoch 57/100
7/7 [==============================] - 0s 7ms/step - loss: 2.2840 - accuracy: 0.8627 - val_loss: 2.2981 - val_accuracy: 0.8571
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3611 - accuracy: 0.8518 - val_loss: 2.5729 - val_accuracy: 0.7802
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3431 - accuracy: 0.8676 - val_loss: 2.3395 - val_accuracy: 0.8681
Epoch 60/100
7/7 [==============================] - 0s 6ms/step - loss: 2.3086 - accuracy: 0.8578 - val_loss: 2.3432 - val_accuracy: 0.8571
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3139 - accuracy: 0.8481 - val_loss: 2.4290 - val_accuracy: 0.8571
Epoch 62/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3338 - accuracy: 0.8591 - val_loss: 2.3654 - val_accuracy: 0.8681
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3484 - accuracy: 0.8578 - val_loss: 2.2890 - val_accuracy: 0.8681
Epoch 64/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3220 - accuracy: 0.8518 - val_loss: 2.3906 - val_accuracy: 0.8352
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3032 - accuracy: 0.8542 - val_loss: 2.5762 - val_accuracy: 0.7582
Epoch 66/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3460 - accuracy: 0.8591 - val_loss: 2.3463 - val_accuracy: 0.8132
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2820 - accuracy: 0.8603 - val_loss: 2.3474 - val_accuracy: 0.8352
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2692 - accuracy: 0.8481 - val_loss: 2.4478 - val_accuracy: 0.7582
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3518 - accuracy: 0.8457 - val_loss: 2.4232 - val_accuracy: 0.7802
Epoch 70/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2929 - accuracy: 0.8493 - val_loss: 2.3265 - val_accuracy: 0.8132
Epoch 71/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3144 - accuracy: 0.8445 - val_loss: 2.2854 - val_accuracy: 0.8681
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3168 - accuracy: 0.8554 - val_loss: 2.4346 - val_accuracy: 0.8352
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3762 - accuracy: 0.8457 - val_loss: 2.4948 - val_accuracy: 0.8132
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3252 - accuracy: 0.8518 - val_loss: 2.2942 - val_accuracy: 0.8571
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2756 - accuracy: 0.8493 - val_loss: 2.2294 - val_accuracy: 0.8462
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2911 - accuracy: 0.8481 - val_loss: 2.2689 - val_accuracy: 0.8571
Epoch 77/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2701 - accuracy: 0.8457 - val_loss: 2.3379 - val_accuracy: 0.8132
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2671 - accuracy: 0.8469 - val_loss: 2.2097 - val_accuracy: 0.8681
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2454 - accuracy: 0.8530 - val_loss: 2.2933 - val_accuracy: 0.8571
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2183 - accuracy: 0.8615 - val_loss: 2.3264 - val_accuracy: 0.8242
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3256 - accuracy: 0.8530 - val_loss: 2.3911 - val_accuracy: 0.8681
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3913 - accuracy: 0.8578 - val_loss: 2.4902 - val_accuracy: 0.7582
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3305 - accuracy: 0.8566 - val_loss: 2.2870 - val_accuracy: 0.7912
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3051 - accuracy: 0.8566 - val_loss: 2.4463 - val_accuracy: 0.8022
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3864 - accuracy: 0.8408 - val_loss: 2.4529 - val_accuracy: 0.7473
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2960 - accuracy: 0.8591 - val_loss: 2.3121 - val_accuracy: 0.8242
Epoch 87/100
7/7 [==============================] - 0s 7ms/step - loss: 2.2459 - accuracy: 0.8469 - val_loss: 2.2541 - val_accuracy: 0.8242
Epoch 88/100
7/7 [==============================] - 0s 7ms/step - loss: 2.2382 - accuracy: 0.8505 - val_loss: 2.4872 - val_accuracy: 0.7692
Epoch 89/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3017 - accuracy: 0.8542 - val_loss: 2.3402 - val_accuracy: 0.8681
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2913 - accuracy: 0.8493 - val_loss: 2.2698 - val_accuracy: 0.8571
Epoch 91/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2365 - accuracy: 0.8542 - val_loss: 2.6600 - val_accuracy: 0.6923
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3361 - accuracy: 0.8433 - val_loss: 2.8211 - val_accuracy: 0.6703
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3547 - accuracy: 0.8481 - val_loss: 2.2995 - val_accuracy: 0.8132
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2498 - accuracy: 0.8530 - val_loss: 2.2933 - val_accuracy: 0.8571
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2310 - accuracy: 0.8566 - val_loss: 2.5685 - val_accuracy: 0.7473
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3219 - accuracy: 0.8615 - val_loss: 2.4100 - val_accuracy: 0.8022
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3715 - accuracy: 0.8408 - val_loss: 2.3411 - val_accuracy: 0.8352
Epoch 98/100
7/7 [==============================] - 0s 6ms/step - loss: 2.2871 - accuracy: 0.8542 - val_loss: 2.3023 - val_accuracy: 0.8462
Epoch 99/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2703 - accuracy: 0.8591 - val_loss: 2.3337 - val_accuracy: 0.8132
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2852 - accuracy: 0.8433 - val_loss: 2.3346 - val_accuracy: 0.8242
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 48ms/step - loss: 10.8695 - accuracy: 0.6136 - val_loss: 8.7283 - val_accuracy: 0.8901
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 7.9688 - accuracy: 0.8299 - val_loss: 4.9255 - val_accuracy: 0.8901
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 5.3762 - accuracy: 0.8311 - val_loss: 4.5079 - val_accuracy: 0.8901
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 4.6510 - accuracy: 0.8177 - val_loss: 4.0518 - val_accuracy: 0.8901
Epoch 5/100
7/7 [==============================] - 0s 7ms/step - loss: 3.8952 - accuracy: 0.8408 - val_loss: 3.6100 - val_accuracy: 0.8901
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6258 - accuracy: 0.8287 - val_loss: 3.4187 - val_accuracy: 0.8901
Epoch 7/100
7/7 [==============================] - 0s 10ms/step - loss: 3.4197 - accuracy: 0.8262 - val_loss: 3.3774 - val_accuracy: 0.8901
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 3.3239 - accuracy: 0.8250 - val_loss: 3.1440 - val_accuracy: 0.8901
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 3.0947 - accuracy: 0.8505 - val_loss: 3.0197 - val_accuracy: 0.8901
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 3.2814 - accuracy: 0.8032 - val_loss: 2.9063 - val_accuracy: 0.8901
Epoch 11/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9288 - accuracy: 0.8445 - val_loss: 2.8591 - val_accuracy: 0.8901
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7910 - accuracy: 0.8481 - val_loss: 2.9841 - val_accuracy: 0.8901
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 2.9194 - accuracy: 0.8445 - val_loss: 2.7089 - val_accuracy: 0.8901
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7515 - accuracy: 0.8287 - val_loss: 2.6894 - val_accuracy: 0.8901
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7244 - accuracy: 0.8420 - val_loss: 2.5741 - val_accuracy: 0.8901
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5931 - accuracy: 0.8493 - val_loss: 2.5563 - val_accuracy: 0.8901
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5141 - accuracy: 0.8469 - val_loss: 2.4574 - val_accuracy: 0.8901
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5110 - accuracy: 0.8554 - val_loss: 2.5318 - val_accuracy: 0.8901
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5528 - accuracy: 0.8493 - val_loss: 2.3823 - val_accuracy: 0.8901
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5113 - accuracy: 0.8493 - val_loss: 2.4676 - val_accuracy: 0.8901
Epoch 21/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4707 - accuracy: 0.8603 - val_loss: 2.5336 - val_accuracy: 0.8901
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6610 - accuracy: 0.8396 - val_loss: 2.4595 - val_accuracy: 0.8901
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5565 - accuracy: 0.8214 - val_loss: 2.5672 - val_accuracy: 0.8901
Epoch 24/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5918 - accuracy: 0.8384 - val_loss: 2.5801 - val_accuracy: 0.8901
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5692 - accuracy: 0.8566 - val_loss: 2.5200 - val_accuracy: 0.8901
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6418 - accuracy: 0.8457 - val_loss: 2.6119 - val_accuracy: 0.8901
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6382 - accuracy: 0.8420 - val_loss: 2.5070 - val_accuracy: 0.8901
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5516 - accuracy: 0.8481 - val_loss: 2.4599 - val_accuracy: 0.8901
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5246 - accuracy: 0.8323 - val_loss: 2.5017 - val_accuracy: 0.8901
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5164 - accuracy: 0.8481 - val_loss: 2.3695 - val_accuracy: 0.8901
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4440 - accuracy: 0.8481 - val_loss: 2.4045 - val_accuracy: 0.8901
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5083 - accuracy: 0.8469 - val_loss: 2.4857 - val_accuracy: 0.8901
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4858 - accuracy: 0.8469 - val_loss: 2.4926 - val_accuracy: 0.8901
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5977 - accuracy: 0.8360 - val_loss: 2.4737 - val_accuracy: 0.8901
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5483 - accuracy: 0.8505 - val_loss: 2.4689 - val_accuracy: 0.8901
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4615 - accuracy: 0.8408 - val_loss: 2.3989 - val_accuracy: 0.8901
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4822 - accuracy: 0.8469 - val_loss: 2.5012 - val_accuracy: 0.8901
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5417 - accuracy: 0.8493 - val_loss: 2.5177 - val_accuracy: 0.8901
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5087 - accuracy: 0.8408 - val_loss: 2.3443 - val_accuracy: 0.8901
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4323 - accuracy: 0.8396 - val_loss: 2.3767 - val_accuracy: 0.8901
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4418 - accuracy: 0.8396 - val_loss: 2.3787 - val_accuracy: 0.8901
Epoch 42/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4168 - accuracy: 0.8481 - val_loss: 2.3708 - val_accuracy: 0.8901
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4272 - accuracy: 0.8469 - val_loss: 2.4582 - val_accuracy: 0.8901
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4885 - accuracy: 0.8323 - val_loss: 2.3655 - val_accuracy: 0.8901
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4067 - accuracy: 0.8518 - val_loss: 2.3304 - val_accuracy: 0.8901
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4465 - accuracy: 0.8445 - val_loss: 2.4175 - val_accuracy: 0.8901
Epoch 47/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3992 - accuracy: 0.8554 - val_loss: 2.3881 - val_accuracy: 0.8901
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5247 - accuracy: 0.8457 - val_loss: 2.3639 - val_accuracy: 0.8901
Epoch 49/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4828 - accuracy: 0.8505 - val_loss: 2.4764 - val_accuracy: 0.8901
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5047 - accuracy: 0.8578 - val_loss: 2.4089 - val_accuracy: 0.8791
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4508 - accuracy: 0.8457 - val_loss: 2.4242 - val_accuracy: 0.8901
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4236 - accuracy: 0.8554 - val_loss: 2.3604 - val_accuracy: 0.8901
Epoch 53/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4025 - accuracy: 0.8591 - val_loss: 2.3465 - val_accuracy: 0.8901
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4087 - accuracy: 0.8481 - val_loss: 2.4285 - val_accuracy: 0.9011
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5130 - accuracy: 0.8360 - val_loss: 2.4230 - val_accuracy: 0.8901
Epoch 56/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5623 - accuracy: 0.8396 - val_loss: 2.3516 - val_accuracy: 0.9011
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5584 - accuracy: 0.8287 - val_loss: 2.4119 - val_accuracy: 0.8901
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4913 - accuracy: 0.8408 - val_loss: 2.3858 - val_accuracy: 0.9011
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4561 - accuracy: 0.8311 - val_loss: 2.4815 - val_accuracy: 0.8901
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5928 - accuracy: 0.8372 - val_loss: 2.4107 - val_accuracy: 0.8791
Epoch 61/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4888 - accuracy: 0.8505 - val_loss: 2.4561 - val_accuracy: 0.8901
Epoch 62/100
7/7 [==============================] - 0s 12ms/step - loss: 2.4192 - accuracy: 0.8530 - val_loss: 2.3264 - val_accuracy: 0.9011
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4538 - accuracy: 0.8481 - val_loss: 2.3497 - val_accuracy: 0.8901
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4037 - accuracy: 0.8493 - val_loss: 2.2474 - val_accuracy: 0.8901
Epoch 65/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4073 - accuracy: 0.8287 - val_loss: 2.2916 - val_accuracy: 0.9011
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4353 - accuracy: 0.8591 - val_loss: 2.3293 - val_accuracy: 0.8901
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3740 - accuracy: 0.8493 - val_loss: 2.3044 - val_accuracy: 0.8901
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3570 - accuracy: 0.8591 - val_loss: 2.3034 - val_accuracy: 0.8901
Epoch 69/100
7/7 [==============================] - 0s 11ms/step - loss: 2.3594 - accuracy: 0.8554 - val_loss: 2.3584 - val_accuracy: 0.8791
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4307 - accuracy: 0.8323 - val_loss: 2.3130 - val_accuracy: 0.8901
Epoch 71/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3888 - accuracy: 0.8481 - val_loss: 2.3152 - val_accuracy: 0.9011
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3967 - accuracy: 0.8518 - val_loss: 2.3122 - val_accuracy: 0.8901
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4803 - accuracy: 0.8408 - val_loss: 2.2731 - val_accuracy: 0.8901
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4070 - accuracy: 0.8457 - val_loss: 2.3443 - val_accuracy: 0.8791
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4202 - accuracy: 0.8348 - val_loss: 2.3078 - val_accuracy: 0.8901
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4235 - accuracy: 0.8493 - val_loss: 2.2541 - val_accuracy: 0.9011
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3720 - accuracy: 0.8505 - val_loss: 2.2614 - val_accuracy: 0.9121
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3749 - accuracy: 0.8396 - val_loss: 2.3096 - val_accuracy: 0.8901
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3950 - accuracy: 0.8530 - val_loss: 2.3581 - val_accuracy: 0.8901
Epoch 80/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4971 - accuracy: 0.8481 - val_loss: 2.2879 - val_accuracy: 0.8901
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3375 - accuracy: 0.8505 - val_loss: 2.3013 - val_accuracy: 0.9011
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4459 - accuracy: 0.8420 - val_loss: 2.2829 - val_accuracy: 0.8901
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3329 - accuracy: 0.8554 - val_loss: 2.2568 - val_accuracy: 0.9011
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3436 - accuracy: 0.8360 - val_loss: 2.2860 - val_accuracy: 0.8901
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3253 - accuracy: 0.8433 - val_loss: 2.2440 - val_accuracy: 0.8901
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3088 - accuracy: 0.8469 - val_loss: 2.3159 - val_accuracy: 0.9011
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3720 - accuracy: 0.8469 - val_loss: 2.2857 - val_accuracy: 0.8901
Epoch 88/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3635 - accuracy: 0.8542 - val_loss: 2.3745 - val_accuracy: 0.8901
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4030 - accuracy: 0.8457 - val_loss: 2.3679 - val_accuracy: 0.8901
Epoch 90/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3588 - accuracy: 0.8493 - val_loss: 2.3082 - val_accuracy: 0.9121
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3098 - accuracy: 0.8481 - val_loss: 2.3338 - val_accuracy: 0.8791
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3042 - accuracy: 0.8469 - val_loss: 2.1649 - val_accuracy: 0.8901
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2754 - accuracy: 0.8542 - val_loss: 2.2537 - val_accuracy: 0.9011
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3265 - accuracy: 0.8408 - val_loss: 2.3066 - val_accuracy: 0.9011
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3196 - accuracy: 0.8493 - val_loss: 2.2648 - val_accuracy: 0.8901
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3851 - accuracy: 0.8433 - val_loss: 2.3041 - val_accuracy: 0.9011
Epoch 97/100
7/7 [==============================] - 0s 6ms/step - loss: 2.3897 - accuracy: 0.8505 - val_loss: 2.3221 - val_accuracy: 0.9011
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3959 - accuracy: 0.8408 - val_loss: 2.3871 - val_accuracy: 0.8901
Epoch 99/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4182 - accuracy: 0.8384 - val_loss: 2.2438 - val_accuracy: 0.8901
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3821 - accuracy: 0.8591 - val_loss: 2.3528 - val_accuracy: 0.8571
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 128, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 45ms/step - loss: 10.7954 - accuracy: 0.5735 - val_loss: 8.7926 - val_accuracy: 0.8352
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 7.8647 - accuracy: 0.8481 - val_loss: 5.1894 - val_accuracy: 0.8352
Epoch 3/100
7/7 [==============================] - 0s 10ms/step - loss: 5.4425 - accuracy: 0.8202 - val_loss: 4.8204 - val_accuracy: 0.8352
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 4.6969 - accuracy: 0.8457 - val_loss: 4.4931 - val_accuracy: 0.8352
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 4.2303 - accuracy: 0.8408 - val_loss: 4.0454 - val_accuracy: 0.8352
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 3.7371 - accuracy: 0.8348 - val_loss: 3.5813 - val_accuracy: 0.8352
Epoch 7/100
7/7 [==============================] - 0s 7ms/step - loss: 3.4246 - accuracy: 0.8396 - val_loss: 3.2881 - val_accuracy: 0.8352
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3036 - accuracy: 0.8445 - val_loss: 3.2624 - val_accuracy: 0.8352
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9872 - accuracy: 0.8481 - val_loss: 3.1166 - val_accuracy: 0.8352
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9978 - accuracy: 0.8420 - val_loss: 3.0139 - val_accuracy: 0.8352
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8089 - accuracy: 0.8433 - val_loss: 2.8377 - val_accuracy: 0.8352
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6995 - accuracy: 0.8566 - val_loss: 2.8529 - val_accuracy: 0.8352
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 2.7488 - accuracy: 0.8493 - val_loss: 2.8950 - val_accuracy: 0.8352
Epoch 14/100
7/7 [==============================] - 0s 6ms/step - loss: 2.7173 - accuracy: 0.8542 - val_loss: 2.7617 - val_accuracy: 0.8352
Epoch 15/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6137 - accuracy: 0.8457 - val_loss: 2.7235 - val_accuracy: 0.8352
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 2.6389 - accuracy: 0.8578 - val_loss: 2.6413 - val_accuracy: 0.8352
Epoch 17/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6222 - accuracy: 0.8493 - val_loss: 2.7411 - val_accuracy: 0.8352
Epoch 18/100
7/7 [==============================] - 0s 7ms/step - loss: 2.6186 - accuracy: 0.8554 - val_loss: 2.8074 - val_accuracy: 0.8352
Epoch 19/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6402 - accuracy: 0.8530 - val_loss: 2.6917 - val_accuracy: 0.8352
Epoch 20/100
7/7 [==============================] - 0s 11ms/step - loss: 2.6259 - accuracy: 0.8505 - val_loss: 2.7732 - val_accuracy: 0.8352
Epoch 21/100
7/7 [==============================] - 0s 9ms/step - loss: 2.6412 - accuracy: 0.8469 - val_loss: 2.6848 - val_accuracy: 0.8352
Epoch 22/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5272 - accuracy: 0.8542 - val_loss: 2.5881 - val_accuracy: 0.8352
Epoch 23/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4858 - accuracy: 0.8603 - val_loss: 2.6417 - val_accuracy: 0.8352
Epoch 24/100
7/7 [==============================] - 0s 11ms/step - loss: 2.6119 - accuracy: 0.8469 - val_loss: 2.5971 - val_accuracy: 0.8352
Epoch 25/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5911 - accuracy: 0.8457 - val_loss: 2.6574 - val_accuracy: 0.8352
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5353 - accuracy: 0.8505 - val_loss: 2.6796 - val_accuracy: 0.8352
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5645 - accuracy: 0.8530 - val_loss: 2.5512 - val_accuracy: 0.8352
Epoch 28/100
7/7 [==============================] - 0s 11ms/step - loss: 2.5237 - accuracy: 0.8505 - val_loss: 2.6702 - val_accuracy: 0.8352
Epoch 29/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5190 - accuracy: 0.8578 - val_loss: 2.6457 - val_accuracy: 0.8352
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4299 - accuracy: 0.8457 - val_loss: 2.5639 - val_accuracy: 0.8352
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 2.5452 - accuracy: 0.8335 - val_loss: 2.6142 - val_accuracy: 0.8352
Epoch 32/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5473 - accuracy: 0.8578 - val_loss: 2.4873 - val_accuracy: 0.8352
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5129 - accuracy: 0.8433 - val_loss: 2.6022 - val_accuracy: 0.8352
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4903 - accuracy: 0.8457 - val_loss: 2.6037 - val_accuracy: 0.8352
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4806 - accuracy: 0.8591 - val_loss: 2.6123 - val_accuracy: 0.8352
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5430 - accuracy: 0.8505 - val_loss: 2.5187 - val_accuracy: 0.8352
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4513 - accuracy: 0.8481 - val_loss: 2.5908 - val_accuracy: 0.8352
Epoch 38/100
7/7 [==============================] - 0s 7ms/step - loss: 2.5047 - accuracy: 0.8420 - val_loss: 2.4936 - val_accuracy: 0.8352
Epoch 39/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3953 - accuracy: 0.8518 - val_loss: 2.5134 - val_accuracy: 0.8352
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4428 - accuracy: 0.8566 - val_loss: 2.5598 - val_accuracy: 0.8352
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4711 - accuracy: 0.8651 - val_loss: 2.4756 - val_accuracy: 0.8352
Epoch 42/100
7/7 [==============================] - 0s 6ms/step - loss: 2.4313 - accuracy: 0.8518 - val_loss: 2.5093 - val_accuracy: 0.8352
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4051 - accuracy: 0.8457 - val_loss: 2.5298 - val_accuracy: 0.8352
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4822 - accuracy: 0.8457 - val_loss: 2.6518 - val_accuracy: 0.8352
Epoch 45/100
7/7 [==============================] - 0s 10ms/step - loss: 2.6815 - accuracy: 0.8518 - val_loss: 2.6488 - val_accuracy: 0.8352
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4817 - accuracy: 0.8433 - val_loss: 2.6839 - val_accuracy: 0.8242
Epoch 47/100
7/7 [==============================] - 0s 10ms/step - loss: 2.5892 - accuracy: 0.8360 - val_loss: 2.6171 - val_accuracy: 0.8352
Epoch 48/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4747 - accuracy: 0.8530 - val_loss: 2.5406 - val_accuracy: 0.8352
Epoch 49/100
7/7 [==============================] - 0s 6ms/step - loss: 2.4004 - accuracy: 0.8530 - val_loss: 2.4426 - val_accuracy: 0.8352
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3954 - accuracy: 0.8603 - val_loss: 2.5022 - val_accuracy: 0.8352
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4906 - accuracy: 0.8445 - val_loss: 2.4986 - val_accuracy: 0.8352
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3757 - accuracy: 0.8530 - val_loss: 2.5167 - val_accuracy: 0.8352
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4427 - accuracy: 0.8554 - val_loss: 2.4876 - val_accuracy: 0.8352
Epoch 54/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3233 - accuracy: 0.8566 - val_loss: 2.4951 - val_accuracy: 0.8352
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4177 - accuracy: 0.8445 - val_loss: 2.5792 - val_accuracy: 0.8352
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3892 - accuracy: 0.8542 - val_loss: 2.4703 - val_accuracy: 0.8462
Epoch 57/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3700 - accuracy: 0.8627 - val_loss: 2.4906 - val_accuracy: 0.8352
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3430 - accuracy: 0.8627 - val_loss: 2.5494 - val_accuracy: 0.8352
Epoch 59/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4215 - accuracy: 0.8530 - val_loss: 2.5710 - val_accuracy: 0.8352
Epoch 60/100
7/7 [==============================] - 0s 7ms/step - loss: 2.4631 - accuracy: 0.8578 - val_loss: 2.5398 - val_accuracy: 0.8352
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4572 - accuracy: 0.8505 - val_loss: 2.7022 - val_accuracy: 0.8352
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4614 - accuracy: 0.8493 - val_loss: 2.4399 - val_accuracy: 0.8352
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3723 - accuracy: 0.8530 - val_loss: 2.4057 - val_accuracy: 0.8352
Epoch 64/100
7/7 [==============================] - 0s 10ms/step - loss: 2.2946 - accuracy: 0.8530 - val_loss: 2.3869 - val_accuracy: 0.8242
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3250 - accuracy: 0.8542 - val_loss: 2.4657 - val_accuracy: 0.8132
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3581 - accuracy: 0.8481 - val_loss: 2.4702 - val_accuracy: 0.8352
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3065 - accuracy: 0.8481 - val_loss: 2.4554 - val_accuracy: 0.8352
Epoch 68/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3185 - accuracy: 0.8530 - val_loss: 2.4640 - val_accuracy: 0.8352
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3982 - accuracy: 0.8554 - val_loss: 2.4102 - val_accuracy: 0.8352
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3672 - accuracy: 0.8566 - val_loss: 2.4913 - val_accuracy: 0.8242
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3336 - accuracy: 0.8554 - val_loss: 2.4335 - val_accuracy: 0.7912
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3818 - accuracy: 0.8505 - val_loss: 2.4176 - val_accuracy: 0.8352
Epoch 73/100
7/7 [==============================] - 0s 13ms/step - loss: 2.3021 - accuracy: 0.8566 - val_loss: 2.4139 - val_accuracy: 0.8352
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3279 - accuracy: 0.8554 - val_loss: 2.3891 - val_accuracy: 0.8132
Epoch 75/100
7/7 [==============================] - 0s 9ms/step - loss: 2.4292 - accuracy: 0.8481 - val_loss: 2.5634 - val_accuracy: 0.8462
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4056 - accuracy: 0.8420 - val_loss: 2.3962 - val_accuracy: 0.8352
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3315 - accuracy: 0.8554 - val_loss: 2.3444 - val_accuracy: 0.8352
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3532 - accuracy: 0.8481 - val_loss: 2.5206 - val_accuracy: 0.8352
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3514 - accuracy: 0.8518 - val_loss: 2.4287 - val_accuracy: 0.8242
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4053 - accuracy: 0.8518 - val_loss: 2.4893 - val_accuracy: 0.8352
Epoch 81/100
7/7 [==============================] - 0s 6ms/step - loss: 2.4049 - accuracy: 0.8578 - val_loss: 2.5232 - val_accuracy: 0.8462
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3719 - accuracy: 0.8542 - val_loss: 2.4562 - val_accuracy: 0.8242
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3983 - accuracy: 0.8518 - val_loss: 2.5624 - val_accuracy: 0.8132
Epoch 84/100
7/7 [==============================] - 0s 10ms/step - loss: 2.4394 - accuracy: 0.8566 - val_loss: 2.4955 - val_accuracy: 0.8462
Epoch 85/100
7/7 [==============================] - 0s 6ms/step - loss: 2.4122 - accuracy: 0.8591 - val_loss: 2.4846 - val_accuracy: 0.8022
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3935 - accuracy: 0.8518 - val_loss: 2.4412 - val_accuracy: 0.8571
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4071 - accuracy: 0.8505 - val_loss: 2.4358 - val_accuracy: 0.8242
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4171 - accuracy: 0.8554 - val_loss: 2.5734 - val_accuracy: 0.7582
Epoch 89/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3533 - accuracy: 0.8627 - val_loss: 2.7580 - val_accuracy: 0.7473
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 2.5193 - accuracy: 0.8445 - val_loss: 2.5130 - val_accuracy: 0.8242
Epoch 91/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3881 - accuracy: 0.8554 - val_loss: 2.5315 - val_accuracy: 0.7582
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 2.4376 - accuracy: 0.8445 - val_loss: 2.5049 - val_accuracy: 0.8022
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 2.3700 - accuracy: 0.8627 - val_loss: 2.5007 - val_accuracy: 0.8352
Epoch 94/100
7/7 [==============================] - 0s 6ms/step - loss: 2.3065 - accuracy: 0.8457 - val_loss: 2.3920 - val_accuracy: 0.8352
Epoch 95/100
7/7 [==============================] - 0s 7ms/step - loss: 2.3000 - accuracy: 0.8591 - val_loss: 2.3765 - val_accuracy: 0.8132
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 2.2925 - accuracy: 0.8651 - val_loss: 2.3240 - val_accuracy: 0.8242
Epoch 97/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3748 - accuracy: 0.8518 - val_loss: 2.3418 - val_accuracy: 0.8352
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 2.3051 - accuracy: 0.8554 - val_loss: 2.3790 - val_accuracy: 0.7912
Epoch 99/100
7/7 [==============================] - 0s 10ms/step - loss: 2.3671 - accuracy: 0.8554 - val_loss: 2.3372 - val_accuracy: 0.8022
Epoch 100/100
7/7 [==============================] - 0s 9ms/step - loss: 2.2797 - accuracy: 0.8603 - val_loss: 2.5110 - val_accuracy: 0.7692
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 3ms/step
Experiment number: 10
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 4.5797 - accuracy: 0.6034 - val_loss: 2.1213 - val_accuracy: 0.8370
Epoch 2/100
7/7 [==============================] - 0s 7ms/step - loss: 2.7538 - accuracy: 0.8479 - val_loss: 4.5406 - val_accuracy: 0.7283
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 4.5778 - accuracy: 0.7530 - val_loss: 3.7960 - val_accuracy: 0.8370
Epoch 4/100
7/7 [==============================] - 0s 7ms/step - loss: 3.3550 - accuracy: 0.7798 - val_loss: 3.9595 - val_accuracy: 0.8370
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 4.0869 - accuracy: 0.7616 - val_loss: 5.2311 - val_accuracy: 0.8370
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 4.8455 - accuracy: 0.8041 - val_loss: 4.0829 - val_accuracy: 0.8152
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 4.6617 - accuracy: 0.8321 - val_loss: 3.9200 - val_accuracy: 0.8587
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 4.4251 - accuracy: 0.7822 - val_loss: 4.1099 - val_accuracy: 0.7935
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 4.4514 - accuracy: 0.8163 - val_loss: 4.6839 - val_accuracy: 0.8370
Epoch 10/100
7/7 [==============================] - 0s 7ms/step - loss: 4.7406 - accuracy: 0.7981 - val_loss: 6.0556 - val_accuracy: 0.8370
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 4.8686 - accuracy: 0.8200 - val_loss: 5.8419 - val_accuracy: 0.8370
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 4.8892 - accuracy: 0.8333 - val_loss: 6.8619 - val_accuracy: 0.8370
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 5.6410 - accuracy: 0.8066 - val_loss: 7.2119 - val_accuracy: 0.8370
Epoch 14/100
7/7 [==============================] - 0s 9ms/step - loss: 5.6547 - accuracy: 0.8151 - val_loss: 6.2181 - val_accuracy: 0.7500
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 5.6448 - accuracy: 0.8005 - val_loss: 6.1535 - val_accuracy: 0.7283
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 5.6272 - accuracy: 0.8200 - val_loss: 6.3764 - val_accuracy: 0.8152
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 6.1845 - accuracy: 0.8114 - val_loss: 6.7121 - val_accuracy: 0.7935
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 6.4170 - accuracy: 0.8236 - val_loss: 6.4275 - val_accuracy: 0.8370
Epoch 19/100
7/7 [==============================] - 0s 7ms/step - loss: 6.2490 - accuracy: 0.8017 - val_loss: 6.1506 - val_accuracy: 0.7826
Epoch 20/100
7/7 [==============================] - 0s 7ms/step - loss: 5.9913 - accuracy: 0.7713 - val_loss: 6.7654 - val_accuracy: 0.7935
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 6.5846 - accuracy: 0.7968 - val_loss: 6.5126 - val_accuracy: 0.7826
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 6.3986 - accuracy: 0.8114 - val_loss: 6.6830 - val_accuracy: 0.8152
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 6.2254 - accuracy: 0.8005 - val_loss: 7.2731 - val_accuracy: 0.5543
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 6.6015 - accuracy: 0.8029 - val_loss: 10.7695 - val_accuracy: 0.3043
Epoch 25/100
7/7 [==============================] - 0s 7ms/step - loss: 6.7507 - accuracy: 0.7652 - val_loss: 6.5559 - val_accuracy: 0.8370
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 6.2854 - accuracy: 0.8005 - val_loss: 8.1908 - val_accuracy: 0.8043
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 7.0200 - accuracy: 0.7725 - val_loss: 8.4972 - val_accuracy: 0.8152
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 8.0074 - accuracy: 0.7567 - val_loss: 8.3587 - val_accuracy: 0.8370
Epoch 29/100
7/7 [==============================] - 0s 7ms/step - loss: 7.6671 - accuracy: 0.8102 - val_loss: 9.5112 - val_accuracy: 0.8370
Epoch 30/100
7/7 [==============================] - 0s 7ms/step - loss: 8.0211 - accuracy: 0.7664 - val_loss: 11.4979 - val_accuracy: 0.8370
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 8.2804 - accuracy: 0.7944 - val_loss: 10.6697 - val_accuracy: 0.8370
Epoch 32/100
7/7 [==============================] - 0s 9ms/step - loss: 8.5368 - accuracy: 0.7859 - val_loss: 8.8389 - val_accuracy: 0.8152
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 9.2621 - accuracy: 0.7628 - val_loss: 9.4850 - val_accuracy: 0.8261
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 9.3256 - accuracy: 0.7859 - val_loss: 11.4847 - val_accuracy: 0.8261
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 9.6142 - accuracy: 0.7774 - val_loss: 12.1319 - val_accuracy: 0.7174
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 10.5004 - accuracy: 0.7822 - val_loss: 13.1566 - val_accuracy: 0.6413
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 11.1294 - accuracy: 0.7981 - val_loss: 15.4529 - val_accuracy: 0.5652
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 11.5047 - accuracy: 0.7506 - val_loss: 18.5802 - val_accuracy: 0.6522
Epoch 39/100
7/7 [==============================] - 0s 7ms/step - loss: 12.3766 - accuracy: 0.8224 - val_loss: 12.7529 - val_accuracy: 0.8370
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 12.0976 - accuracy: 0.7421 - val_loss: 14.6452 - val_accuracy: 0.8370
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 12.4544 - accuracy: 0.8297 - val_loss: 17.2647 - val_accuracy: 0.6304
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 13.1874 - accuracy: 0.7457 - val_loss: 15.6584 - val_accuracy: 0.8261
Epoch 43/100
7/7 [==============================] - 0s 7ms/step - loss: 14.6477 - accuracy: 0.7737 - val_loss: 24.7224 - val_accuracy: 0.7174
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 15.1594 - accuracy: 0.7968 - val_loss: 16.2518 - val_accuracy: 0.8152
Epoch 45/100
7/7 [==============================] - 0s 9ms/step - loss: 13.7603 - accuracy: 0.7944 - val_loss: 13.4149 - val_accuracy: 0.8152
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 13.7373 - accuracy: 0.8139 - val_loss: 13.6913 - val_accuracy: 0.8261
Epoch 47/100
7/7 [==============================] - 0s 7ms/step - loss: 13.9678 - accuracy: 0.7883 - val_loss: 14.7486 - val_accuracy: 0.8696
Epoch 48/100
7/7 [==============================] - 0s 7ms/step - loss: 14.6846 - accuracy: 0.8114 - val_loss: 14.0386 - val_accuracy: 0.7609
Epoch 49/100
7/7 [==============================] - 0s 9ms/step - loss: 14.2655 - accuracy: 0.7689 - val_loss: 15.3665 - val_accuracy: 0.8370
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 14.9056 - accuracy: 0.7725 - val_loss: 15.9441 - val_accuracy: 0.8370
Epoch 51/100
7/7 [==============================] - 0s 10ms/step - loss: 15.6671 - accuracy: 0.8029 - val_loss: 19.1045 - val_accuracy: 0.7283
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 17.5962 - accuracy: 0.7871 - val_loss: 19.1584 - val_accuracy: 0.8261
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 16.3552 - accuracy: 0.7944 - val_loss: 18.3554 - val_accuracy: 0.8261
Epoch 54/100
7/7 [==============================] - 0s 9ms/step - loss: 17.0547 - accuracy: 0.7908 - val_loss: 21.5349 - val_accuracy: 0.7065
Epoch 55/100
7/7 [==============================] - 0s 7ms/step - loss: 18.4357 - accuracy: 0.7871 - val_loss: 22.9669 - val_accuracy: 0.6304
Epoch 56/100
7/7 [==============================] - 0s 9ms/step - loss: 18.1639 - accuracy: 0.8248 - val_loss: 24.9050 - val_accuracy: 0.6739
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 18.2332 - accuracy: 0.7786 - val_loss: 21.2315 - val_accuracy: 0.8261
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 18.2420 - accuracy: 0.7908 - val_loss: 19.6502 - val_accuracy: 0.8370
Epoch 59/100
7/7 [==============================] - 0s 9ms/step - loss: 18.1266 - accuracy: 0.8187 - val_loss: 20.2408 - val_accuracy: 0.7935
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 19.1857 - accuracy: 0.8005 - val_loss: 21.2956 - val_accuracy: 0.7609
Epoch 61/100
7/7 [==============================] - 0s 7ms/step - loss: 19.4986 - accuracy: 0.8260 - val_loss: 22.9555 - val_accuracy: 0.8261
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 19.7349 - accuracy: 0.7993 - val_loss: 23.3075 - val_accuracy: 0.8370
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 21.3287 - accuracy: 0.7457 - val_loss: 25.8936 - val_accuracy: 0.8370
Epoch 64/100
7/7 [==============================] - 0s 6ms/step - loss: 21.5604 - accuracy: 0.7835 - val_loss: 30.1863 - val_accuracy: 0.8370
Epoch 65/100
7/7 [==============================] - 0s 5ms/step - loss: 21.2108 - accuracy: 0.8005 - val_loss: 26.6316 - val_accuracy: 0.8478
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 22.3432 - accuracy: 0.7835 - val_loss: 24.1275 - val_accuracy: 0.8478
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 20.7913 - accuracy: 0.7749 - val_loss: 23.5041 - val_accuracy: 0.8370
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 21.0071 - accuracy: 0.7932 - val_loss: 18.9888 - val_accuracy: 0.8261
Epoch 69/100
7/7 [==============================] - 0s 7ms/step - loss: 18.9893 - accuracy: 0.7664 - val_loss: 22.9563 - val_accuracy: 0.3370
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 19.8262 - accuracy: 0.7275 - val_loss: 23.4777 - val_accuracy: 0.8152
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 23.6462 - accuracy: 0.7689 - val_loss: 23.3688 - val_accuracy: 0.7826
Epoch 72/100
7/7 [==============================] - 0s 7ms/step - loss: 23.9886 - accuracy: 0.8443 - val_loss: 35.4567 - val_accuracy: 0.6413
Epoch 73/100
7/7 [==============================] - 0s 7ms/step - loss: 26.9799 - accuracy: 0.8078 - val_loss: 40.3908 - val_accuracy: 0.5978
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 30.3204 - accuracy: 0.7749 - val_loss: 34.8286 - val_accuracy: 0.5978
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 27.8882 - accuracy: 0.8066 - val_loss: 35.9371 - val_accuracy: 0.8587
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 29.9719 - accuracy: 0.7676 - val_loss: 40.0938 - val_accuracy: 0.8587
Epoch 77/100
7/7 [==============================] - 0s 9ms/step - loss: 28.4704 - accuracy: 0.7908 - val_loss: 43.9639 - val_accuracy: 0.7826
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 32.5029 - accuracy: 0.7920 - val_loss: 41.3825 - val_accuracy: 0.7935
Epoch 79/100
7/7 [==============================] - 0s 7ms/step - loss: 29.6071 - accuracy: 0.7993 - val_loss: 41.0567 - val_accuracy: 0.8261
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 30.5347 - accuracy: 0.7993 - val_loss: 32.8687 - val_accuracy: 0.8478
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 32.0164 - accuracy: 0.7822 - val_loss: 34.0241 - val_accuracy: 0.8261
Epoch 82/100
7/7 [==============================] - 0s 7ms/step - loss: 33.1940 - accuracy: 0.8090 - val_loss: 39.4040 - val_accuracy: 0.6413
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 36.4459 - accuracy: 0.8224 - val_loss: 43.8588 - val_accuracy: 0.7935
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 37.7300 - accuracy: 0.7981 - val_loss: 53.2553 - val_accuracy: 0.5761
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 41.5114 - accuracy: 0.7701 - val_loss: 46.5641 - val_accuracy: 0.8261
Epoch 86/100
7/7 [==============================] - 0s 6ms/step - loss: 40.5976 - accuracy: 0.7920 - val_loss: 47.8615 - val_accuracy: 0.7283
Epoch 87/100
7/7 [==============================] - 0s 7ms/step - loss: 43.4016 - accuracy: 0.8127 - val_loss: 63.0701 - val_accuracy: 0.7283
Epoch 88/100
7/7 [==============================] - 0s 11ms/step - loss: 46.0627 - accuracy: 0.8187 - val_loss: 56.7986 - val_accuracy: 0.7500
Epoch 89/100
7/7 [==============================] - 0s 6ms/step - loss: 48.0054 - accuracy: 0.7543 - val_loss: 54.5409 - val_accuracy: 0.8370
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 53.6354 - accuracy: 0.8200 - val_loss: 56.6671 - val_accuracy: 0.8152
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 51.0807 - accuracy: 0.7956 - val_loss: 52.5739 - val_accuracy: 0.6630
Epoch 92/100
7/7 [==============================] - 0s 7ms/step - loss: 48.9961 - accuracy: 0.7543 - val_loss: 45.6501 - val_accuracy: 0.7826
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 48.0043 - accuracy: 0.7798 - val_loss: 52.4214 - val_accuracy: 0.8370
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 47.9843 - accuracy: 0.7895 - val_loss: 56.6795 - val_accuracy: 0.7826
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 53.9580 - accuracy: 0.7762 - val_loss: 54.6628 - val_accuracy: 0.8043
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 49.3765 - accuracy: 0.7944 - val_loss: 54.2643 - val_accuracy: 0.7935
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 58.6170 - accuracy: 0.7895 - val_loss: 84.7180 - val_accuracy: 0.7391
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 69.6618 - accuracy: 0.7652 - val_loss: 66.6838 - val_accuracy: 0.7935
Epoch 99/100
7/7 [==============================] - 0s 6ms/step - loss: 73.2541 - accuracy: 0.7774 - val_loss: 78.3868 - val_accuracy: 0.6848
Epoch 100/100
7/7 [==============================] - 0s 7ms/step - loss: 71.6710 - accuracy: 0.7932 - val_loss: 71.5374 - val_accuracy: 0.8261
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 4.4821 - accuracy: 0.5365 - val_loss: 2.2582 - val_accuracy: 0.7935
Epoch 2/100
7/7 [==============================] - 0s 10ms/step - loss: 2.7795 - accuracy: 0.8516 - val_loss: 4.1861 - val_accuracy: 0.7935
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 4.1938 - accuracy: 0.8127 - val_loss: 4.1793 - val_accuracy: 0.7935
Epoch 4/100
7/7 [==============================] - 0s 7ms/step - loss: 3.3828 - accuracy: 0.8248 - val_loss: 3.6914 - val_accuracy: 0.7935
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 3.8636 - accuracy: 0.8127 - val_loss: 4.6174 - val_accuracy: 0.7935
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 4.3717 - accuracy: 0.7883 - val_loss: 3.6742 - val_accuracy: 0.6739
Epoch 7/100
7/7 [==============================] - 0s 7ms/step - loss: 4.0864 - accuracy: 0.7944 - val_loss: 3.5079 - val_accuracy: 0.8696
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 5.1435 - accuracy: 0.7749 - val_loss: 6.3817 - val_accuracy: 0.7935
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 6.6211 - accuracy: 0.8029 - val_loss: 5.4071 - val_accuracy: 0.7500
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 7.1740 - accuracy: 0.8175 - val_loss: 7.0857 - val_accuracy: 0.8587
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 8.8425 - accuracy: 0.7786 - val_loss: 9.7466 - val_accuracy: 0.7826
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 9.1735 - accuracy: 0.7725 - val_loss: 16.7652 - val_accuracy: 0.6522
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 9.6005 - accuracy: 0.7956 - val_loss: 7.0375 - val_accuracy: 0.8804
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 8.6027 - accuracy: 0.8127 - val_loss: 8.3008 - val_accuracy: 0.8804
Epoch 15/100
7/7 [==============================] - 0s 10ms/step - loss: 9.6219 - accuracy: 0.8114 - val_loss: 9.4870 - val_accuracy: 0.8043
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 9.1481 - accuracy: 0.7908 - val_loss: 7.7055 - val_accuracy: 0.8261
Epoch 17/100
7/7 [==============================] - 0s 7ms/step - loss: 8.9370 - accuracy: 0.8102 - val_loss: 7.9812 - val_accuracy: 0.8043
Epoch 18/100
7/7 [==============================] - 0s 9ms/step - loss: 9.3502 - accuracy: 0.7981 - val_loss: 8.2308 - val_accuracy: 0.8152
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 9.6755 - accuracy: 0.7981 - val_loss: 8.5805 - val_accuracy: 0.8587
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 9.8169 - accuracy: 0.8066 - val_loss: 9.2592 - val_accuracy: 0.7391
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 9.7951 - accuracy: 0.8273 - val_loss: 8.9999 - val_accuracy: 0.6630
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 12.0556 - accuracy: 0.7871 - val_loss: 15.0027 - val_accuracy: 0.6087
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 11.9348 - accuracy: 0.7543 - val_loss: 24.1938 - val_accuracy: 0.7391
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 14.2117 - accuracy: 0.7981 - val_loss: 14.1703 - val_accuracy: 0.8152
Epoch 25/100
7/7 [==============================] - 0s 7ms/step - loss: 14.4104 - accuracy: 0.8090 - val_loss: 14.3264 - val_accuracy: 0.8370
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 15.8097 - accuracy: 0.7713 - val_loss: 12.9081 - val_accuracy: 0.8587
Epoch 27/100
7/7 [==============================] - 0s 5ms/step - loss: 14.3672 - accuracy: 0.8248 - val_loss: 17.7507 - val_accuracy: 0.3152
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 14.5637 - accuracy: 0.7324 - val_loss: 16.7388 - val_accuracy: 0.6522
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 14.5443 - accuracy: 0.7007 - val_loss: 25.4972 - val_accuracy: 0.5109
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 15.4736 - accuracy: 0.8285 - val_loss: 17.8766 - val_accuracy: 0.5652
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 15.9382 - accuracy: 0.7567 - val_loss: 19.4593 - val_accuracy: 0.6196
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 17.4572 - accuracy: 0.8041 - val_loss: 17.2890 - val_accuracy: 0.7609
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 19.3873 - accuracy: 0.8285 - val_loss: 13.7003 - val_accuracy: 0.9022
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 19.9701 - accuracy: 0.7518 - val_loss: 20.9747 - val_accuracy: 0.7935
Epoch 35/100
7/7 [==============================] - 0s 6ms/step - loss: 20.6651 - accuracy: 0.8163 - val_loss: 30.8252 - val_accuracy: 0.5543
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 20.3385 - accuracy: 0.7676 - val_loss: 18.2846 - val_accuracy: 0.8261
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 21.6618 - accuracy: 0.7822 - val_loss: 25.3792 - val_accuracy: 0.8152
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 27.5834 - accuracy: 0.7932 - val_loss: 42.4003 - val_accuracy: 0.7935
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 31.3762 - accuracy: 0.7993 - val_loss: 48.6605 - val_accuracy: 0.7500
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 36.3803 - accuracy: 0.8041 - val_loss: 60.3575 - val_accuracy: 0.5652
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 35.4418 - accuracy: 0.8200 - val_loss: 37.8681 - val_accuracy: 0.7826
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 36.8177 - accuracy: 0.7421 - val_loss: 48.7535 - val_accuracy: 0.7935
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 40.5700 - accuracy: 0.7737 - val_loss: 35.1773 - val_accuracy: 0.8152
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 36.5022 - accuracy: 0.8175 - val_loss: 32.2632 - val_accuracy: 0.7174
Epoch 45/100
7/7 [==============================] - 0s 7ms/step - loss: 37.2844 - accuracy: 0.7543 - val_loss: 42.2175 - val_accuracy: 0.6957
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 40.5294 - accuracy: 0.7640 - val_loss: 34.9201 - val_accuracy: 0.7826
Epoch 47/100
7/7 [==============================] - 0s 5ms/step - loss: 40.5252 - accuracy: 0.7530 - val_loss: 33.9418 - val_accuracy: 0.7826
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 40.4426 - accuracy: 0.8163 - val_loss: 48.3655 - val_accuracy: 0.7826
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 47.5156 - accuracy: 0.8029 - val_loss: 44.5977 - val_accuracy: 0.7935
Epoch 50/100
7/7 [==============================] - 0s 5ms/step - loss: 50.0651 - accuracy: 0.7908 - val_loss: 49.7908 - val_accuracy: 0.7935
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 50.7327 - accuracy: 0.7725 - val_loss: 51.1724 - val_accuracy: 0.7826
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 49.9534 - accuracy: 0.7774 - val_loss: 39.3035 - val_accuracy: 0.7935
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 43.8723 - accuracy: 0.7457 - val_loss: 54.5190 - val_accuracy: 0.7935
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 48.2336 - accuracy: 0.7689 - val_loss: 37.7086 - val_accuracy: 0.8370
Epoch 55/100
7/7 [==============================] - 0s 7ms/step - loss: 46.0277 - accuracy: 0.7956 - val_loss: 37.4199 - val_accuracy: 0.7935
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 44.3071 - accuracy: 0.7482 - val_loss: 39.3765 - val_accuracy: 0.7935
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 46.5649 - accuracy: 0.7482 - val_loss: 65.2325 - val_accuracy: 0.7065
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 54.0591 - accuracy: 0.7421 - val_loss: 41.7468 - val_accuracy: 0.8696
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 54.1427 - accuracy: 0.8333 - val_loss: 66.5936 - val_accuracy: 0.8587
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 61.3441 - accuracy: 0.7798 - val_loss: 65.3493 - val_accuracy: 0.6630
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 61.1224 - accuracy: 0.7859 - val_loss: 69.4528 - val_accuracy: 0.7717
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 63.8682 - accuracy: 0.7993 - val_loss: 54.2933 - val_accuracy: 0.6196
Epoch 63/100
7/7 [==============================] - 0s 10ms/step - loss: 67.7350 - accuracy: 0.7311 - val_loss: 69.9375 - val_accuracy: 0.7935
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 71.9192 - accuracy: 0.7774 - val_loss: 69.0414 - val_accuracy: 0.8152
Epoch 65/100
7/7 [==============================] - 0s 6ms/step - loss: 85.9289 - accuracy: 0.7457 - val_loss: 126.9241 - val_accuracy: 0.7283
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 93.2031 - accuracy: 0.8187 - val_loss: 100.7630 - val_accuracy: 0.7609
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 83.2726 - accuracy: 0.7847 - val_loss: 81.6211 - val_accuracy: 0.7826
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 83.7806 - accuracy: 0.7956 - val_loss: 117.8130 - val_accuracy: 0.6848
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 80.0150 - accuracy: 0.8041 - val_loss: 75.8337 - val_accuracy: 0.7609
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 86.9478 - accuracy: 0.7506 - val_loss: 80.1789 - val_accuracy: 0.8152
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 98.7158 - accuracy: 0.7810 - val_loss: 82.0458 - val_accuracy: 0.8478
Epoch 72/100
7/7 [==============================] - 0s 5ms/step - loss: 108.6812 - accuracy: 0.8029 - val_loss: 95.6006 - val_accuracy: 0.7935
Epoch 73/100
7/7 [==============================] - 0s 9ms/step - loss: 111.1521 - accuracy: 0.8029 - val_loss: 110.5465 - val_accuracy: 0.8152
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 114.3672 - accuracy: 0.7628 - val_loss: 102.2411 - val_accuracy: 0.7826
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 121.3060 - accuracy: 0.7628 - val_loss: 157.2904 - val_accuracy: 0.7935
Epoch 76/100
7/7 [==============================] - 0s 13ms/step - loss: 154.8769 - accuracy: 0.8248 - val_loss: 119.4666 - val_accuracy: 0.8478
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 136.8390 - accuracy: 0.7956 - val_loss: 158.9845 - val_accuracy: 0.8043
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 154.9198 - accuracy: 0.7530 - val_loss: 142.7126 - val_accuracy: 0.7935
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 164.0943 - accuracy: 0.8358 - val_loss: 138.3746 - val_accuracy: 0.8370
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 162.8430 - accuracy: 0.7786 - val_loss: 163.5206 - val_accuracy: 0.7500
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 193.0046 - accuracy: 0.7056 - val_loss: 172.6274 - val_accuracy: 0.7500
Epoch 82/100
7/7 [==============================] - 0s 7ms/step - loss: 193.4245 - accuracy: 0.8102 - val_loss: 384.7299 - val_accuracy: 0.7283
Epoch 83/100
7/7 [==============================] - 0s 7ms/step - loss: 226.7470 - accuracy: 0.8321 - val_loss: 234.4790 - val_accuracy: 0.6413
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 237.7521 - accuracy: 0.7786 - val_loss: 231.4698 - val_accuracy: 0.8478
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 255.0128 - accuracy: 0.7895 - val_loss: 252.3334 - val_accuracy: 0.8152
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 241.1102 - accuracy: 0.8212 - val_loss: 199.5336 - val_accuracy: 0.7935
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 256.7552 - accuracy: 0.7932 - val_loss: 239.5759 - val_accuracy: 0.8152
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 271.8252 - accuracy: 0.7628 - val_loss: 222.1075 - val_accuracy: 0.8043
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 287.2789 - accuracy: 0.7445 - val_loss: 221.7791 - val_accuracy: 0.8804
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 295.4686 - accuracy: 0.7956 - val_loss: 338.4761 - val_accuracy: 0.5978
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 373.0431 - accuracy: 0.7628 - val_loss: 381.2490 - val_accuracy: 0.6413
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 361.8265 - accuracy: 0.7640 - val_loss: 335.8725 - val_accuracy: 0.7935
Epoch 93/100
7/7 [==============================] - 0s 5ms/step - loss: 363.7191 - accuracy: 0.7409 - val_loss: 472.4388 - val_accuracy: 0.7935
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 399.7969 - accuracy: 0.8236 - val_loss: 633.3771 - val_accuracy: 0.6739
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 495.0666 - accuracy: 0.7883 - val_loss: 604.0114 - val_accuracy: 0.7935
Epoch 96/100
7/7 [==============================] - 0s 5ms/step - loss: 505.4567 - accuracy: 0.6861 - val_loss: 296.3799 - val_accuracy: 0.8587
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 586.7075 - accuracy: 0.8528 - val_loss: 375.1064 - val_accuracy: 0.8043
Epoch 98/100
7/7 [==============================] - 0s 10ms/step - loss: 592.4692 - accuracy: 0.7530 - val_loss: 389.0761 - val_accuracy: 0.7935
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 542.0880 - accuracy: 0.7956 - val_loss: 365.8494 - val_accuracy: 0.7174
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 525.5022 - accuracy: 0.7348 - val_loss: 341.0057 - val_accuracy: 0.8587
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 2s 42ms/step - loss: 4.2688 - accuracy: 0.6192 - val_loss: 2.2183 - val_accuracy: 0.8152
Epoch 2/100
7/7 [==============================] - 0s 16ms/step - loss: 2.7484 - accuracy: 0.8479 - val_loss: 4.1424 - val_accuracy: 0.8043
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 4.2929 - accuracy: 0.7567 - val_loss: 4.2383 - val_accuracy: 0.8152
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4453 - accuracy: 0.7981 - val_loss: 3.6445 - val_accuracy: 0.8152
Epoch 5/100
7/7 [==============================] - 0s 10ms/step - loss: 4.0207 - accuracy: 0.8443 - val_loss: 3.8809 - val_accuracy: 0.7935
Epoch 6/100
7/7 [==============================] - 0s 6ms/step - loss: 4.6414 - accuracy: 0.7956 - val_loss: 4.7848 - val_accuracy: 0.8152
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 4.3890 - accuracy: 0.7616 - val_loss: 5.7160 - val_accuracy: 0.8152
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 4.9842 - accuracy: 0.8297 - val_loss: 4.8477 - val_accuracy: 0.7935
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 5.0372 - accuracy: 0.8187 - val_loss: 5.8443 - val_accuracy: 0.8152
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 5.0701 - accuracy: 0.7835 - val_loss: 4.7983 - val_accuracy: 0.8587
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 5.6690 - accuracy: 0.8516 - val_loss: 6.9573 - val_accuracy: 0.7609
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 6.1758 - accuracy: 0.8090 - val_loss: 6.0990 - val_accuracy: 0.6739
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 5.6964 - accuracy: 0.7908 - val_loss: 6.0116 - val_accuracy: 0.8043
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 6.0408 - accuracy: 0.8431 - val_loss: 6.0907 - val_accuracy: 0.8043
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 6.9613 - accuracy: 0.8236 - val_loss: 9.3906 - val_accuracy: 0.6304
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 7.1715 - accuracy: 0.8066 - val_loss: 11.9568 - val_accuracy: 0.6630
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 7.2102 - accuracy: 0.8041 - val_loss: 7.8089 - val_accuracy: 0.7826
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 7.6092 - accuracy: 0.7956 - val_loss: 8.9906 - val_accuracy: 0.7609
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 8.4242 - accuracy: 0.8066 - val_loss: 8.4993 - val_accuracy: 0.8043
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 8.3744 - accuracy: 0.7762 - val_loss: 9.3124 - val_accuracy: 0.7500
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 9.6143 - accuracy: 0.7871 - val_loss: 11.0023 - val_accuracy: 0.8370
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 10.7347 - accuracy: 0.8029 - val_loss: 14.4682 - val_accuracy: 0.8261
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 11.6934 - accuracy: 0.7713 - val_loss: 14.8069 - val_accuracy: 0.6739
Epoch 24/100
7/7 [==============================] - 0s 10ms/step - loss: 10.9101 - accuracy: 0.7859 - val_loss: 13.3544 - val_accuracy: 0.7174
Epoch 25/100
7/7 [==============================] - 0s 6ms/step - loss: 11.2771 - accuracy: 0.8114 - val_loss: 16.4135 - val_accuracy: 0.6304
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 11.5758 - accuracy: 0.8041 - val_loss: 14.7598 - val_accuracy: 0.7826
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 12.7855 - accuracy: 0.7543 - val_loss: 15.1662 - val_accuracy: 0.8152
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 12.9644 - accuracy: 0.7944 - val_loss: 13.2833 - val_accuracy: 0.8152
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 11.8908 - accuracy: 0.8297 - val_loss: 13.6856 - val_accuracy: 0.7174
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 13.4303 - accuracy: 0.7494 - val_loss: 13.8596 - val_accuracy: 0.7500
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 13.7439 - accuracy: 0.7737 - val_loss: 14.0565 - val_accuracy: 0.7283
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 14.3516 - accuracy: 0.7956 - val_loss: 13.7259 - val_accuracy: 0.8587
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 15.1069 - accuracy: 0.8066 - val_loss: 18.9617 - val_accuracy: 0.7065
Epoch 34/100
7/7 [==============================] - 0s 10ms/step - loss: 16.3196 - accuracy: 0.7786 - val_loss: 21.9206 - val_accuracy: 0.8152
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 16.7836 - accuracy: 0.8175 - val_loss: 18.3073 - val_accuracy: 0.7609
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 16.7670 - accuracy: 0.8029 - val_loss: 21.4317 - val_accuracy: 0.8043
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 18.6322 - accuracy: 0.7579 - val_loss: 19.0518 - val_accuracy: 0.8478
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 20.5712 - accuracy: 0.8406 - val_loss: 26.9957 - val_accuracy: 0.7717
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 23.7439 - accuracy: 0.7567 - val_loss: 36.4662 - val_accuracy: 0.8152
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 25.9830 - accuracy: 0.8333 - val_loss: 27.2270 - val_accuracy: 0.7826
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 26.7775 - accuracy: 0.7506 - val_loss: 39.2187 - val_accuracy: 0.8152
Epoch 42/100
7/7 [==============================] - 0s 10ms/step - loss: 26.7290 - accuracy: 0.7895 - val_loss: 28.1549 - val_accuracy: 0.8152
Epoch 43/100
7/7 [==============================] - 0s 9ms/step - loss: 25.2530 - accuracy: 0.8382 - val_loss: 35.9882 - val_accuracy: 0.7174
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 27.5053 - accuracy: 0.7689 - val_loss: 35.2850 - val_accuracy: 0.8261
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 28.8909 - accuracy: 0.7871 - val_loss: 34.5822 - val_accuracy: 0.8261
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 32.4364 - accuracy: 0.8406 - val_loss: 42.3863 - val_accuracy: 0.5978
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 33.6270 - accuracy: 0.7664 - val_loss: 33.9370 - val_accuracy: 0.8478
Epoch 48/100
7/7 [==============================] - 0s 7ms/step - loss: 34.1893 - accuracy: 0.7762 - val_loss: 34.0184 - val_accuracy: 0.7391
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 30.5351 - accuracy: 0.8212 - val_loss: 36.2635 - val_accuracy: 0.6848
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 28.8883 - accuracy: 0.8054 - val_loss: 31.5693 - val_accuracy: 0.8261
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 30.2277 - accuracy: 0.7993 - val_loss: 35.7205 - val_accuracy: 0.8152
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 30.6950 - accuracy: 0.7895 - val_loss: 41.8226 - val_accuracy: 0.7391
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 31.9847 - accuracy: 0.8163 - val_loss: 35.4492 - val_accuracy: 0.7283
Epoch 54/100
7/7 [==============================] - 0s 7ms/step - loss: 33.6038 - accuracy: 0.7908 - val_loss: 50.5489 - val_accuracy: 0.7500
Epoch 55/100
7/7 [==============================] - 0s 10ms/step - loss: 36.3837 - accuracy: 0.7616 - val_loss: 49.7598 - val_accuracy: 0.5761
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 36.3591 - accuracy: 0.7701 - val_loss: 40.9281 - val_accuracy: 0.7935
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 37.5359 - accuracy: 0.8273 - val_loss: 39.6489 - val_accuracy: 0.7717
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 40.8755 - accuracy: 0.7822 - val_loss: 47.5518 - val_accuracy: 0.7609
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 44.6464 - accuracy: 0.7810 - val_loss: 40.3046 - val_accuracy: 0.8261
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 50.2722 - accuracy: 0.8345 - val_loss: 80.0270 - val_accuracy: 0.3370
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 51.1334 - accuracy: 0.7482 - val_loss: 54.7927 - val_accuracy: 0.8152
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 45.8717 - accuracy: 0.7324 - val_loss: 39.7484 - val_accuracy: 0.8152
Epoch 63/100
7/7 [==============================] - 0s 10ms/step - loss: 45.9100 - accuracy: 0.8041 - val_loss: 43.4382 - val_accuracy: 0.7391
Epoch 64/100
7/7 [==============================] - 0s 7ms/step - loss: 46.9672 - accuracy: 0.7822 - val_loss: 46.8175 - val_accuracy: 0.8152
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 48.2965 - accuracy: 0.7616 - val_loss: 53.6598 - val_accuracy: 0.8478
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 54.0457 - accuracy: 0.8041 - val_loss: 56.3107 - val_accuracy: 0.7609
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 58.6450 - accuracy: 0.8187 - val_loss: 57.7388 - val_accuracy: 0.8261
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 63.2464 - accuracy: 0.7762 - val_loss: 67.1332 - val_accuracy: 0.7935
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 58.6685 - accuracy: 0.7822 - val_loss: 63.1765 - val_accuracy: 0.8370
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 65.4464 - accuracy: 0.8151 - val_loss: 76.5724 - val_accuracy: 0.6957
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 68.1501 - accuracy: 0.8017 - val_loss: 73.0920 - val_accuracy: 0.7826
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 68.6200 - accuracy: 0.7676 - val_loss: 73.7643 - val_accuracy: 0.7826
Epoch 73/100
7/7 [==============================] - 0s 7ms/step - loss: 70.7811 - accuracy: 0.7944 - val_loss: 67.4434 - val_accuracy: 0.8152
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 68.8729 - accuracy: 0.8066 - val_loss: 69.9700 - val_accuracy: 0.8370
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 77.3280 - accuracy: 0.8005 - val_loss: 80.1354 - val_accuracy: 0.7935
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 81.2310 - accuracy: 0.7749 - val_loss: 95.6869 - val_accuracy: 0.6739
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 87.9730 - accuracy: 0.7603 - val_loss: 97.5495 - val_accuracy: 0.8152
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 87.6725 - accuracy: 0.8041 - val_loss: 86.4382 - val_accuracy: 0.7717
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 94.2623 - accuracy: 0.7737 - val_loss: 87.6098 - val_accuracy: 0.6957
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 101.0476 - accuracy: 0.7640 - val_loss: 136.6986 - val_accuracy: 0.7935
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 104.5872 - accuracy: 0.7786 - val_loss: 144.6342 - val_accuracy: 0.6196
Epoch 82/100
7/7 [==============================] - 0s 9ms/step - loss: 105.3610 - accuracy: 0.7409 - val_loss: 121.5592 - val_accuracy: 0.8043
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 105.4679 - accuracy: 0.7798 - val_loss: 87.8721 - val_accuracy: 0.8152
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 99.7946 - accuracy: 0.7749 - val_loss: 115.3835 - val_accuracy: 0.8152
Epoch 85/100
7/7 [==============================] - 0s 5ms/step - loss: 118.0707 - accuracy: 0.8321 - val_loss: 103.7168 - val_accuracy: 0.8152
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 147.4505 - accuracy: 0.7530 - val_loss: 225.4074 - val_accuracy: 0.8370
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 157.8909 - accuracy: 0.7932 - val_loss: 125.8481 - val_accuracy: 0.8478
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 140.4422 - accuracy: 0.7798 - val_loss: 138.2188 - val_accuracy: 0.7717
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 133.0881 - accuracy: 0.7895 - val_loss: 179.3456 - val_accuracy: 0.8587
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 170.8276 - accuracy: 0.8041 - val_loss: 206.9803 - val_accuracy: 0.7826
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 169.9089 - accuracy: 0.7664 - val_loss: 224.4439 - val_accuracy: 0.7935
Epoch 92/100
7/7 [==============================] - 0s 9ms/step - loss: 192.9664 - accuracy: 0.7397 - val_loss: 199.3564 - val_accuracy: 0.7391
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 201.3849 - accuracy: 0.7579 - val_loss: 276.5490 - val_accuracy: 0.8152
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 238.6022 - accuracy: 0.7579 - val_loss: 361.9721 - val_accuracy: 0.8152
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 270.6246 - accuracy: 0.7993 - val_loss: 317.9421 - val_accuracy: 0.7283
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 246.2769 - accuracy: 0.8102 - val_loss: 230.4575 - val_accuracy: 0.8696
Epoch 97/100
7/7 [==============================] - 0s 5ms/step - loss: 264.4294 - accuracy: 0.7421 - val_loss: 278.6697 - val_accuracy: 0.8043
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 285.1354 - accuracy: 0.7956 - val_loss: 355.6518 - val_accuracy: 0.8043
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 284.8032 - accuracy: 0.8078 - val_loss: 350.7054 - val_accuracy: 0.8370
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 282.8549 - accuracy: 0.7956 - val_loss: 282.1135 - val_accuracy: 0.8261
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (822, 11)
y_current_train shape: (822, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 4.2134 - accuracy: 0.5815 - val_loss: 2.0185 - val_accuracy: 0.8587
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7928 - accuracy: 0.8467 - val_loss: 3.9925 - val_accuracy: 0.8587
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 4.3015 - accuracy: 0.7847 - val_loss: 3.7332 - val_accuracy: 0.8587
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 3.3598 - accuracy: 0.8029 - val_loss: 3.2202 - val_accuracy: 0.8587
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6397 - accuracy: 0.7908 - val_loss: 4.1358 - val_accuracy: 0.8587
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 4.0963 - accuracy: 0.8041 - val_loss: 3.6072 - val_accuracy: 0.8587
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 3.8927 - accuracy: 0.7835 - val_loss: 3.2884 - val_accuracy: 0.8587
Epoch 8/100
7/7 [==============================] - 0s 9ms/step - loss: 4.3388 - accuracy: 0.8090 - val_loss: 3.7746 - val_accuracy: 0.8913
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 5.1322 - accuracy: 0.7737 - val_loss: 3.5437 - val_accuracy: 0.8913
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 5.8231 - accuracy: 0.8491 - val_loss: 4.0296 - val_accuracy: 0.8804
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 5.6421 - accuracy: 0.7445 - val_loss: 4.5277 - val_accuracy: 0.9348
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 6.2042 - accuracy: 0.8406 - val_loss: 6.2848 - val_accuracy: 0.8152
Epoch 13/100
7/7 [==============================] - 0s 9ms/step - loss: 6.5466 - accuracy: 0.7859 - val_loss: 7.4912 - val_accuracy: 0.6413
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 6.2590 - accuracy: 0.8005 - val_loss: 5.3502 - val_accuracy: 0.8804
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 6.3529 - accuracy: 0.8175 - val_loss: 5.8788 - val_accuracy: 0.8261
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 6.9770 - accuracy: 0.7518 - val_loss: 6.2624 - val_accuracy: 0.8804
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 7.2410 - accuracy: 0.8151 - val_loss: 7.6298 - val_accuracy: 0.8587
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 7.7153 - accuracy: 0.8151 - val_loss: 6.3232 - val_accuracy: 0.8587
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 7.5669 - accuracy: 0.7652 - val_loss: 8.0242 - val_accuracy: 0.8587
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 8.2426 - accuracy: 0.7725 - val_loss: 12.2823 - val_accuracy: 0.6304
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 9.8660 - accuracy: 0.7859 - val_loss: 22.2932 - val_accuracy: 0.3696
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 10.2958 - accuracy: 0.7324 - val_loss: 32.6405 - val_accuracy: 0.5870
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 17.3798 - accuracy: 0.8163 - val_loss: 80.1207 - val_accuracy: 0.5652
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 17.5034 - accuracy: 0.7299 - val_loss: 13.4830 - val_accuracy: 0.8152
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 17.0478 - accuracy: 0.7920 - val_loss: 14.5299 - val_accuracy: 0.8696
Epoch 26/100
7/7 [==============================] - 0s 5ms/step - loss: 16.6123 - accuracy: 0.7883 - val_loss: 13.0997 - val_accuracy: 0.9239
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 18.6918 - accuracy: 0.7822 - val_loss: 16.6016 - val_accuracy: 0.8696
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 22.0495 - accuracy: 0.7847 - val_loss: 16.8242 - val_accuracy: 0.8370
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 23.4311 - accuracy: 0.7543 - val_loss: 18.8524 - val_accuracy: 0.8478
Epoch 30/100
7/7 [==============================] - 0s 9ms/step - loss: 23.8196 - accuracy: 0.7798 - val_loss: 20.0203 - val_accuracy: 0.8696
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 24.5312 - accuracy: 0.7409 - val_loss: 28.6090 - val_accuracy: 0.8261
Epoch 32/100
7/7 [==============================] - 0s 10ms/step - loss: 28.6934 - accuracy: 0.7482 - val_loss: 44.0649 - val_accuracy: 0.7391
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 27.8205 - accuracy: 0.7421 - val_loss: 24.5458 - val_accuracy: 0.8587
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 28.4544 - accuracy: 0.7968 - val_loss: 25.7844 - val_accuracy: 0.9022
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 34.6579 - accuracy: 0.7445 - val_loss: 31.1691 - val_accuracy: 0.8913
Epoch 36/100
7/7 [==============================] - 0s 10ms/step - loss: 36.3150 - accuracy: 0.7494 - val_loss: 49.2291 - val_accuracy: 0.7391
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 39.5658 - accuracy: 0.7981 - val_loss: 37.5601 - val_accuracy: 0.8152
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 44.3084 - accuracy: 0.7616 - val_loss: 41.6801 - val_accuracy: 0.8587
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 47.7672 - accuracy: 0.8005 - val_loss: 41.0624 - val_accuracy: 0.8478
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 49.1336 - accuracy: 0.7774 - val_loss: 43.1188 - val_accuracy: 0.7826
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 51.4122 - accuracy: 0.7445 - val_loss: 45.8853 - val_accuracy: 0.7935
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 53.3388 - accuracy: 0.7762 - val_loss: 46.3063 - val_accuracy: 0.8804
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 56.9278 - accuracy: 0.8017 - val_loss: 58.6465 - val_accuracy: 0.7717
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 60.4846 - accuracy: 0.8029 - val_loss: 53.5724 - val_accuracy: 0.7609
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 61.0645 - accuracy: 0.7275 - val_loss: 58.4303 - val_accuracy: 0.8478
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 69.0559 - accuracy: 0.7299 - val_loss: 55.4133 - val_accuracy: 0.8261
Epoch 47/100
7/7 [==============================] - 0s 7ms/step - loss: 69.8208 - accuracy: 0.8248 - val_loss: 65.7128 - val_accuracy: 0.7826
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 78.9446 - accuracy: 0.7409 - val_loss: 84.1815 - val_accuracy: 0.8587
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 90.1862 - accuracy: 0.7981 - val_loss: 81.3471 - val_accuracy: 0.8152
Epoch 50/100
7/7 [==============================] - 0s 10ms/step - loss: 89.0972 - accuracy: 0.7384 - val_loss: 76.3346 - val_accuracy: 0.8696
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 90.4036 - accuracy: 0.7944 - val_loss: 113.4215 - val_accuracy: 0.4674
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 93.4248 - accuracy: 0.7494 - val_loss: 109.0947 - val_accuracy: 0.5761
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 99.4545 - accuracy: 0.7579 - val_loss: 108.7430 - val_accuracy: 0.8152
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 112.4330 - accuracy: 0.8127 - val_loss: 113.0340 - val_accuracy: 0.8587
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 119.4267 - accuracy: 0.7579 - val_loss: 99.6877 - val_accuracy: 0.8913
Epoch 56/100
7/7 [==============================] - 0s 10ms/step - loss: 115.0543 - accuracy: 0.7567 - val_loss: 113.5516 - val_accuracy: 0.5326
Epoch 57/100
7/7 [==============================] - 0s 7ms/step - loss: 121.8742 - accuracy: 0.7847 - val_loss: 134.5035 - val_accuracy: 0.6196
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 129.1380 - accuracy: 0.7847 - val_loss: 155.9402 - val_accuracy: 0.4457
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 123.7742 - accuracy: 0.7579 - val_loss: 105.0271 - val_accuracy: 0.7826
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 156.1293 - accuracy: 0.8102 - val_loss: 96.2700 - val_accuracy: 0.8261
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 153.2812 - accuracy: 0.7251 - val_loss: 89.0399 - val_accuracy: 0.8804
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 139.6803 - accuracy: 0.8285 - val_loss: 127.1962 - val_accuracy: 0.7500
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 127.0218 - accuracy: 0.7470 - val_loss: 107.1943 - val_accuracy: 0.8696
Epoch 64/100
7/7 [==============================] - 0s 6ms/step - loss: 145.2788 - accuracy: 0.8005 - val_loss: 113.4416 - val_accuracy: 0.8696
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 159.3504 - accuracy: 0.7287 - val_loss: 117.1338 - val_accuracy: 0.8587
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 166.1620 - accuracy: 0.7567 - val_loss: 173.6597 - val_accuracy: 0.8587
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 179.2662 - accuracy: 0.7530 - val_loss: 130.9698 - val_accuracy: 0.8587
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 204.6026 - accuracy: 0.8041 - val_loss: 339.0461 - val_accuracy: 0.6413
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 285.0587 - accuracy: 0.7968 - val_loss: 182.2046 - val_accuracy: 0.8043
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 253.4679 - accuracy: 0.7372 - val_loss: 340.3835 - val_accuracy: 0.6630
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 245.3646 - accuracy: 0.8175 - val_loss: 250.0205 - val_accuracy: 0.8587
Epoch 72/100
7/7 [==============================] - 0s 5ms/step - loss: 265.3651 - accuracy: 0.7822 - val_loss: 199.3641 - val_accuracy: 0.8696
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 257.5454 - accuracy: 0.8041 - val_loss: 245.8625 - val_accuracy: 0.8587
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 258.1764 - accuracy: 0.7397 - val_loss: 197.9110 - val_accuracy: 0.8696
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 327.1278 - accuracy: 0.7409 - val_loss: 240.5243 - val_accuracy: 0.8478
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 328.5653 - accuracy: 0.7847 - val_loss: 260.1900 - val_accuracy: 0.8152
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 346.8742 - accuracy: 0.7591 - val_loss: 306.7932 - val_accuracy: 0.7935
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 365.2713 - accuracy: 0.7494 - val_loss: 317.6867 - val_accuracy: 0.8696
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 377.4612 - accuracy: 0.7311 - val_loss: 298.8756 - val_accuracy: 0.9022
Epoch 80/100
7/7 [==============================] - 0s 6ms/step - loss: 419.3317 - accuracy: 0.7263 - val_loss: 402.7841 - val_accuracy: 0.8587
Epoch 81/100
7/7 [==============================] - 0s 13ms/step - loss: 532.2483 - accuracy: 0.8163 - val_loss: 310.5208 - val_accuracy: 0.8913
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 626.9560 - accuracy: 0.7117 - val_loss: 679.4771 - val_accuracy: 0.8587
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 776.9224 - accuracy: 0.8455 - val_loss: 435.6418 - val_accuracy: 0.7609
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 637.5098 - accuracy: 0.6533 - val_loss: 555.9936 - val_accuracy: 0.8152
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 732.9349 - accuracy: 0.8041 - val_loss: 1101.3950 - val_accuracy: 0.6522
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 879.1678 - accuracy: 0.7019 - val_loss: 796.5068 - val_accuracy: 0.7935
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 873.0910 - accuracy: 0.8090 - val_loss: 1254.8812 - val_accuracy: 0.7717
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 641.1455 - accuracy: 0.7713 - val_loss: 661.6364 - val_accuracy: 0.8043
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 744.4444 - accuracy: 0.7360 - val_loss: 526.8100 - val_accuracy: 0.6413
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 672.6328 - accuracy: 0.7299 - val_loss: 941.5219 - val_accuracy: 0.6630
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 796.7757 - accuracy: 0.7579 - val_loss: 1496.3118 - val_accuracy: 0.5761
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 1773.9739 - accuracy: 0.7238 - val_loss: 1090.8044 - val_accuracy: 0.8478
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 1807.3455 - accuracy: 0.6825 - val_loss: 2453.1653 - val_accuracy: 0.8478
Epoch 94/100
7/7 [==============================] - 0s 10ms/step - loss: 2782.5469 - accuracy: 0.7993 - val_loss: 4586.9233 - val_accuracy: 0.6848
Epoch 95/100
7/7 [==============================] - 0s 6ms/step - loss: 2243.5884 - accuracy: 0.8017 - val_loss: 1417.9072 - val_accuracy: 0.8478
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 2369.1465 - accuracy: 0.7409 - val_loss: 2188.2410 - val_accuracy: 0.7065
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 2161.8850 - accuracy: 0.8139 - val_loss: 1888.1227 - val_accuracy: 0.8587
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 2339.2087 - accuracy: 0.7105 - val_loss: 1763.6832 - val_accuracy: 0.8587
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 2785.4160 - accuracy: 0.8358 - val_loss: 4518.4888 - val_accuracy: 0.7391
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 3645.3552 - accuracy: 0.7397 - val_loss: 1549.9319 - val_accuracy: 0.9022
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 4.5340 - accuracy: 0.5541 - val_loss: 2.1326 - val_accuracy: 0.8352
Epoch 2/100
7/7 [==============================] - 0s 9ms/step - loss: 3.0610 - accuracy: 0.8311 - val_loss: 4.4853 - val_accuracy: 0.8352
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 4.3693 - accuracy: 0.8092 - val_loss: 3.9291 - val_accuracy: 0.8352
Epoch 4/100
7/7 [==============================] - 0s 7ms/step - loss: 3.5210 - accuracy: 0.8007 - val_loss: 3.5235 - val_accuracy: 0.8352
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 4.0133 - accuracy: 0.7910 - val_loss: 4.1695 - val_accuracy: 0.8352
Epoch 6/100
7/7 [==============================] - 0s 9ms/step - loss: 4.5564 - accuracy: 0.7922 - val_loss: 3.7317 - val_accuracy: 0.8791
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 4.3027 - accuracy: 0.7971 - val_loss: 4.0338 - val_accuracy: 0.8462
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 4.6786 - accuracy: 0.8032 - val_loss: 5.2900 - val_accuracy: 0.8352
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 4.6962 - accuracy: 0.8165 - val_loss: 5.5023 - val_accuracy: 0.8352
Epoch 10/100
7/7 [==============================] - 0s 7ms/step - loss: 5.1220 - accuracy: 0.7776 - val_loss: 5.4228 - val_accuracy: 0.8352
Epoch 11/100
7/7 [==============================] - 0s 5ms/step - loss: 5.5640 - accuracy: 0.8117 - val_loss: 5.4602 - val_accuracy: 0.8352
Epoch 12/100
7/7 [==============================] - 0s 11ms/step - loss: 5.4949 - accuracy: 0.8044 - val_loss: 5.8279 - val_accuracy: 0.8352
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 5.4539 - accuracy: 0.8153 - val_loss: 6.2435 - val_accuracy: 0.8242
Epoch 14/100
7/7 [==============================] - 0s 7ms/step - loss: 6.2217 - accuracy: 0.8311 - val_loss: 6.7019 - val_accuracy: 0.8462
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 6.8515 - accuracy: 0.8153 - val_loss: 5.7601 - val_accuracy: 0.8791
Epoch 16/100
7/7 [==============================] - 0s 5ms/step - loss: 6.7071 - accuracy: 0.7801 - val_loss: 5.6386 - val_accuracy: 0.8352
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 6.6382 - accuracy: 0.7801 - val_loss: 10.2002 - val_accuracy: 0.7033
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 7.6295 - accuracy: 0.7740 - val_loss: 6.7352 - val_accuracy: 0.8352
Epoch 19/100
7/7 [==============================] - 0s 9ms/step - loss: 8.3510 - accuracy: 0.7655 - val_loss: 7.2344 - val_accuracy: 0.8242
Epoch 20/100
7/7 [==============================] - 0s 10ms/step - loss: 8.4178 - accuracy: 0.7606 - val_loss: 7.9364 - val_accuracy: 0.8352
Epoch 21/100
7/7 [==============================] - 0s 10ms/step - loss: 8.1871 - accuracy: 0.7752 - val_loss: 7.3111 - val_accuracy: 0.8352
Epoch 22/100
7/7 [==============================] - 0s 10ms/step - loss: 8.0058 - accuracy: 0.8153 - val_loss: 8.0230 - val_accuracy: 0.8681
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 8.6604 - accuracy: 0.7849 - val_loss: 8.9134 - val_accuracy: 0.8242
Epoch 24/100
7/7 [==============================] - 0s 12ms/step - loss: 8.5645 - accuracy: 0.7886 - val_loss: 10.6465 - val_accuracy: 0.8352
Epoch 25/100
7/7 [==============================] - 0s 10ms/step - loss: 9.7230 - accuracy: 0.7558 - val_loss: 9.1703 - val_accuracy: 0.8132
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 9.7280 - accuracy: 0.8117 - val_loss: 9.7190 - val_accuracy: 0.7143
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 10.0412 - accuracy: 0.8056 - val_loss: 13.9611 - val_accuracy: 0.5055
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 10.6570 - accuracy: 0.7400 - val_loss: 8.9139 - val_accuracy: 0.8242
Epoch 29/100
7/7 [==============================] - 0s 11ms/step - loss: 9.9828 - accuracy: 0.7570 - val_loss: 8.6187 - val_accuracy: 0.8791
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 9.9585 - accuracy: 0.7983 - val_loss: 9.7086 - val_accuracy: 0.8242
Epoch 31/100
7/7 [==============================] - 0s 9ms/step - loss: 10.8016 - accuracy: 0.7436 - val_loss: 10.1915 - val_accuracy: 0.8352
Epoch 32/100
7/7 [==============================] - 0s 11ms/step - loss: 12.1589 - accuracy: 0.7582 - val_loss: 11.9591 - val_accuracy: 0.8352
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 12.5411 - accuracy: 0.7704 - val_loss: 11.4682 - val_accuracy: 0.6923
Epoch 34/100
7/7 [==============================] - 0s 10ms/step - loss: 13.0333 - accuracy: 0.7801 - val_loss: 12.2201 - val_accuracy: 0.8571
Epoch 35/100
7/7 [==============================] - 0s 9ms/step - loss: 12.4437 - accuracy: 0.7813 - val_loss: 11.2243 - val_accuracy: 0.8901
Epoch 36/100
7/7 [==============================] - 0s 9ms/step - loss: 13.1313 - accuracy: 0.7594 - val_loss: 11.4790 - val_accuracy: 0.8901
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 13.9817 - accuracy: 0.7971 - val_loss: 12.6693 - val_accuracy: 0.8791
Epoch 38/100
7/7 [==============================] - 0s 7ms/step - loss: 14.7435 - accuracy: 0.7740 - val_loss: 15.2309 - val_accuracy: 0.7253
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 15.0228 - accuracy: 0.8068 - val_loss: 13.7022 - val_accuracy: 0.8462
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 15.5336 - accuracy: 0.7412 - val_loss: 18.0955 - val_accuracy: 0.8352
Epoch 41/100
7/7 [==============================] - 0s 7ms/step - loss: 16.0825 - accuracy: 0.7594 - val_loss: 18.4402 - val_accuracy: 0.8352
Epoch 42/100
7/7 [==============================] - 0s 7ms/step - loss: 18.9185 - accuracy: 0.8117 - val_loss: 26.1758 - val_accuracy: 0.4286
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 16.7091 - accuracy: 0.7740 - val_loss: 14.5496 - val_accuracy: 0.8681
Epoch 44/100
7/7 [==============================] - 0s 7ms/step - loss: 16.5847 - accuracy: 0.8177 - val_loss: 16.4415 - val_accuracy: 0.7143
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 16.9897 - accuracy: 0.7776 - val_loss: 20.7456 - val_accuracy: 0.8352
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 19.5919 - accuracy: 0.7874 - val_loss: 17.5753 - val_accuracy: 0.8462
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 20.2986 - accuracy: 0.7704 - val_loss: 19.9851 - val_accuracy: 0.6923
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 21.8037 - accuracy: 0.7375 - val_loss: 21.2795 - val_accuracy: 0.8352
Epoch 49/100
7/7 [==============================] - 0s 7ms/step - loss: 25.2543 - accuracy: 0.8408 - val_loss: 18.8255 - val_accuracy: 0.8462
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 24.0607 - accuracy: 0.7898 - val_loss: 21.4226 - val_accuracy: 0.8462
Epoch 51/100
7/7 [==============================] - 0s 10ms/step - loss: 20.7767 - accuracy: 0.8153 - val_loss: 19.0516 - val_accuracy: 0.7802
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 23.0588 - accuracy: 0.7606 - val_loss: 25.1945 - val_accuracy: 0.4286
Epoch 53/100
7/7 [==============================] - 0s 10ms/step - loss: 23.8096 - accuracy: 0.8129 - val_loss: 44.8635 - val_accuracy: 0.2747
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 24.4460 - accuracy: 0.7801 - val_loss: 45.5664 - val_accuracy: 0.3297
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 29.0453 - accuracy: 0.7509 - val_loss: 23.1543 - val_accuracy: 0.6264
Epoch 56/100
7/7 [==============================] - 0s 6ms/step - loss: 29.7732 - accuracy: 0.7825 - val_loss: 25.6004 - val_accuracy: 0.7582
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 30.8989 - accuracy: 0.7728 - val_loss: 39.4868 - val_accuracy: 0.5165
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 40.9631 - accuracy: 0.7825 - val_loss: 41.9801 - val_accuracy: 0.8022
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 46.5179 - accuracy: 0.7691 - val_loss: 45.8925 - val_accuracy: 0.8022
Epoch 60/100
7/7 [==============================] - 0s 7ms/step - loss: 47.0382 - accuracy: 0.7303 - val_loss: 50.5997 - val_accuracy: 0.8352
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 52.3812 - accuracy: 0.8469 - val_loss: 44.5326 - val_accuracy: 0.7912
Epoch 62/100
7/7 [==============================] - 0s 7ms/step - loss: 55.3105 - accuracy: 0.7120 - val_loss: 54.2755 - val_accuracy: 0.8352
Epoch 63/100
7/7 [==============================] - 0s 7ms/step - loss: 53.9139 - accuracy: 0.8141 - val_loss: 47.0104 - val_accuracy: 0.8901
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 56.8736 - accuracy: 0.7339 - val_loss: 50.1901 - val_accuracy: 0.7802
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 55.7932 - accuracy: 0.7740 - val_loss: 51.3533 - val_accuracy: 0.8132
Epoch 66/100
7/7 [==============================] - 0s 6ms/step - loss: 59.1595 - accuracy: 0.7789 - val_loss: 58.2803 - val_accuracy: 0.8242
Epoch 67/100
7/7 [==============================] - 0s 7ms/step - loss: 65.2320 - accuracy: 0.8056 - val_loss: 60.7592 - val_accuracy: 0.7033
Epoch 68/100
7/7 [==============================] - 0s 7ms/step - loss: 65.1881 - accuracy: 0.8408 - val_loss: 66.0032 - val_accuracy: 0.6923
Epoch 69/100
7/7 [==============================] - 0s 9ms/step - loss: 59.1698 - accuracy: 0.7655 - val_loss: 51.9664 - val_accuracy: 0.8242
Epoch 70/100
7/7 [==============================] - 0s 5ms/step - loss: 58.7355 - accuracy: 0.7570 - val_loss: 51.0539 - val_accuracy: 0.8901
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 62.4543 - accuracy: 0.8384 - val_loss: 61.5072 - val_accuracy: 0.7802
Epoch 72/100
7/7 [==============================] - 0s 7ms/step - loss: 60.3568 - accuracy: 0.7582 - val_loss: 65.5889 - val_accuracy: 0.7033
Epoch 73/100
7/7 [==============================] - 0s 6ms/step - loss: 65.9298 - accuracy: 0.8177 - val_loss: 64.2729 - val_accuracy: 0.7363
Epoch 74/100
7/7 [==============================] - 0s 7ms/step - loss: 63.7130 - accuracy: 0.8226 - val_loss: 50.7753 - val_accuracy: 0.8571
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 62.8728 - accuracy: 0.7631 - val_loss: 57.1702 - val_accuracy: 0.8462
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 64.1996 - accuracy: 0.7910 - val_loss: 54.3512 - val_accuracy: 0.8132
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 65.6392 - accuracy: 0.7947 - val_loss: 66.6552 - val_accuracy: 0.8462
Epoch 78/100
7/7 [==============================] - 0s 6ms/step - loss: 64.7639 - accuracy: 0.7643 - val_loss: 50.5619 - val_accuracy: 0.8352
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 60.0666 - accuracy: 0.7801 - val_loss: 66.2704 - val_accuracy: 0.7143
Epoch 80/100
7/7 [==============================] - 0s 9ms/step - loss: 60.6197 - accuracy: 0.7509 - val_loss: 46.7110 - val_accuracy: 0.8242
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 59.5667 - accuracy: 0.8044 - val_loss: 57.7814 - val_accuracy: 0.8352
Epoch 82/100
7/7 [==============================] - 0s 6ms/step - loss: 68.9143 - accuracy: 0.7789 - val_loss: 70.4289 - val_accuracy: 0.7692
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 75.3618 - accuracy: 0.7254 - val_loss: 75.9598 - val_accuracy: 0.8352
Epoch 84/100
7/7 [==============================] - 0s 9ms/step - loss: 128.3506 - accuracy: 0.7740 - val_loss: 94.8503 - val_accuracy: 0.8352
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 104.5872 - accuracy: 0.8177 - val_loss: 92.0723 - val_accuracy: 0.8462
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 95.1696 - accuracy: 0.7898 - val_loss: 124.4435 - val_accuracy: 0.8352
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 119.1762 - accuracy: 0.7618 - val_loss: 91.5652 - val_accuracy: 0.8352
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 98.7311 - accuracy: 0.8214 - val_loss: 92.4358 - val_accuracy: 0.8022
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 105.3116 - accuracy: 0.6999 - val_loss: 79.7625 - val_accuracy: 0.8901
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 107.0579 - accuracy: 0.8493 - val_loss: 112.0602 - val_accuracy: 0.8242
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 123.0770 - accuracy: 0.7388 - val_loss: 163.9005 - val_accuracy: 0.8242
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 134.8784 - accuracy: 0.7752 - val_loss: 129.8264 - val_accuracy: 0.7692
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 123.8808 - accuracy: 0.7874 - val_loss: 111.8544 - val_accuracy: 0.7802
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 121.5364 - accuracy: 0.7521 - val_loss: 90.1147 - val_accuracy: 0.8791
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 119.8913 - accuracy: 0.8141 - val_loss: 83.8648 - val_accuracy: 0.8242
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 134.3174 - accuracy: 0.7594 - val_loss: 94.3152 - val_accuracy: 0.8242
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 119.4344 - accuracy: 0.7813 - val_loss: 107.4841 - val_accuracy: 0.7582
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 133.8441 - accuracy: 0.8044 - val_loss: 159.7125 - val_accuracy: 0.7473
Epoch 99/100
7/7 [==============================] - 0s 7ms/step - loss: 159.8992 - accuracy: 0.7716 - val_loss: 167.3852 - val_accuracy: 0.7363
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 161.2159 - accuracy: 0.7679 - val_loss: 144.6156 - val_accuracy: 0.8352
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 4.3364 - accuracy: 0.6002 - val_loss: 2.0313 - val_accuracy: 0.8681
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 2.8848 - accuracy: 0.8408 - val_loss: 4.0608 - val_accuracy: 0.8681
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 4.0469 - accuracy: 0.8275 - val_loss: 3.3994 - val_accuracy: 0.8681
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 3.4755 - accuracy: 0.7874 - val_loss: 3.1333 - val_accuracy: 0.8571
Epoch 5/100
7/7 [==============================] - 0s 7ms/step - loss: 4.0292 - accuracy: 0.7874 - val_loss: 4.3248 - val_accuracy: 0.8681
Epoch 6/100
7/7 [==============================] - 0s 7ms/step - loss: 4.4726 - accuracy: 0.7861 - val_loss: 4.8190 - val_accuracy: 0.8681
Epoch 7/100
7/7 [==============================] - 0s 10ms/step - loss: 4.8177 - accuracy: 0.7716 - val_loss: 5.5077 - val_accuracy: 0.8681
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 5.0328 - accuracy: 0.7776 - val_loss: 5.6202 - val_accuracy: 0.8681
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 5.6055 - accuracy: 0.8153 - val_loss: 5.5478 - val_accuracy: 0.8462
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 5.8242 - accuracy: 0.8056 - val_loss: 6.1798 - val_accuracy: 0.8462
Epoch 11/100
7/7 [==============================] - 0s 7ms/step - loss: 6.2244 - accuracy: 0.7813 - val_loss: 7.2140 - val_accuracy: 0.8681
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 6.6868 - accuracy: 0.8457 - val_loss: 6.5448 - val_accuracy: 0.8462
Epoch 13/100
7/7 [==============================] - 0s 10ms/step - loss: 7.0348 - accuracy: 0.8032 - val_loss: 9.4090 - val_accuracy: 0.8681
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 8.3123 - accuracy: 0.7740 - val_loss: 11.0791 - val_accuracy: 0.8462
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 8.5379 - accuracy: 0.8019 - val_loss: 8.7451 - val_accuracy: 0.7363
Epoch 16/100
7/7 [==============================] - 0s 7ms/step - loss: 8.3472 - accuracy: 0.8165 - val_loss: 8.0429 - val_accuracy: 0.7802
Epoch 17/100
7/7 [==============================] - 0s 7ms/step - loss: 9.6498 - accuracy: 0.7716 - val_loss: 12.5169 - val_accuracy: 0.8681
Epoch 18/100
7/7 [==============================] - 0s 15ms/step - loss: 9.8637 - accuracy: 0.8044 - val_loss: 14.0286 - val_accuracy: 0.8681
Epoch 19/100
7/7 [==============================] - 0s 10ms/step - loss: 10.1911 - accuracy: 0.7825 - val_loss: 11.1006 - val_accuracy: 0.8681
Epoch 20/100
7/7 [==============================] - 0s 9ms/step - loss: 10.5806 - accuracy: 0.8287 - val_loss: 11.5286 - val_accuracy: 0.6593
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 11.1456 - accuracy: 0.7424 - val_loss: 10.5005 - val_accuracy: 0.8681
Epoch 22/100
7/7 [==============================] - 0s 9ms/step - loss: 11.8763 - accuracy: 0.8141 - val_loss: 11.0630 - val_accuracy: 0.8022
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 11.3322 - accuracy: 0.7400 - val_loss: 11.8910 - val_accuracy: 0.8681
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 12.0804 - accuracy: 0.7704 - val_loss: 13.0042 - val_accuracy: 0.7143
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 12.0873 - accuracy: 0.8226 - val_loss: 15.2503 - val_accuracy: 0.8681
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 12.9590 - accuracy: 0.7655 - val_loss: 13.2023 - val_accuracy: 0.7582
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 13.5258 - accuracy: 0.7947 - val_loss: 19.9797 - val_accuracy: 0.3956
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 13.5203 - accuracy: 0.7594 - val_loss: 55.0866 - val_accuracy: 0.1319
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 14.7616 - accuracy: 0.7801 - val_loss: 24.7868 - val_accuracy: 0.4066
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 14.0559 - accuracy: 0.8190 - val_loss: 15.2318 - val_accuracy: 0.8571
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 15.6656 - accuracy: 0.7509 - val_loss: 17.3149 - val_accuracy: 0.5275
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 15.4708 - accuracy: 0.7764 - val_loss: 18.1329 - val_accuracy: 0.3077
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 15.0839 - accuracy: 0.7861 - val_loss: 21.1573 - val_accuracy: 0.2527
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 14.9773 - accuracy: 0.7254 - val_loss: 14.7432 - val_accuracy: 0.8022
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 17.0843 - accuracy: 0.8007 - val_loss: 16.1515 - val_accuracy: 0.8571
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 16.5439 - accuracy: 0.7825 - val_loss: 16.7145 - val_accuracy: 0.7692
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 18.9215 - accuracy: 0.7546 - val_loss: 21.4230 - val_accuracy: 0.7582
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 21.0808 - accuracy: 0.8360 - val_loss: 22.0442 - val_accuracy: 0.7802
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 21.2979 - accuracy: 0.7679 - val_loss: 23.4389 - val_accuracy: 0.8681
Epoch 40/100
7/7 [==============================] - 0s 8ms/step - loss: 20.9867 - accuracy: 0.7728 - val_loss: 17.0948 - val_accuracy: 0.8462
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 20.3172 - accuracy: 0.8032 - val_loss: 19.9710 - val_accuracy: 0.8132
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 21.7794 - accuracy: 0.7594 - val_loss: 21.8288 - val_accuracy: 0.7912
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 26.6988 - accuracy: 0.7448 - val_loss: 32.9498 - val_accuracy: 0.7912
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 38.8522 - accuracy: 0.7448 - val_loss: 45.6837 - val_accuracy: 0.8242
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 51.7815 - accuracy: 0.7618 - val_loss: 70.5412 - val_accuracy: 0.6044
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 63.7095 - accuracy: 0.7886 - val_loss: 76.7263 - val_accuracy: 0.6923
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 69.7416 - accuracy: 0.7801 - val_loss: 84.2572 - val_accuracy: 0.8681
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 82.9696 - accuracy: 0.7764 - val_loss: 87.9293 - val_accuracy: 0.8462
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 93.1794 - accuracy: 0.7886 - val_loss: 98.4463 - val_accuracy: 0.8242
Epoch 50/100
7/7 [==============================] - 0s 7ms/step - loss: 102.5734 - accuracy: 0.7667 - val_loss: 110.8488 - val_accuracy: 0.7912
Epoch 51/100
7/7 [==============================] - 0s 9ms/step - loss: 109.4714 - accuracy: 0.8007 - val_loss: 117.0000 - val_accuracy: 0.8681
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 116.4100 - accuracy: 0.8214 - val_loss: 124.1533 - val_accuracy: 0.7582
Epoch 53/100
7/7 [==============================] - 0s 9ms/step - loss: 123.4120 - accuracy: 0.7400 - val_loss: 116.3362 - val_accuracy: 0.8681
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 122.3366 - accuracy: 0.8056 - val_loss: 131.4615 - val_accuracy: 0.8242
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 127.0725 - accuracy: 0.7351 - val_loss: 131.0433 - val_accuracy: 0.8681
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 131.2094 - accuracy: 0.7947 - val_loss: 135.4950 - val_accuracy: 0.8681
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 129.8912 - accuracy: 0.7764 - val_loss: 138.5351 - val_accuracy: 0.6703
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 133.5601 - accuracy: 0.7570 - val_loss: 154.9521 - val_accuracy: 0.7363
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 124.9488 - accuracy: 0.7728 - val_loss: 125.2001 - val_accuracy: 0.8681
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 113.1323 - accuracy: 0.7667 - val_loss: 115.4080 - val_accuracy: 0.8681
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 109.8610 - accuracy: 0.7995 - val_loss: 112.4125 - val_accuracy: 0.8681
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 108.5454 - accuracy: 0.7740 - val_loss: 96.1844 - val_accuracy: 0.8242
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 101.3140 - accuracy: 0.8323 - val_loss: 101.2197 - val_accuracy: 0.7363
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 92.4542 - accuracy: 0.7874 - val_loss: 115.3448 - val_accuracy: 0.4066
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 89.6764 - accuracy: 0.7655 - val_loss: 77.3985 - val_accuracy: 0.8352
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 76.7875 - accuracy: 0.7631 - val_loss: 89.8197 - val_accuracy: 0.8681
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 73.3878 - accuracy: 0.7242 - val_loss: 76.1189 - val_accuracy: 0.8681
Epoch 68/100
7/7 [==============================] - 0s 10ms/step - loss: 67.6666 - accuracy: 0.8177 - val_loss: 75.4684 - val_accuracy: 0.8681
Epoch 69/100
7/7 [==============================] - 0s 7ms/step - loss: 76.2322 - accuracy: 0.7327 - val_loss: 63.0266 - val_accuracy: 0.8462
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 82.5073 - accuracy: 0.8262 - val_loss: 100.8698 - val_accuracy: 0.8022
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 96.0669 - accuracy: 0.8117 - val_loss: 85.5720 - val_accuracy: 0.8681
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 103.5257 - accuracy: 0.7448 - val_loss: 106.1549 - val_accuracy: 0.8462
Epoch 73/100
7/7 [==============================] - 0s 7ms/step - loss: 121.8273 - accuracy: 0.7910 - val_loss: 122.0631 - val_accuracy: 0.8681
Epoch 74/100
7/7 [==============================] - 0s 7ms/step - loss: 133.2126 - accuracy: 0.7825 - val_loss: 136.8999 - val_accuracy: 0.8352
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 145.9798 - accuracy: 0.8019 - val_loss: 140.6040 - val_accuracy: 0.8571
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 155.7226 - accuracy: 0.7776 - val_loss: 149.9860 - val_accuracy: 0.7802
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 165.9143 - accuracy: 0.7570 - val_loss: 137.9005 - val_accuracy: 0.8681
Epoch 78/100
7/7 [==============================] - 0s 7ms/step - loss: 161.9036 - accuracy: 0.7400 - val_loss: 167.2012 - val_accuracy: 0.8571
Epoch 79/100
7/7 [==============================] - 0s 7ms/step - loss: 174.3388 - accuracy: 0.7934 - val_loss: 189.2740 - val_accuracy: 0.8242
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 173.1580 - accuracy: 0.7947 - val_loss: 194.1977 - val_accuracy: 0.8681
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 187.1154 - accuracy: 0.7533 - val_loss: 254.1328 - val_accuracy: 0.7692
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 206.5535 - accuracy: 0.8007 - val_loss: 412.3472 - val_accuracy: 0.5385
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 251.1729 - accuracy: 0.7813 - val_loss: 288.4288 - val_accuracy: 0.5385
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 238.8121 - accuracy: 0.7558 - val_loss: 451.5894 - val_accuracy: 0.4615
Epoch 85/100
7/7 [==============================] - 0s 9ms/step - loss: 235.9358 - accuracy: 0.7776 - val_loss: 643.4114 - val_accuracy: 0.3516
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 274.2673 - accuracy: 0.7910 - val_loss: 623.0688 - val_accuracy: 0.4396
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 324.9384 - accuracy: 0.6902 - val_loss: 538.9515 - val_accuracy: 0.7692
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 266.1151 - accuracy: 0.7606 - val_loss: 386.6544 - val_accuracy: 0.7253
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 334.1209 - accuracy: 0.7995 - val_loss: 750.9244 - val_accuracy: 0.6154
Epoch 90/100
7/7 [==============================] - 0s 7ms/step - loss: 402.2049 - accuracy: 0.7643 - val_loss: 238.0464 - val_accuracy: 0.8462
Epoch 91/100
7/7 [==============================] - 0s 9ms/step - loss: 414.3116 - accuracy: 0.8068 - val_loss: 258.3107 - val_accuracy: 0.6813
Epoch 92/100
7/7 [==============================] - 0s 7ms/step - loss: 318.1417 - accuracy: 0.7509 - val_loss: 461.6318 - val_accuracy: 0.8022
Epoch 93/100
7/7 [==============================] - 0s 7ms/step - loss: 448.5756 - accuracy: 0.7497 - val_loss: 395.8525 - val_accuracy: 0.8352
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 446.3550 - accuracy: 0.7971 - val_loss: 415.2153 - val_accuracy: 0.8242
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 399.8187 - accuracy: 0.7849 - val_loss: 572.7059 - val_accuracy: 0.7363
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 486.0707 - accuracy: 0.7801 - val_loss: 331.6123 - val_accuracy: 0.8242
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 448.9276 - accuracy: 0.7521 - val_loss: 545.5620 - val_accuracy: 0.8901
Epoch 98/100
7/7 [==============================] - 0s 6ms/step - loss: 648.4460 - accuracy: 0.7934 - val_loss: 1409.3054 - val_accuracy: 0.7363
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 646.7974 - accuracy: 0.8202 - val_loss: 708.3901 - val_accuracy: 0.8681
Epoch 100/100
7/7 [==============================] - 0s 6ms/step - loss: 590.3258 - accuracy: 0.7193 - val_loss: 857.6449 - val_accuracy: 0.8681
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 8ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 41ms/step - loss: 4.2679 - accuracy: 0.6221 - val_loss: 2.1100 - val_accuracy: 0.9011
Epoch 2/100
7/7 [==============================] - 0s 7ms/step - loss: 3.1339 - accuracy: 0.8420 - val_loss: 4.1853 - val_accuracy: 0.8901
Epoch 3/100
7/7 [==============================] - 0s 8ms/step - loss: 4.5884 - accuracy: 0.7266 - val_loss: 3.9155 - val_accuracy: 0.9011
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 3.8254 - accuracy: 0.7388 - val_loss: 3.5224 - val_accuracy: 0.9011
Epoch 5/100
7/7 [==============================] - 0s 7ms/step - loss: 4.2911 - accuracy: 0.7886 - val_loss: 3.9151 - val_accuracy: 0.8681
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 4.6456 - accuracy: 0.8250 - val_loss: 4.3521 - val_accuracy: 0.4396
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 4.5762 - accuracy: 0.7339 - val_loss: 5.0991 - val_accuracy: 0.9011
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 5.5372 - accuracy: 0.8056 - val_loss: 13.7937 - val_accuracy: 0.5824
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 5.9504 - accuracy: 0.8092 - val_loss: 6.4734 - val_accuracy: 0.7143
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 6.8361 - accuracy: 0.7874 - val_loss: 6.1114 - val_accuracy: 0.8242
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 6.8462 - accuracy: 0.7874 - val_loss: 7.1716 - val_accuracy: 0.7033
Epoch 12/100
7/7 [==============================] - 0s 7ms/step - loss: 6.6332 - accuracy: 0.8153 - val_loss: 5.9219 - val_accuracy: 0.9011
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 6.9968 - accuracy: 0.7728 - val_loss: 7.1355 - val_accuracy: 0.8791
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 7.6520 - accuracy: 0.8068 - val_loss: 7.7269 - val_accuracy: 0.9011
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 7.6381 - accuracy: 0.8117 - val_loss: 7.5026 - val_accuracy: 0.9011
Epoch 16/100
7/7 [==============================] - 0s 9ms/step - loss: 8.2553 - accuracy: 0.7898 - val_loss: 7.5780 - val_accuracy: 0.8681
Epoch 17/100
7/7 [==============================] - 0s 9ms/step - loss: 8.8477 - accuracy: 0.8019 - val_loss: 9.1477 - val_accuracy: 0.7143
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 9.2956 - accuracy: 0.8238 - val_loss: 10.9134 - val_accuracy: 0.6044
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 9.9230 - accuracy: 0.8080 - val_loss: 10.7983 - val_accuracy: 0.4505
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 9.5710 - accuracy: 0.7886 - val_loss: 8.8503 - val_accuracy: 0.9121
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 9.0523 - accuracy: 0.7849 - val_loss: 8.8608 - val_accuracy: 0.8791
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 9.2150 - accuracy: 0.7971 - val_loss: 9.2980 - val_accuracy: 0.8901
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 10.2260 - accuracy: 0.7533 - val_loss: 11.0750 - val_accuracy: 0.9011
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 11.0766 - accuracy: 0.7861 - val_loss: 12.4506 - val_accuracy: 0.9011
Epoch 25/100
7/7 [==============================] - 0s 7ms/step - loss: 11.9935 - accuracy: 0.7740 - val_loss: 12.0909 - val_accuracy: 0.8901
Epoch 26/100
7/7 [==============================] - 0s 8ms/step - loss: 13.5181 - accuracy: 0.8007 - val_loss: 13.9690 - val_accuracy: 0.7692
Epoch 27/100
7/7 [==============================] - 0s 9ms/step - loss: 13.8836 - accuracy: 0.7837 - val_loss: 16.0663 - val_accuracy: 0.6593
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 15.9383 - accuracy: 0.7801 - val_loss: 24.8125 - val_accuracy: 0.3077
Epoch 29/100
7/7 [==============================] - 0s 7ms/step - loss: 18.7509 - accuracy: 0.7606 - val_loss: 25.1254 - val_accuracy: 0.2198
Epoch 30/100
7/7 [==============================] - 0s 6ms/step - loss: 20.4513 - accuracy: 0.7473 - val_loss: 19.4044 - val_accuracy: 0.9011
Epoch 31/100
7/7 [==============================] - 0s 7ms/step - loss: 23.4529 - accuracy: 0.7278 - val_loss: 20.4951 - val_accuracy: 0.8791
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 22.7069 - accuracy: 0.7497 - val_loss: 24.0799 - val_accuracy: 0.8901
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 25.0451 - accuracy: 0.7983 - val_loss: 23.5083 - val_accuracy: 0.9011
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 24.5674 - accuracy: 0.7412 - val_loss: 21.3120 - val_accuracy: 0.8132
Epoch 35/100
7/7 [==============================] - 0s 7ms/step - loss: 23.9237 - accuracy: 0.7315 - val_loss: 21.6272 - val_accuracy: 0.4286
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 22.6248 - accuracy: 0.8080 - val_loss: 32.8335 - val_accuracy: 0.0989
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 27.0791 - accuracy: 0.7084 - val_loss: 29.1439 - val_accuracy: 0.7692
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 32.6161 - accuracy: 0.7339 - val_loss: 44.5595 - val_accuracy: 0.6044
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 37.5355 - accuracy: 0.7898 - val_loss: 42.7765 - val_accuracy: 0.6813
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 46.5460 - accuracy: 0.7679 - val_loss: 63.5801 - val_accuracy: 0.7692
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 55.7890 - accuracy: 0.7497 - val_loss: 59.3132 - val_accuracy: 0.8352
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 66.0851 - accuracy: 0.7922 - val_loss: 73.5151 - val_accuracy: 0.7582
Epoch 43/100
7/7 [==============================] - 0s 7ms/step - loss: 71.4809 - accuracy: 0.7983 - val_loss: 73.4228 - val_accuracy: 0.8242
Epoch 44/100
7/7 [==============================] - 0s 7ms/step - loss: 76.5564 - accuracy: 0.7801 - val_loss: 86.0599 - val_accuracy: 0.7253
Epoch 45/100
7/7 [==============================] - 0s 7ms/step - loss: 84.7953 - accuracy: 0.7691 - val_loss: 101.4762 - val_accuracy: 0.6923
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 84.7202 - accuracy: 0.8214 - val_loss: 103.6874 - val_accuracy: 0.6374
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 87.7736 - accuracy: 0.7922 - val_loss: 81.2411 - val_accuracy: 0.8901
Epoch 48/100
7/7 [==============================] - 0s 7ms/step - loss: 87.3695 - accuracy: 0.7388 - val_loss: 92.1786 - val_accuracy: 0.6374
Epoch 49/100
7/7 [==============================] - 0s 7ms/step - loss: 81.6189 - accuracy: 0.8214 - val_loss: 98.6211 - val_accuracy: 0.6484
Epoch 50/100
7/7 [==============================] - 0s 12ms/step - loss: 85.7149 - accuracy: 0.7448 - val_loss: 116.5434 - val_accuracy: 0.8132
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 91.8362 - accuracy: 0.7448 - val_loss: 79.5608 - val_accuracy: 0.8791
Epoch 52/100
7/7 [==============================] - 0s 11ms/step - loss: 110.6489 - accuracy: 0.7947 - val_loss: 101.4434 - val_accuracy: 0.8132
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 107.2183 - accuracy: 0.7971 - val_loss: 119.0526 - val_accuracy: 0.7473
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 110.3079 - accuracy: 0.7752 - val_loss: 111.1795 - val_accuracy: 0.8901
Epoch 55/100
7/7 [==============================] - 0s 9ms/step - loss: 119.6094 - accuracy: 0.7485 - val_loss: 110.4763 - val_accuracy: 0.8901
Epoch 56/100
7/7 [==============================] - 0s 7ms/step - loss: 123.4663 - accuracy: 0.7679 - val_loss: 129.6869 - val_accuracy: 0.7143
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 120.1388 - accuracy: 0.7947 - val_loss: 126.2020 - val_accuracy: 0.7363
Epoch 58/100
7/7 [==============================] - 0s 9ms/step - loss: 122.8861 - accuracy: 0.8129 - val_loss: 129.5734 - val_accuracy: 0.7802
Epoch 59/100
7/7 [==============================] - 0s 7ms/step - loss: 137.3433 - accuracy: 0.7473 - val_loss: 137.6372 - val_accuracy: 0.9011
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 151.9159 - accuracy: 0.7473 - val_loss: 126.3702 - val_accuracy: 0.9011
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 159.9419 - accuracy: 0.8214 - val_loss: 183.7281 - val_accuracy: 0.8352
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 185.3731 - accuracy: 0.7436 - val_loss: 215.1352 - val_accuracy: 0.8352
Epoch 63/100
7/7 [==============================] - 0s 5ms/step - loss: 194.4744 - accuracy: 0.8226 - val_loss: 270.6799 - val_accuracy: 0.7363
Epoch 64/100
7/7 [==============================] - 0s 8ms/step - loss: 203.3103 - accuracy: 0.8238 - val_loss: 201.4161 - val_accuracy: 0.9011
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 224.9181 - accuracy: 0.7060 - val_loss: 185.1621 - val_accuracy: 0.8352
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 196.9134 - accuracy: 0.8335 - val_loss: 296.6502 - val_accuracy: 0.7473
Epoch 67/100
7/7 [==============================] - 0s 7ms/step - loss: 191.0742 - accuracy: 0.7837 - val_loss: 204.8768 - val_accuracy: 0.8022
Epoch 68/100
7/7 [==============================] - 0s 7ms/step - loss: 192.9688 - accuracy: 0.7448 - val_loss: 331.1552 - val_accuracy: 0.5385
Epoch 69/100
7/7 [==============================] - 0s 7ms/step - loss: 195.4039 - accuracy: 0.7801 - val_loss: 182.3329 - val_accuracy: 0.7143
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 194.8734 - accuracy: 0.7874 - val_loss: 257.6863 - val_accuracy: 0.6264
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 186.7591 - accuracy: 0.7776 - val_loss: 172.6487 - val_accuracy: 0.8901
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 195.5872 - accuracy: 0.7521 - val_loss: 295.4821 - val_accuracy: 0.7143
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 271.8997 - accuracy: 0.7825 - val_loss: 335.1887 - val_accuracy: 0.7582
Epoch 74/100
7/7 [==============================] - 0s 9ms/step - loss: 259.5838 - accuracy: 0.7740 - val_loss: 220.1412 - val_accuracy: 0.7473
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 256.2618 - accuracy: 0.7631 - val_loss: 245.2467 - val_accuracy: 0.8571
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 267.2026 - accuracy: 0.8032 - val_loss: 291.5714 - val_accuracy: 0.8901
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 308.4545 - accuracy: 0.7667 - val_loss: 281.2321 - val_accuracy: 0.6264
Epoch 78/100
7/7 [==============================] - 0s 7ms/step - loss: 279.3040 - accuracy: 0.7448 - val_loss: 277.6440 - val_accuracy: 0.7802
Epoch 79/100
7/7 [==============================] - 0s 9ms/step - loss: 315.4207 - accuracy: 0.8032 - val_loss: 343.5724 - val_accuracy: 0.7912
Epoch 80/100
7/7 [==============================] - 0s 10ms/step - loss: 303.4566 - accuracy: 0.8190 - val_loss: 292.1033 - val_accuracy: 0.8901
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 326.7066 - accuracy: 0.7339 - val_loss: 342.8590 - val_accuracy: 0.8681
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 408.2054 - accuracy: 0.7716 - val_loss: 397.0359 - val_accuracy: 0.8132
Epoch 83/100
7/7 [==============================] - 0s 7ms/step - loss: 408.4578 - accuracy: 0.8092 - val_loss: 430.6189 - val_accuracy: 0.7363
Epoch 84/100
7/7 [==============================] - 0s 6ms/step - loss: 442.1477 - accuracy: 0.7898 - val_loss: 404.6751 - val_accuracy: 0.7912
Epoch 85/100
7/7 [==============================] - 0s 6ms/step - loss: 434.7758 - accuracy: 0.7995 - val_loss: 435.8658 - val_accuracy: 0.6264
Epoch 86/100
7/7 [==============================] - 0s 9ms/step - loss: 431.8858 - accuracy: 0.7485 - val_loss: 410.6128 - val_accuracy: 0.8462
Epoch 87/100
7/7 [==============================] - 0s 9ms/step - loss: 423.9089 - accuracy: 0.7509 - val_loss: 356.9021 - val_accuracy: 0.8242
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 392.1522 - accuracy: 0.7691 - val_loss: 381.4394 - val_accuracy: 0.8791
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 375.8949 - accuracy: 0.7679 - val_loss: 425.9436 - val_accuracy: 0.8901
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 482.8668 - accuracy: 0.7546 - val_loss: 326.0862 - val_accuracy: 0.8022
Epoch 91/100
7/7 [==============================] - 0s 10ms/step - loss: 449.1333 - accuracy: 0.7339 - val_loss: 346.7072 - val_accuracy: 0.8901
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 574.3718 - accuracy: 0.7363 - val_loss: 414.3029 - val_accuracy: 0.8462
Epoch 93/100
7/7 [==============================] - 0s 7ms/step - loss: 526.1008 - accuracy: 0.7643 - val_loss: 535.2341 - val_accuracy: 0.7692
Epoch 94/100
7/7 [==============================] - 0s 7ms/step - loss: 434.0453 - accuracy: 0.8250 - val_loss: 563.4387 - val_accuracy: 0.3187
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 508.6056 - accuracy: 0.7363 - val_loss: 581.8663 - val_accuracy: 0.7692
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 661.2813 - accuracy: 0.7084 - val_loss: 453.4153 - val_accuracy: 0.9011
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 616.3005 - accuracy: 0.7424 - val_loss: 781.6210 - val_accuracy: 0.8901
Epoch 98/100
7/7 [==============================] - 0s 7ms/step - loss: 942.7112 - accuracy: 0.8117 - val_loss: 1851.5844 - val_accuracy: 0.5824
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 1035.6444 - accuracy: 0.7631 - val_loss: 1543.4015 - val_accuracy: 0.8571
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 1467.9745 - accuracy: 0.7205 - val_loss: 1520.4562 - val_accuracy: 0.8901
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 4ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 4.1708 - accuracy: 0.5687 - val_loss: 1.8725 - val_accuracy: 0.8681
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 2.7277 - accuracy: 0.8445 - val_loss: 3.8436 - val_accuracy: 0.8571
Epoch 3/100
7/7 [==============================] - 0s 7ms/step - loss: 4.0513 - accuracy: 0.8044 - val_loss: 3.6405 - val_accuracy: 0.8681
Epoch 4/100
7/7 [==============================] - 0s 7ms/step - loss: 3.4727 - accuracy: 0.8129 - val_loss: 3.5384 - val_accuracy: 0.8681
Epoch 5/100
7/7 [==============================] - 0s 7ms/step - loss: 3.7256 - accuracy: 0.7874 - val_loss: 3.9339 - val_accuracy: 0.8681
Epoch 6/100
7/7 [==============================] - 0s 7ms/step - loss: 4.0939 - accuracy: 0.8190 - val_loss: 3.5746 - val_accuracy: 0.8132
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 4.0085 - accuracy: 0.7947 - val_loss: 3.5020 - val_accuracy: 0.8681
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 4.3147 - accuracy: 0.7922 - val_loss: 4.6177 - val_accuracy: 0.8681
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 4.9334 - accuracy: 0.7861 - val_loss: 4.8745 - val_accuracy: 0.8681
Epoch 10/100
7/7 [==============================] - 0s 9ms/step - loss: 4.7903 - accuracy: 0.7910 - val_loss: 4.4807 - val_accuracy: 0.7253
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 5.7054 - accuracy: 0.8068 - val_loss: 6.7474 - val_accuracy: 0.7143
Epoch 12/100
7/7 [==============================] - 0s 9ms/step - loss: 6.9603 - accuracy: 0.8080 - val_loss: 8.2504 - val_accuracy: 0.6154
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 7.2122 - accuracy: 0.7959 - val_loss: 10.9218 - val_accuracy: 0.6813
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 7.0817 - accuracy: 0.8275 - val_loss: 6.4440 - val_accuracy: 0.8681
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 8.1523 - accuracy: 0.8262 - val_loss: 8.7950 - val_accuracy: 0.8681
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 7.8777 - accuracy: 0.8056 - val_loss: 8.8695 - val_accuracy: 0.8681
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 8.9434 - accuracy: 0.8323 - val_loss: 10.3575 - val_accuracy: 0.6703
Epoch 18/100
7/7 [==============================] - 0s 7ms/step - loss: 8.8491 - accuracy: 0.7910 - val_loss: 10.3932 - val_accuracy: 0.6703
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 8.9331 - accuracy: 0.8275 - val_loss: 11.4553 - val_accuracy: 0.6044
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 9.3584 - accuracy: 0.7473 - val_loss: 8.9158 - val_accuracy: 0.7253
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 9.8565 - accuracy: 0.8032 - val_loss: 17.0785 - val_accuracy: 0.5165
Epoch 22/100
7/7 [==============================] - 0s 7ms/step - loss: 10.9375 - accuracy: 0.7922 - val_loss: 12.1658 - val_accuracy: 0.6703
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 12.2806 - accuracy: 0.7983 - val_loss: 19.1146 - val_accuracy: 0.4176
Epoch 24/100
7/7 [==============================] - 0s 9ms/step - loss: 11.8125 - accuracy: 0.8165 - val_loss: 14.0400 - val_accuracy: 0.5934
Epoch 25/100
7/7 [==============================] - 0s 6ms/step - loss: 11.7783 - accuracy: 0.7764 - val_loss: 18.5543 - val_accuracy: 0.5824
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 13.6207 - accuracy: 0.8019 - val_loss: 11.5796 - val_accuracy: 0.8132
Epoch 27/100
7/7 [==============================] - 0s 7ms/step - loss: 12.9418 - accuracy: 0.7776 - val_loss: 11.8906 - val_accuracy: 0.7692
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 12.3146 - accuracy: 0.7606 - val_loss: 13.3321 - val_accuracy: 0.7912
Epoch 29/100
7/7 [==============================] - 0s 9ms/step - loss: 12.8950 - accuracy: 0.8457 - val_loss: 14.6152 - val_accuracy: 0.7692
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 14.0566 - accuracy: 0.7789 - val_loss: 13.2699 - val_accuracy: 0.8681
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 13.4223 - accuracy: 0.7716 - val_loss: 16.8118 - val_accuracy: 0.7363
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 14.7708 - accuracy: 0.8372 - val_loss: 13.0421 - val_accuracy: 0.7802
Epoch 33/100
7/7 [==============================] - 0s 7ms/step - loss: 14.5379 - accuracy: 0.7667 - val_loss: 12.6921 - val_accuracy: 0.5714
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 13.9982 - accuracy: 0.7363 - val_loss: 13.7654 - val_accuracy: 0.8352
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 14.2108 - accuracy: 0.7861 - val_loss: 20.8820 - val_accuracy: 0.6264
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 14.9709 - accuracy: 0.7947 - val_loss: 17.4730 - val_accuracy: 0.5934
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 18.2094 - accuracy: 0.7704 - val_loss: 27.2110 - val_accuracy: 0.7582
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 19.3532 - accuracy: 0.7400 - val_loss: 35.9072 - val_accuracy: 0.7253
Epoch 39/100
7/7 [==============================] - 0s 9ms/step - loss: 19.5824 - accuracy: 0.8092 - val_loss: 25.2977 - val_accuracy: 0.7253
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 21.3037 - accuracy: 0.7728 - val_loss: 19.7765 - val_accuracy: 0.8132
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 19.3773 - accuracy: 0.8214 - val_loss: 17.0084 - val_accuracy: 0.7473
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 21.5088 - accuracy: 0.7825 - val_loss: 53.4492 - val_accuracy: 0.1868
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 23.4138 - accuracy: 0.7789 - val_loss: 63.3165 - val_accuracy: 0.4945
Epoch 44/100
7/7 [==============================] - 0s 7ms/step - loss: 25.6062 - accuracy: 0.7959 - val_loss: 22.3897 - val_accuracy: 0.8132
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 26.3945 - accuracy: 0.7801 - val_loss: 22.6682 - val_accuracy: 0.7363
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 25.7977 - accuracy: 0.7983 - val_loss: 22.8214 - val_accuracy: 0.7802
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 24.3106 - accuracy: 0.7983 - val_loss: 22.0171 - val_accuracy: 0.7692
Epoch 48/100
7/7 [==============================] - 0s 6ms/step - loss: 24.1090 - accuracy: 0.8068 - val_loss: 29.9111 - val_accuracy: 0.7253
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 27.0816 - accuracy: 0.7363 - val_loss: 21.8210 - val_accuracy: 0.7473
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 24.9140 - accuracy: 0.7922 - val_loss: 49.5691 - val_accuracy: 0.3077
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 27.1384 - accuracy: 0.8032 - val_loss: 25.8165 - val_accuracy: 0.8132
Epoch 52/100
7/7 [==============================] - 0s 6ms/step - loss: 27.7368 - accuracy: 0.7558 - val_loss: 24.2531 - val_accuracy: 0.8132
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 27.2065 - accuracy: 0.7606 - val_loss: 30.3457 - val_accuracy: 0.6923
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 32.0836 - accuracy: 0.8202 - val_loss: 34.2088 - val_accuracy: 0.7473
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 29.5290 - accuracy: 0.7752 - val_loss: 28.4363 - val_accuracy: 0.8242
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 30.2028 - accuracy: 0.8019 - val_loss: 41.8937 - val_accuracy: 0.8681
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 31.3555 - accuracy: 0.7886 - val_loss: 31.6022 - val_accuracy: 0.8352
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 32.1238 - accuracy: 0.8299 - val_loss: 83.6334 - val_accuracy: 0.2418
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 34.5811 - accuracy: 0.7752 - val_loss: 34.3612 - val_accuracy: 0.8571
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 36.0817 - accuracy: 0.8092 - val_loss: 41.4483 - val_accuracy: 0.2637
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 34.0971 - accuracy: 0.7533 - val_loss: 33.5384 - val_accuracy: 0.7692
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 36.0594 - accuracy: 0.8408 - val_loss: 49.7720 - val_accuracy: 0.6264
Epoch 63/100
7/7 [==============================] - 0s 8ms/step - loss: 37.2083 - accuracy: 0.7959 - val_loss: 36.1555 - val_accuracy: 0.8242
Epoch 64/100
7/7 [==============================] - 0s 7ms/step - loss: 43.0084 - accuracy: 0.8177 - val_loss: 134.3163 - val_accuracy: 0.2967
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 46.0142 - accuracy: 0.7388 - val_loss: 46.5471 - val_accuracy: 0.6703
Epoch 66/100
7/7 [==============================] - 0s 6ms/step - loss: 44.2447 - accuracy: 0.7691 - val_loss: 55.1301 - val_accuracy: 0.6923
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 47.7060 - accuracy: 0.8092 - val_loss: 47.5676 - val_accuracy: 0.8132
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 49.5795 - accuracy: 0.8214 - val_loss: 44.2678 - val_accuracy: 0.8242
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 51.7346 - accuracy: 0.7752 - val_loss: 42.7749 - val_accuracy: 0.7143
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 53.2111 - accuracy: 0.7424 - val_loss: 59.5327 - val_accuracy: 0.8242
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 51.5895 - accuracy: 0.8214 - val_loss: 62.6942 - val_accuracy: 0.7582
Epoch 72/100
7/7 [==============================] - 0s 8ms/step - loss: 57.7076 - accuracy: 0.8032 - val_loss: 87.3325 - val_accuracy: 0.6703
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 63.2401 - accuracy: 0.8141 - val_loss: 83.0569 - val_accuracy: 0.8681
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 70.2039 - accuracy: 0.7606 - val_loss: 68.3378 - val_accuracy: 0.8681
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 72.0096 - accuracy: 0.7898 - val_loss: 76.2680 - val_accuracy: 0.8681
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 76.0085 - accuracy: 0.7424 - val_loss: 92.5129 - val_accuracy: 0.8681
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 85.9049 - accuracy: 0.8238 - val_loss: 75.7178 - val_accuracy: 0.8022
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 72.0295 - accuracy: 0.7728 - val_loss: 79.1370 - val_accuracy: 0.8022
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 91.2217 - accuracy: 0.8287 - val_loss: 89.6768 - val_accuracy: 0.6593
Epoch 80/100
7/7 [==============================] - 0s 7ms/step - loss: 79.1590 - accuracy: 0.7120 - val_loss: 79.9753 - val_accuracy: 0.8681
Epoch 81/100
7/7 [==============================] - 0s 9ms/step - loss: 97.7660 - accuracy: 0.8445 - val_loss: 71.4608 - val_accuracy: 0.8132
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 91.8029 - accuracy: 0.6950 - val_loss: 109.4214 - val_accuracy: 0.8681
Epoch 83/100
7/7 [==============================] - 0s 7ms/step - loss: 104.0710 - accuracy: 0.8469 - val_loss: 136.7424 - val_accuracy: 0.8022
Epoch 84/100
7/7 [==============================] - 0s 7ms/step - loss: 125.7777 - accuracy: 0.7849 - val_loss: 128.2130 - val_accuracy: 0.7912
Epoch 85/100
7/7 [==============================] - 0s 7ms/step - loss: 122.8017 - accuracy: 0.7679 - val_loss: 127.6648 - val_accuracy: 0.4945
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 103.2388 - accuracy: 0.8068 - val_loss: 108.9691 - val_accuracy: 0.8242
Epoch 87/100
7/7 [==============================] - 0s 7ms/step - loss: 123.4595 - accuracy: 0.7849 - val_loss: 153.6771 - val_accuracy: 0.7582
Epoch 88/100
7/7 [==============================] - 0s 7ms/step - loss: 145.0677 - accuracy: 0.7825 - val_loss: 217.6576 - val_accuracy: 0.6813
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 170.4210 - accuracy: 0.8092 - val_loss: 392.3612 - val_accuracy: 0.6484
Epoch 90/100
7/7 [==============================] - 0s 9ms/step - loss: 170.9353 - accuracy: 0.7898 - val_loss: 147.0129 - val_accuracy: 0.7473
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 146.2646 - accuracy: 0.7546 - val_loss: 154.9254 - val_accuracy: 0.8571
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 141.8568 - accuracy: 0.7691 - val_loss: 143.0988 - val_accuracy: 0.8242
Epoch 93/100
7/7 [==============================] - 0s 8ms/step - loss: 159.4060 - accuracy: 0.7959 - val_loss: 159.7168 - val_accuracy: 0.7912
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 174.8400 - accuracy: 0.7825 - val_loss: 147.2885 - val_accuracy: 0.7802
Epoch 95/100
7/7 [==============================] - 0s 7ms/step - loss: 165.5519 - accuracy: 0.7558 - val_loss: 188.9382 - val_accuracy: 0.6923
Epoch 96/100
7/7 [==============================] - 0s 9ms/step - loss: 202.6828 - accuracy: 0.7509 - val_loss: 270.6986 - val_accuracy: 0.6703
Epoch 97/100
7/7 [==============================] - 0s 8ms/step - loss: 210.2102 - accuracy: 0.8420 - val_loss: 371.1104 - val_accuracy: 0.6593
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 239.8344 - accuracy: 0.8032 - val_loss: 210.3422 - val_accuracy: 0.8571
Epoch 99/100
7/7 [==============================] - 0s 7ms/step - loss: 218.9311 - accuracy: 0.7776 - val_loss: 229.5561 - val_accuracy: 0.8571
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 212.8043 - accuracy: 0.8007 - val_loss: 179.9759 - val_accuracy: 0.7363
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 9ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 42ms/step - loss: 4.4829 - accuracy: 0.5808 - val_loss: 2.0587 - val_accuracy: 0.8901
Epoch 2/100
7/7 [==============================] - 0s 8ms/step - loss: 2.9812 - accuracy: 0.8311 - val_loss: 4.1186 - val_accuracy: 0.8791
Epoch 3/100
7/7 [==============================] - 0s 6ms/step - loss: 4.3359 - accuracy: 0.7801 - val_loss: 3.8550 - val_accuracy: 0.8901
Epoch 4/100
7/7 [==============================] - 0s 8ms/step - loss: 3.6262 - accuracy: 0.7801 - val_loss: 3.7777 - val_accuracy: 0.8901
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 4.4091 - accuracy: 0.7448 - val_loss: 4.8165 - val_accuracy: 0.8901
Epoch 6/100
7/7 [==============================] - 0s 8ms/step - loss: 4.9646 - accuracy: 0.8129 - val_loss: 3.5815 - val_accuracy: 0.8901
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 5.5513 - accuracy: 0.8019 - val_loss: 5.9307 - val_accuracy: 0.8901
Epoch 8/100
7/7 [==============================] - 0s 8ms/step - loss: 7.0020 - accuracy: 0.7716 - val_loss: 8.2048 - val_accuracy: 0.9121
Epoch 9/100
7/7 [==============================] - 0s 8ms/step - loss: 6.5135 - accuracy: 0.8275 - val_loss: 6.1896 - val_accuracy: 0.9011
Epoch 10/100
7/7 [==============================] - 0s 8ms/step - loss: 6.0870 - accuracy: 0.7959 - val_loss: 6.0283 - val_accuracy: 0.8791
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 6.4783 - accuracy: 0.7363 - val_loss: 6.5351 - val_accuracy: 0.8791
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 6.9768 - accuracy: 0.8396 - val_loss: 5.5322 - val_accuracy: 0.8571
Epoch 13/100
7/7 [==============================] - 0s 7ms/step - loss: 6.7526 - accuracy: 0.7570 - val_loss: 6.4756 - val_accuracy: 0.8681
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 8.0851 - accuracy: 0.8129 - val_loss: 7.7104 - val_accuracy: 0.8242
Epoch 15/100
7/7 [==============================] - 0s 8ms/step - loss: 8.0439 - accuracy: 0.7436 - val_loss: 10.5925 - val_accuracy: 0.8352
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 10.5782 - accuracy: 0.7509 - val_loss: 12.2074 - val_accuracy: 0.7253
Epoch 17/100
7/7 [==============================] - 0s 8ms/step - loss: 10.8184 - accuracy: 0.8214 - val_loss: 11.3483 - val_accuracy: 0.8901
Epoch 18/100
7/7 [==============================] - 0s 7ms/step - loss: 10.8438 - accuracy: 0.7886 - val_loss: 11.6018 - val_accuracy: 0.8681
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 11.4907 - accuracy: 0.8032 - val_loss: 12.9559 - val_accuracy: 0.8901
Epoch 20/100
7/7 [==============================] - 0s 7ms/step - loss: 12.1409 - accuracy: 0.8214 - val_loss: 13.9017 - val_accuracy: 0.7802
Epoch 21/100
7/7 [==============================] - 0s 8ms/step - loss: 12.4364 - accuracy: 0.7728 - val_loss: 11.5979 - val_accuracy: 0.9011
Epoch 22/100
7/7 [==============================] - 0s 8ms/step - loss: 11.7689 - accuracy: 0.8141 - val_loss: 11.4870 - val_accuracy: 0.8901
Epoch 23/100
7/7 [==============================] - 0s 8ms/step - loss: 10.7317 - accuracy: 0.8214 - val_loss: 10.8843 - val_accuracy: 0.8681
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 10.4938 - accuracy: 0.8080 - val_loss: 12.1567 - val_accuracy: 0.6044
Epoch 25/100
7/7 [==============================] - 0s 7ms/step - loss: 12.2903 - accuracy: 0.7533 - val_loss: 12.6835 - val_accuracy: 0.7582
Epoch 26/100
7/7 [==============================] - 0s 7ms/step - loss: 13.0147 - accuracy: 0.7667 - val_loss: 11.9413 - val_accuracy: 0.8681
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 13.0573 - accuracy: 0.7971 - val_loss: 13.1266 - val_accuracy: 0.8242
Epoch 28/100
7/7 [==============================] - 0s 8ms/step - loss: 13.5647 - accuracy: 0.7886 - val_loss: 14.0562 - val_accuracy: 0.7033
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 13.8691 - accuracy: 0.7679 - val_loss: 17.5632 - val_accuracy: 0.3077
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 12.5441 - accuracy: 0.7898 - val_loss: 12.6533 - val_accuracy: 0.4945
Epoch 31/100
7/7 [==============================] - 0s 8ms/step - loss: 11.2819 - accuracy: 0.7582 - val_loss: 11.0936 - val_accuracy: 0.8901
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 11.7234 - accuracy: 0.7861 - val_loss: 15.0412 - val_accuracy: 0.4505
Epoch 33/100
7/7 [==============================] - 0s 8ms/step - loss: 12.8200 - accuracy: 0.7716 - val_loss: 22.0021 - val_accuracy: 0.1099
Epoch 34/100
7/7 [==============================] - 0s 8ms/step - loss: 12.8546 - accuracy: 0.7764 - val_loss: 13.5196 - val_accuracy: 0.7582
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 13.3205 - accuracy: 0.7983 - val_loss: 12.5338 - val_accuracy: 0.8132
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 14.0776 - accuracy: 0.7533 - val_loss: 13.6352 - val_accuracy: 0.8242
Epoch 37/100
7/7 [==============================] - 0s 8ms/step - loss: 14.8010 - accuracy: 0.7704 - val_loss: 15.8314 - val_accuracy: 0.8901
Epoch 38/100
7/7 [==============================] - 0s 8ms/step - loss: 14.8204 - accuracy: 0.7278 - val_loss: 13.4230 - val_accuracy: 0.9011
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 13.1324 - accuracy: 0.8177 - val_loss: 12.5407 - val_accuracy: 0.8901
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 14.3888 - accuracy: 0.7594 - val_loss: 17.1655 - val_accuracy: 0.8462
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 16.9474 - accuracy: 0.7497 - val_loss: 21.6477 - val_accuracy: 0.7802
Epoch 42/100
7/7 [==============================] - 0s 8ms/step - loss: 19.2794 - accuracy: 0.8287 - val_loss: 22.4417 - val_accuracy: 0.8352
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 20.7997 - accuracy: 0.7947 - val_loss: 21.5373 - val_accuracy: 0.8901
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 20.7979 - accuracy: 0.8153 - val_loss: 21.6167 - val_accuracy: 0.8681
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 20.1701 - accuracy: 0.8153 - val_loss: 19.6458 - val_accuracy: 0.7363
Epoch 46/100
7/7 [==============================] - 0s 7ms/step - loss: 19.6342 - accuracy: 0.8080 - val_loss: 21.2647 - val_accuracy: 0.6813
Epoch 47/100
7/7 [==============================] - 0s 7ms/step - loss: 20.7000 - accuracy: 0.8080 - val_loss: 39.2078 - val_accuracy: 0.1099
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 19.9739 - accuracy: 0.7691 - val_loss: 31.7871 - val_accuracy: 0.1099
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 20.1944 - accuracy: 0.8165 - val_loss: 42.2518 - val_accuracy: 0.1099
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 19.2461 - accuracy: 0.7861 - val_loss: 16.1163 - val_accuracy: 0.7253
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 17.4899 - accuracy: 0.7716 - val_loss: 14.4295 - val_accuracy: 0.8352
Epoch 52/100
7/7 [==============================] - 0s 9ms/step - loss: 17.0181 - accuracy: 0.8177 - val_loss: 18.3689 - val_accuracy: 0.6923
Epoch 53/100
7/7 [==============================] - 0s 7ms/step - loss: 19.0688 - accuracy: 0.7934 - val_loss: 18.4377 - val_accuracy: 0.9011
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 19.7906 - accuracy: 0.8068 - val_loss: 20.9525 - val_accuracy: 0.8901
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 18.7091 - accuracy: 0.8190 - val_loss: 20.4969 - val_accuracy: 0.8132
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 19.5856 - accuracy: 0.7886 - val_loss: 28.6697 - val_accuracy: 0.3956
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 21.1712 - accuracy: 0.7631 - val_loss: 27.5604 - val_accuracy: 0.8022
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 23.7202 - accuracy: 0.8007 - val_loss: 24.3169 - val_accuracy: 0.8571
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 25.2364 - accuracy: 0.7813 - val_loss: 27.2218 - val_accuracy: 0.8462
Epoch 60/100
7/7 [==============================] - 0s 8ms/step - loss: 25.0168 - accuracy: 0.7266 - val_loss: 24.4317 - val_accuracy: 0.8901
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 23.1153 - accuracy: 0.7521 - val_loss: 21.3849 - val_accuracy: 0.8901
Epoch 62/100
7/7 [==============================] - 0s 8ms/step - loss: 21.3981 - accuracy: 0.8117 - val_loss: 17.9588 - val_accuracy: 0.7802
Epoch 63/100
7/7 [==============================] - 0s 9ms/step - loss: 20.1871 - accuracy: 0.7351 - val_loss: 21.0018 - val_accuracy: 0.6374
Epoch 64/100
7/7 [==============================] - 0s 9ms/step - loss: 22.5083 - accuracy: 0.7424 - val_loss: 23.8504 - val_accuracy: 0.6264
Epoch 65/100
7/7 [==============================] - 0s 8ms/step - loss: 22.8018 - accuracy: 0.8129 - val_loss: 32.9692 - val_accuracy: 0.2637
Epoch 66/100
7/7 [==============================] - 0s 9ms/step - loss: 21.1799 - accuracy: 0.7704 - val_loss: 20.3516 - val_accuracy: 0.5275
Epoch 67/100
7/7 [==============================] - 0s 7ms/step - loss: 22.3566 - accuracy: 0.7400 - val_loss: 36.1081 - val_accuracy: 0.2857
Epoch 68/100
7/7 [==============================] - 0s 8ms/step - loss: 23.7334 - accuracy: 0.7667 - val_loss: 35.8303 - val_accuracy: 0.3407
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 23.8021 - accuracy: 0.7983 - val_loss: 22.0913 - val_accuracy: 0.8352
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 26.9757 - accuracy: 0.7546 - val_loss: 23.6668 - val_accuracy: 0.8571
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 26.9507 - accuracy: 0.8092 - val_loss: 22.8519 - val_accuracy: 0.8571
Epoch 72/100
7/7 [==============================] - 0s 9ms/step - loss: 29.1390 - accuracy: 0.7886 - val_loss: 45.6103 - val_accuracy: 0.3297
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 28.9509 - accuracy: 0.7922 - val_loss: 50.8668 - val_accuracy: 0.1758
Epoch 74/100
7/7 [==============================] - 0s 8ms/step - loss: 29.0577 - accuracy: 0.8032 - val_loss: 25.9246 - val_accuracy: 0.8681
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 28.8792 - accuracy: 0.7764 - val_loss: 29.7495 - val_accuracy: 0.8901
Epoch 76/100
7/7 [==============================] - 0s 8ms/step - loss: 29.2049 - accuracy: 0.7874 - val_loss: 23.7022 - val_accuracy: 0.8132
Epoch 77/100
7/7 [==============================] - 0s 8ms/step - loss: 28.3753 - accuracy: 0.7776 - val_loss: 28.3441 - val_accuracy: 0.8901
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 31.5318 - accuracy: 0.7995 - val_loss: 33.8837 - val_accuracy: 0.8901
Epoch 79/100
7/7 [==============================] - 0s 8ms/step - loss: 36.2433 - accuracy: 0.7740 - val_loss: 29.9590 - val_accuracy: 0.8242
Epoch 80/100
7/7 [==============================] - 0s 8ms/step - loss: 33.0331 - accuracy: 0.8153 - val_loss: 32.7896 - val_accuracy: 0.8132
Epoch 81/100
7/7 [==============================] - 0s 8ms/step - loss: 36.6887 - accuracy: 0.7254 - val_loss: 43.0624 - val_accuracy: 0.6264
Epoch 82/100
7/7 [==============================] - 0s 8ms/step - loss: 37.8511 - accuracy: 0.7995 - val_loss: 33.5889 - val_accuracy: 0.7143
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 38.1136 - accuracy: 0.7691 - val_loss: 36.6496 - val_accuracy: 0.7473
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 39.5759 - accuracy: 0.7546 - val_loss: 37.5574 - val_accuracy: 0.8901
Epoch 85/100
7/7 [==============================] - 0s 8ms/step - loss: 42.3861 - accuracy: 0.8287 - val_loss: 42.5916 - val_accuracy: 0.5275
Epoch 86/100
7/7 [==============================] - 0s 8ms/step - loss: 44.7674 - accuracy: 0.7011 - val_loss: 44.9736 - val_accuracy: 0.8901
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 43.2432 - accuracy: 0.7874 - val_loss: 31.0241 - val_accuracy: 0.8791
Epoch 88/100
7/7 [==============================] - 0s 9ms/step - loss: 38.8157 - accuracy: 0.7169 - val_loss: 30.6631 - val_accuracy: 0.8242
Epoch 89/100
7/7 [==============================] - 0s 8ms/step - loss: 41.1340 - accuracy: 0.7704 - val_loss: 38.0238 - val_accuracy: 0.8242
Epoch 90/100
7/7 [==============================] - 0s 8ms/step - loss: 47.3678 - accuracy: 0.8007 - val_loss: 37.6150 - val_accuracy: 0.8901
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 51.1972 - accuracy: 0.7728 - val_loss: 45.0358 - val_accuracy: 0.8571
Epoch 92/100
7/7 [==============================] - 0s 8ms/step - loss: 52.7346 - accuracy: 0.7959 - val_loss: 63.8000 - val_accuracy: 0.7473
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 56.6124 - accuracy: 0.7691 - val_loss: 72.2847 - val_accuracy: 0.6813
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 57.9579 - accuracy: 0.7934 - val_loss: 61.5328 - val_accuracy: 0.7802
Epoch 95/100
7/7 [==============================] - 0s 7ms/step - loss: 54.3136 - accuracy: 0.8190 - val_loss: 44.9823 - val_accuracy: 0.8242
Epoch 96/100
7/7 [==============================] - 0s 8ms/step - loss: 56.8929 - accuracy: 0.7776 - val_loss: 41.5808 - val_accuracy: 0.6264
Epoch 97/100
7/7 [==============================] - 0s 7ms/step - loss: 53.9262 - accuracy: 0.7521 - val_loss: 47.7986 - val_accuracy: 0.8571
Epoch 98/100
7/7 [==============================] - 0s 8ms/step - loss: 55.9406 - accuracy: 0.7473 - val_loss: 53.8780 - val_accuracy: 0.8901
Epoch 99/100
7/7 [==============================] - 0s 8ms/step - loss: 65.9667 - accuracy: 0.8007 - val_loss: 59.4377 - val_accuracy: 0.7473
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 67.8129 - accuracy: 0.7716 - val_loss: 68.7642 - val_accuracy: 0.8901
No description has been provided for this image
No description has been provided for this image 
3/3 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True}
Batch size: 128
X_current_train shape: (823, 11)
y_current_train shape: (823, 3)
Epoch 1/100
7/7 [==============================] - 1s 43ms/step - loss: 4.7445 - accuracy: 0.4775 - val_loss: 2.2769 - val_accuracy: 0.8352
Epoch 2/100
7/7 [==============================] - 0s 7ms/step - loss: 2.9942 - accuracy: 0.8433 - val_loss: 4.7910 - val_accuracy: 0.8352
Epoch 3/100
7/7 [==============================] - 0s 9ms/step - loss: 4.8220 - accuracy: 0.8032 - val_loss: 4.5578 - val_accuracy: 0.8352
Epoch 4/100
7/7 [==============================] - 0s 9ms/step - loss: 3.9753 - accuracy: 0.8299 - val_loss: 4.0604 - val_accuracy: 0.8352
Epoch 5/100
7/7 [==============================] - 0s 8ms/step - loss: 4.4292 - accuracy: 0.7764 - val_loss: 5.2651 - val_accuracy: 0.8352
Epoch 6/100
7/7 [==============================] - 0s 7ms/step - loss: 5.0955 - accuracy: 0.7849 - val_loss: 5.1053 - val_accuracy: 0.8352
Epoch 7/100
7/7 [==============================] - 0s 8ms/step - loss: 4.6493 - accuracy: 0.8032 - val_loss: 6.2079 - val_accuracy: 0.8352
Epoch 8/100
7/7 [==============================] - 0s 7ms/step - loss: 5.6364 - accuracy: 0.7922 - val_loss: 5.9314 - val_accuracy: 0.8352
Epoch 9/100
7/7 [==============================] - 0s 6ms/step - loss: 5.6858 - accuracy: 0.8165 - val_loss: 6.1300 - val_accuracy: 0.8462
Epoch 10/100
7/7 [==============================] - 0s 7ms/step - loss: 6.4926 - accuracy: 0.7922 - val_loss: 7.5797 - val_accuracy: 0.8132
Epoch 11/100
7/7 [==============================] - 0s 8ms/step - loss: 7.0774 - accuracy: 0.8104 - val_loss: 9.0747 - val_accuracy: 0.7582
Epoch 12/100
7/7 [==============================] - 0s 8ms/step - loss: 8.8875 - accuracy: 0.8032 - val_loss: 11.6788 - val_accuracy: 0.7253
Epoch 13/100
7/7 [==============================] - 0s 8ms/step - loss: 10.1950 - accuracy: 0.8190 - val_loss: 10.7479 - val_accuracy: 0.8022
Epoch 14/100
7/7 [==============================] - 0s 8ms/step - loss: 9.8246 - accuracy: 0.8202 - val_loss: 9.6514 - val_accuracy: 0.7912
Epoch 15/100
7/7 [==============================] - 0s 7ms/step - loss: 9.4174 - accuracy: 0.7825 - val_loss: 10.1173 - val_accuracy: 0.8352
Epoch 16/100
7/7 [==============================] - 0s 8ms/step - loss: 9.9125 - accuracy: 0.7752 - val_loss: 9.7489 - val_accuracy: 0.8352
Epoch 17/100
7/7 [==============================] - 0s 7ms/step - loss: 9.7185 - accuracy: 0.7934 - val_loss: 11.0491 - val_accuracy: 0.8352
Epoch 18/100
7/7 [==============================] - 0s 8ms/step - loss: 9.5354 - accuracy: 0.8287 - val_loss: 11.1953 - val_accuracy: 0.8022
Epoch 19/100
7/7 [==============================] - 0s 8ms/step - loss: 8.8730 - accuracy: 0.8129 - val_loss: 9.9415 - val_accuracy: 0.8242
Epoch 20/100
7/7 [==============================] - 0s 8ms/step - loss: 9.5102 - accuracy: 0.8141 - val_loss: 10.9065 - val_accuracy: 0.7033
Epoch 21/100
7/7 [==============================] - 0s 7ms/step - loss: 11.3311 - accuracy: 0.8153 - val_loss: 12.2408 - val_accuracy: 0.7912
Epoch 22/100
7/7 [==============================] - 0s 15ms/step - loss: 11.4906 - accuracy: 0.7983 - val_loss: 12.7598 - val_accuracy: 0.7033
Epoch 23/100
7/7 [==============================] - 0s 10ms/step - loss: 12.8471 - accuracy: 0.7934 - val_loss: 13.7849 - val_accuracy: 0.7912
Epoch 24/100
7/7 [==============================] - 0s 8ms/step - loss: 13.4506 - accuracy: 0.8287 - val_loss: 13.4948 - val_accuracy: 0.7912
Epoch 25/100
7/7 [==============================] - 0s 8ms/step - loss: 13.4145 - accuracy: 0.7886 - val_loss: 14.7861 - val_accuracy: 0.7692
Epoch 26/100
7/7 [==============================] - 0s 9ms/step - loss: 13.9859 - accuracy: 0.8214 - val_loss: 13.6616 - val_accuracy: 0.8352
Epoch 27/100
7/7 [==============================] - 0s 8ms/step - loss: 14.3370 - accuracy: 0.7825 - val_loss: 12.9848 - val_accuracy: 0.8352
Epoch 28/100
7/7 [==============================] - 0s 7ms/step - loss: 13.6573 - accuracy: 0.8226 - val_loss: 11.5117 - val_accuracy: 0.7582
Epoch 29/100
7/7 [==============================] - 0s 8ms/step - loss: 13.1137 - accuracy: 0.7072 - val_loss: 14.7835 - val_accuracy: 0.6703
Epoch 30/100
7/7 [==============================] - 0s 8ms/step - loss: 13.1818 - accuracy: 0.7813 - val_loss: 26.9307 - val_accuracy: 0.1648
Epoch 31/100
7/7 [==============================] - 0s 6ms/step - loss: 13.2583 - accuracy: 0.8056 - val_loss: 16.6684 - val_accuracy: 0.6813
Epoch 32/100
7/7 [==============================] - 0s 8ms/step - loss: 16.2324 - accuracy: 0.7363 - val_loss: 16.5896 - val_accuracy: 0.7253
Epoch 33/100
7/7 [==============================] - 0s 9ms/step - loss: 15.5832 - accuracy: 0.7971 - val_loss: 15.0770 - val_accuracy: 0.8022
Epoch 34/100
7/7 [==============================] - 0s 7ms/step - loss: 17.0760 - accuracy: 0.7704 - val_loss: 56.8465 - val_accuracy: 0.5055
Epoch 35/100
7/7 [==============================] - 0s 8ms/step - loss: 32.9553 - accuracy: 0.7655 - val_loss: 64.0266 - val_accuracy: 0.7033
Epoch 36/100
7/7 [==============================] - 0s 8ms/step - loss: 76.1131 - accuracy: 0.8019 - val_loss: 113.0410 - val_accuracy: 0.7692
Epoch 37/100
7/7 [==============================] - 0s 7ms/step - loss: 136.5051 - accuracy: 0.7679 - val_loss: 185.2089 - val_accuracy: 0.7692
Epoch 38/100
7/7 [==============================] - 0s 6ms/step - loss: 213.5590 - accuracy: 0.8019 - val_loss: 272.3902 - val_accuracy: 0.4945
Epoch 39/100
7/7 [==============================] - 0s 8ms/step - loss: 304.0598 - accuracy: 0.7655 - val_loss: 366.4314 - val_accuracy: 0.8022
Epoch 40/100
7/7 [==============================] - 0s 7ms/step - loss: 407.0032 - accuracy: 0.7922 - val_loss: 472.3498 - val_accuracy: 0.8132
Epoch 41/100
7/7 [==============================] - 0s 8ms/step - loss: 513.4675 - accuracy: 0.7910 - val_loss: 1290.6790 - val_accuracy: 0.3626
Epoch 42/100
7/7 [==============================] - 0s 7ms/step - loss: 670.7825 - accuracy: 0.7922 - val_loss: 791.2743 - val_accuracy: 0.7912
Epoch 43/100
7/7 [==============================] - 0s 8ms/step - loss: 873.4898 - accuracy: 0.7230 - val_loss: 1069.0594 - val_accuracy: 0.7473
Epoch 44/100
7/7 [==============================] - 0s 8ms/step - loss: 1136.6381 - accuracy: 0.8056 - val_loss: 1319.4327 - val_accuracy: 0.6703
Epoch 45/100
7/7 [==============================] - 0s 8ms/step - loss: 1398.8379 - accuracy: 0.8007 - val_loss: 1615.1136 - val_accuracy: 0.6484
Epoch 46/100
7/7 [==============================] - 0s 8ms/step - loss: 1701.4786 - accuracy: 0.7801 - val_loss: 1929.1095 - val_accuracy: 0.7253
Epoch 47/100
7/7 [==============================] - 0s 8ms/step - loss: 2010.3551 - accuracy: 0.7521 - val_loss: 2280.3105 - val_accuracy: 0.8132
Epoch 48/100
7/7 [==============================] - 0s 8ms/step - loss: 2313.8130 - accuracy: 0.7825 - val_loss: 2571.8103 - val_accuracy: 0.7912
Epoch 49/100
7/7 [==============================] - 0s 8ms/step - loss: 2599.7043 - accuracy: 0.8007 - val_loss: 2825.7017 - val_accuracy: 0.8352
Epoch 50/100
7/7 [==============================] - 0s 8ms/step - loss: 2851.0002 - accuracy: 0.7303 - val_loss: 3091.6108 - val_accuracy: 0.8132
Epoch 51/100
7/7 [==============================] - 0s 8ms/step - loss: 3121.0381 - accuracy: 0.8299 - val_loss: 3350.7261 - val_accuracy: 0.7473
Epoch 52/100
7/7 [==============================] - 0s 8ms/step - loss: 3338.9395 - accuracy: 0.7874 - val_loss: 3533.1526 - val_accuracy: 0.7912
Epoch 53/100
7/7 [==============================] - 0s 8ms/step - loss: 3521.8088 - accuracy: 0.7752 - val_loss: 3677.3364 - val_accuracy: 0.8242
Epoch 54/100
7/7 [==============================] - 0s 8ms/step - loss: 3674.7441 - accuracy: 0.7934 - val_loss: 3778.7424 - val_accuracy: 0.7912
Epoch 55/100
7/7 [==============================] - 0s 8ms/step - loss: 3752.6609 - accuracy: 0.8080 - val_loss: 3823.4080 - val_accuracy: 0.8462
Epoch 56/100
7/7 [==============================] - 0s 8ms/step - loss: 3793.4126 - accuracy: 0.7910 - val_loss: 3807.9412 - val_accuracy: 0.7912
Epoch 57/100
7/7 [==============================] - 0s 8ms/step - loss: 3766.2822 - accuracy: 0.7813 - val_loss: 3738.6948 - val_accuracy: 0.8352
Epoch 58/100
7/7 [==============================] - 0s 8ms/step - loss: 3698.5051 - accuracy: 0.7776 - val_loss: 3662.0828 - val_accuracy: 0.6813
Epoch 59/100
7/7 [==============================] - 0s 8ms/step - loss: 3579.2412 - accuracy: 0.7594 - val_loss: 3496.1606 - val_accuracy: 0.8022
Epoch 60/100
7/7 [==============================] - 0s 7ms/step - loss: 3421.9463 - accuracy: 0.7740 - val_loss: 3306.5386 - val_accuracy: 0.8352
Epoch 61/100
7/7 [==============================] - 0s 8ms/step - loss: 3224.4402 - accuracy: 0.7570 - val_loss: 3076.6670 - val_accuracy: 0.8352
Epoch 62/100
7/7 [==============================] - 0s 7ms/step - loss: 2984.9382 - accuracy: 0.8530 - val_loss: 2825.3420 - val_accuracy: 0.7582
Epoch 63/100
7/7 [==============================] - 0s 7ms/step - loss: 2711.8765 - accuracy: 0.7230 - val_loss: 2556.2717 - val_accuracy: 0.8132
Epoch 64/100
7/7 [==============================] - 0s 7ms/step - loss: 2439.8779 - accuracy: 0.8202 - val_loss: 2289.8643 - val_accuracy: 0.7363
Epoch 65/100
7/7 [==============================] - 0s 7ms/step - loss: 2174.0212 - accuracy: 0.7448 - val_loss: 2059.9233 - val_accuracy: 0.8352
Epoch 66/100
7/7 [==============================] - 0s 8ms/step - loss: 1949.8527 - accuracy: 0.7485 - val_loss: 1797.7749 - val_accuracy: 0.7912
Epoch 67/100
7/7 [==============================] - 0s 8ms/step - loss: 1704.0083 - accuracy: 0.8068 - val_loss: 1635.5826 - val_accuracy: 0.8132
Epoch 68/100
7/7 [==============================] - 0s 6ms/step - loss: 1522.1978 - accuracy: 0.8080 - val_loss: 1439.4517 - val_accuracy: 0.7912
Epoch 69/100
7/7 [==============================] - 0s 8ms/step - loss: 1355.6327 - accuracy: 0.7764 - val_loss: 1279.6766 - val_accuracy: 0.8242
Epoch 70/100
7/7 [==============================] - 0s 8ms/step - loss: 1247.7109 - accuracy: 0.8129 - val_loss: 1305.6661 - val_accuracy: 0.6923
Epoch 71/100
7/7 [==============================] - 0s 8ms/step - loss: 1210.1113 - accuracy: 0.7922 - val_loss: 1175.0824 - val_accuracy: 0.7802
Epoch 72/100
7/7 [==============================] - 0s 7ms/step - loss: 1200.6726 - accuracy: 0.7618 - val_loss: 1275.0769 - val_accuracy: 0.8352
Epoch 73/100
7/7 [==============================] - 0s 8ms/step - loss: 1317.2793 - accuracy: 0.8275 - val_loss: 1396.1449 - val_accuracy: 0.6484
Epoch 74/100
7/7 [==============================] - 0s 7ms/step - loss: 1442.8284 - accuracy: 0.7849 - val_loss: 1648.7302 - val_accuracy: 0.8352
Epoch 75/100
7/7 [==============================] - 0s 8ms/step - loss: 1607.8147 - accuracy: 0.7655 - val_loss: 1602.7354 - val_accuracy: 0.7912
Epoch 76/100
7/7 [==============================] - 0s 9ms/step - loss: 1737.7307 - accuracy: 0.8032 - val_loss: 2145.4937 - val_accuracy: 0.8242
Epoch 77/100
7/7 [==============================] - 0s 7ms/step - loss: 1956.4210 - accuracy: 0.6974 - val_loss: 2305.2632 - val_accuracy: 0.8242
Epoch 78/100
7/7 [==============================] - 0s 8ms/step - loss: 2113.4685 - accuracy: 0.7922 - val_loss: 2456.3091 - val_accuracy: 0.8132
Epoch 79/100
7/7 [==============================] - 0s 7ms/step - loss: 2373.0991 - accuracy: 0.8068 - val_loss: 2588.5103 - val_accuracy: 0.7473
Epoch 80/100
7/7 [==============================] - 0s 7ms/step - loss: 2619.2515 - accuracy: 0.7849 - val_loss: 2728.3845 - val_accuracy: 0.8571
Epoch 81/100
7/7 [==============================] - 0s 7ms/step - loss: 2796.1414 - accuracy: 0.7691 - val_loss: 2866.0400 - val_accuracy: 0.7912
Epoch 82/100
7/7 [==============================] - 0s 7ms/step - loss: 3027.0999 - accuracy: 0.7837 - val_loss: 3091.1050 - val_accuracy: 0.8022
Epoch 83/100
7/7 [==============================] - 0s 8ms/step - loss: 3206.4775 - accuracy: 0.7740 - val_loss: 3352.9595 - val_accuracy: 0.8022
Epoch 84/100
7/7 [==============================] - 0s 8ms/step - loss: 3323.5833 - accuracy: 0.7874 - val_loss: 3591.8770 - val_accuracy: 0.7912
Epoch 85/100
7/7 [==============================] - 0s 7ms/step - loss: 3431.4563 - accuracy: 0.7959 - val_loss: 3646.2837 - val_accuracy: 0.7692
Epoch 86/100
7/7 [==============================] - 0s 7ms/step - loss: 3413.9792 - accuracy: 0.8177 - val_loss: 3594.1438 - val_accuracy: 0.7473
Epoch 87/100
7/7 [==============================] - 0s 8ms/step - loss: 3475.9021 - accuracy: 0.7181 - val_loss: 3484.9685 - val_accuracy: 0.8132
Epoch 88/100
7/7 [==============================] - 0s 8ms/step - loss: 3397.5349 - accuracy: 0.7728 - val_loss: 3447.6011 - val_accuracy: 0.8022
Epoch 89/100
7/7 [==============================] - 0s 7ms/step - loss: 3284.7292 - accuracy: 0.8250 - val_loss: 3390.4316 - val_accuracy: 0.8462
Epoch 90/100
7/7 [==============================] - 0s 7ms/step - loss: 3223.0720 - accuracy: 0.7704 - val_loss: 3324.1206 - val_accuracy: 0.8242
Epoch 91/100
7/7 [==============================] - 0s 8ms/step - loss: 3126.3972 - accuracy: 0.8238 - val_loss: 3738.5332 - val_accuracy: 0.6923
Epoch 92/100
7/7 [==============================] - 0s 7ms/step - loss: 2983.1118 - accuracy: 0.7910 - val_loss: 3111.3955 - val_accuracy: 0.8352
Epoch 93/100
7/7 [==============================] - 0s 9ms/step - loss: 2771.8708 - accuracy: 0.7339 - val_loss: 2540.2986 - val_accuracy: 0.8242
Epoch 94/100
7/7 [==============================] - 0s 8ms/step - loss: 2513.1150 - accuracy: 0.8420 - val_loss: 2368.4070 - val_accuracy: 0.8022
Epoch 95/100
7/7 [==============================] - 0s 8ms/step - loss: 2345.2878 - accuracy: 0.7570 - val_loss: 2270.6641 - val_accuracy: 0.8242
Epoch 96/100
7/7 [==============================] - 0s 9ms/step - loss: 2126.1165 - accuracy: 0.7971 - val_loss: 1962.6260 - val_accuracy: 0.8242
Epoch 97/100
7/7 [==============================] - 0s 7ms/step - loss: 1958.5962 - accuracy: 0.7473 - val_loss: 1958.6597 - val_accuracy: 0.8571
Epoch 98/100
7/7 [==============================] - 0s 9ms/step - loss: 1796.6755 - accuracy: 0.7509 - val_loss: 1938.7941 - val_accuracy: 0.8462
Epoch 99/100
7/7 [==============================] - 0s 7ms/step - loss: 1871.9535 - accuracy: 0.8092 - val_loss: 1779.9617 - val_accuracy: 0.7473
Epoch 100/100
7/7 [==============================] - 0s 8ms/step - loss: 1695.1500 - accuracy: 0.7691 - val_loss: 2021.7233 - val_accuracy: 0.8132
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No description has been provided for this image 
3/3 [==============================] - 0s 2ms/step
Best score: 0.8545269947443861
Best parameters: {'learning_rate': 0.1, 'hidden_layers': 2, 'hidden_units': 16, 'batch_size': 128, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.9, 'batch_norm': True}
Best model is in 10 experiment

Experiment 2 Result Analysis¶

The integration of batch normalization into the training process seems to have had a nuanced effect on the model's performance.

  • No Significant Improvement on Accuracy The inclusion of batch normalization did not lead to a notable increase in accuracy. This might suggest that the model’s ability to fit the data was not primarily constrained by internal covariate shift or that other factors are limiting the model's performance.

  • Mitigating Overfitting The observation that signs of overfitting have been reduced is encouraging. Batch normalization can have a regularizing effect, as it introduces a small amount of noise into each layer's inputs during training. This can prevent the model from fitting too closely to the training data.

    The fact that batch normalization helped mitigate overfitting but did not improve accuracy might indicate that the model is regularized enough not to overfit but still lacks the capacity to better learn the underlying patterns in the data. This could also be a result of other hyperparameters or aspects of the model architecture that are not optimal.

For the next steps, I will include weight initialization. Proper weight initialization can have an impact on the training dynamics of a neural network.

Step 7: Regularizing the Model — Experiment 3: Kfold = 3, batch_normalization, weight initialization¶

  • Batch Normalization: True, False

Batch normalization is a technique to provide any layer in a neural network with inputs that are zero mean/unit variance, which helps to stabilize the training process.

  • Weight Initializers: random_normal, random_uniform, he_normal, he_uniform, glorot_normal, glorot_uniform

Weight initialization hyperparameters control how the initial weights of a network are set. Proper initialization can improve convergence during training.

In [68]:
n_splits=3
cross_validator = KFold(n_splits=n_splits, shuffle=True, random_state=42)

def create_model(hidden_units, hidden_layers, optimizer, dropout_rate, l1, l2, learning_rate, initializers, adam_beta_1=None, adam_beta_2=None, momentum=None, learning_rate_decay=None, rho=None, batch_norm=False):
    model = models.Sequential()
    model.add(layers.Dense(hidden_units, activation='relu', input_shape=(11,), kernel_regularizer=regularizers.l1_l2(l1=l1, l2=l2)))
    if batch_norm == True:
        model.add(layers.BatchNormalization())
    model.add(layers.Dropout(dropout_rate))
    model.add(layers.Dense(3, activation='softmax', kernel_initializer=initializers))
    
    if optimizer == 'Adam':
        if adam_beta_1 is not None and adam_beta_2 is not None:
            optimizer = Adam(learning_rate=learning_rate, beta_1=adam_beta_1, beta_2=adam_beta_2)
    elif optimizer == 'RMSprop':
        optimizer = RMSprop(learning_rate=learning_rate, rho=rho)
    elif optimizer == 'momentum':
        optimizer = SGD(learning_rate=learning_rate, momentum=momentum)
    else:
        raise ValueError("Unknown optimizer")  
    model.compile(loss='categorical_crossentropy', optimizer=optimizer, metrics=['accuracy'])
    return model
In [69]:
learning_rate = [
    10 ** -i for i in range(1, 6)
]
hidden_layers = [
    1, 2, 3, 4, 5,
]
hidden_units = [
    8, 16, 32, 64, 128, 256,
]
batch_size = [
    128, 256, 512,
]
optimizer = [
    'momentum', 'RMSprop', 'Adam',
]
dropout_rate = [0.2, 0.3, 0.4,]

l1=[0.001, 0.01, 0.1,]
l2=[0.001, 0.01, 0.1,]

momentum = [
    0.8, 0.9, 0.99, 0.999,
]
learning_rate_decay = [lr/100 for lr in learning_rate]

rho = [0.8, 0.9, 0.99]

adam_beta_1 = [0.9, 0.95]
adam_beta_2 = [0.999, 0.9995]

batch_norm = [True, False]
initializers = ['random_normal', 'random_uniform', 'he_normal', 'he_uniform', 'glorot_normal', 'glorot_uniform']

param_space = {
    'learning_rate': learning_rate,
    'hidden_layers': hidden_layers,
    'hidden_units': hidden_units,
    'batch_size': batch_size,
    'learning_rate_decay': learning_rate_decay,
    'optimizer': optimizer,
    'l1': l1,
    'l2': l2,
    'dropout_rate': dropout_rate,
    'momentum': momentum if 'momentum' in optimizer else [None],
    'adam_beta_1': adam_beta_1 if 'Adam' in optimizer else [None],
    'adam_beta_2': adam_beta_2 if 'Adam' in optimizer else [None],
    'rho': rho if 'RMSprop' in optimizer else [None],
    'batch_norm': batch_norm,
    'initializers':initializers,
}
In [70]:
n_iter = 10
best_score = 0
best_params = {}

for i in range(n_iter):
    print(f"Experiment number: {i+1}")
    sampled_params = {k: np.random.choice(list(v)) for k,v in param_space.items()} # use random search
    model_params = {k:v for k, v in sampled_params.items() if k != 'batch_size'}
    if model_params['optimizer'] != 'momentum':
        model_params['momentum'] = None
    if model_params['optimizer'] != 'Adam':
        model_params['adam_beta_1'] = None
        model_params['adam_beta_2'] = None
    if model_params['optimizer'] != 'RMSprop':
        model_params['rho'] = None

    cv_scores = []
    for train_index, val_index in cross_validator.split(X_train): # I am confused about the data splits here, asked GPT4, accessed on Jan 27th
        X_current_train, X_val = X_train[train_index], X_train[val_index]
        y_current_train, y_val = y_train[train_index], y_train[val_index]
        model = create_model(**model_params)
        print("Model parameters:", model_params)
        print("Batch size:", sampled_params['batch_size'])
        print("X_current_train shape:", X_current_train.shape)
        print("y_current_train shape:", y_current_train.shape)
        history = model.fit(
            X_current_train, y_current_train, 
            epochs=100, 
            batch_size=sampled_params['batch_size'],
            verbose=1,
            validation_data=(X_val, y_val)
        )
        plot_loss(history)
        plot_accuracy(history)
        y_val_pred = model.predict(X_val) # the evaluation and scoring part, I am not sure which libraries to use. Asked GPT4, accessed on Jan 27th
        y_val_pred_classes = np.argmax(y_val_pred, axis=1)
        y_true_classes = np.argmax(y_val, axis=1)
        
        scoring = accuracy_score(y_true_classes, y_val_pred_classes)
        cv_scores.append(scoring)
    mean_cv_scores = np.mean(cv_scores)
        
    if mean_cv_scores > best_score:
        best_score = mean_cv_scores
        if sampled_params['optimizer'] == 'momentum':
            sampled_params['adam_beta_1'] = None
            sampled_params['adam_beta_2'] = None
            sampled_params['rho'] = None
        if sampled_params['optimizer'] == 'RMSprop':
            sampled_params['adam_beta_1'] = None
            sampled_params['adam_beta_2'] = None
            sampled_params['momentum'] = None
        if sampled_params['optimizer'] == 'Adam':
            sampled_params['momentum'] = None
            sampled_params['rho'] = None
        best_params = {k: v for k, v in sampled_params.items() if v is not None}
               
print("Best score:", best_score)
print("Best parameters:", best_params)
print(f"Best model is in {i+1} experiment")

Experiment number: 1
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.9, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 64ms/step - loss: 2.1267 - accuracy: 0.6174 - val_loss: 1.2870 - val_accuracy: 0.8393
Epoch 2/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9398 - accuracy: 0.8112 - val_loss: 1.6786 - val_accuracy: 0.8164
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8180 - accuracy: 0.8637 - val_loss: 0.7107 - val_accuracy: 0.8164
Epoch 4/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5550 - accuracy: 0.8637 - val_loss: 0.7335 - val_accuracy: 0.8230
Epoch 5/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5856 - accuracy: 0.8604 - val_loss: 0.5119 - val_accuracy: 0.8590
Epoch 6/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5278 - accuracy: 0.8555 - val_loss: 0.9088 - val_accuracy: 0.8164
Epoch 7/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4870 - accuracy: 0.8571 - val_loss: 0.8402 - val_accuracy: 0.8164
Epoch 8/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5658 - accuracy: 0.8473 - val_loss: 0.5323 - val_accuracy: 0.8164
Epoch 9/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4806 - accuracy: 0.8571 - val_loss: 0.7411 - val_accuracy: 0.8164
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5341 - accuracy: 0.8489 - val_loss: 0.5302 - val_accuracy: 0.8164
Epoch 11/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4246 - accuracy: 0.8654 - val_loss: 0.4896 - val_accuracy: 0.8230
Epoch 12/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4894 - accuracy: 0.8539 - val_loss: 0.5674 - val_accuracy: 0.8623
Epoch 13/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4599 - accuracy: 0.8489 - val_loss: 0.6789 - val_accuracy: 0.8164
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7926 - accuracy: 0.7044 - val_loss: 0.5162 - val_accuracy: 0.8590
Epoch 15/100
5/5 [==============================] - 0s 16ms/step - loss: 0.6576 - accuracy: 0.8489 - val_loss: 0.6876 - val_accuracy: 0.8164
Epoch 16/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4928 - accuracy: 0.8489 - val_loss: 0.5385 - val_accuracy: 0.8164
Epoch 17/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4667 - accuracy: 0.8571 - val_loss: 0.4668 - val_accuracy: 0.8656
Epoch 18/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4208 - accuracy: 0.8768 - val_loss: 0.4511 - val_accuracy: 0.8525
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4009 - accuracy: 0.8818 - val_loss: 0.5757 - val_accuracy: 0.8164
Epoch 20/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4349 - accuracy: 0.8785 - val_loss: 0.4442 - val_accuracy: 0.8623
Epoch 21/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4808 - accuracy: 0.8719 - val_loss: 0.5649 - val_accuracy: 0.8164
Epoch 22/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4580 - accuracy: 0.8571 - val_loss: 0.4893 - val_accuracy: 0.8230
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4753 - accuracy: 0.8407 - val_loss: 0.7142 - val_accuracy: 0.8164
Epoch 24/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4346 - accuracy: 0.8571 - val_loss: 0.7029 - val_accuracy: 0.8164
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4804 - accuracy: 0.8489 - val_loss: 0.4625 - val_accuracy: 0.8393
Epoch 26/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5030 - accuracy: 0.8210 - val_loss: 1.0798 - val_accuracy: 0.8164
Epoch 27/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5610 - accuracy: 0.8588 - val_loss: 0.4542 - val_accuracy: 0.8525
Epoch 28/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4064 - accuracy: 0.8670 - val_loss: 0.4260 - val_accuracy: 0.8492
Epoch 29/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4093 - accuracy: 0.8588 - val_loss: 0.4411 - val_accuracy: 0.8197
Epoch 30/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4171 - accuracy: 0.8604 - val_loss: 0.4700 - val_accuracy: 0.8393
Epoch 31/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4070 - accuracy: 0.8654 - val_loss: 0.5324 - val_accuracy: 0.8164
Epoch 32/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4023 - accuracy: 0.8555 - val_loss: 0.4072 - val_accuracy: 0.8557
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4377 - accuracy: 0.8588 - val_loss: 0.4535 - val_accuracy: 0.8492
Epoch 34/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6952 - accuracy: 0.8079 - val_loss: 0.6820 - val_accuracy: 0.8164
Epoch 35/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4793 - accuracy: 0.8588 - val_loss: 0.4885 - val_accuracy: 0.8164
Epoch 36/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4285 - accuracy: 0.8654 - val_loss: 0.4224 - val_accuracy: 0.8459
Epoch 37/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4477 - accuracy: 0.8522 - val_loss: 0.4331 - val_accuracy: 0.8262
Epoch 38/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3939 - accuracy: 0.8801 - val_loss: 0.4218 - val_accuracy: 0.8557
Epoch 39/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3984 - accuracy: 0.8670 - val_loss: 0.4654 - val_accuracy: 0.8295
Epoch 40/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4263 - accuracy: 0.8424 - val_loss: 0.4391 - val_accuracy: 0.8262
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7891 - accuracy: 0.6913 - val_loss: 0.8697 - val_accuracy: 0.7508
Epoch 42/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6228 - accuracy: 0.8424 - val_loss: 0.4116 - val_accuracy: 0.8623
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5295 - accuracy: 0.8342 - val_loss: 0.5410 - val_accuracy: 0.8230
Epoch 44/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4158 - accuracy: 0.8752 - val_loss: 0.4305 - val_accuracy: 0.8590
Epoch 45/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4415 - accuracy: 0.8506 - val_loss: 0.4107 - val_accuracy: 0.8525
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4212 - accuracy: 0.8522 - val_loss: 0.4576 - val_accuracy: 0.8525
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4163 - accuracy: 0.8555 - val_loss: 0.4722 - val_accuracy: 0.8164
Epoch 48/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3766 - accuracy: 0.8818 - val_loss: 0.4351 - val_accuracy: 0.8689
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4154 - accuracy: 0.8506 - val_loss: 0.4515 - val_accuracy: 0.8459
Epoch 50/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4074 - accuracy: 0.8539 - val_loss: 0.4399 - val_accuracy: 0.8623
Epoch 51/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4285 - accuracy: 0.8506 - val_loss: 0.5292 - val_accuracy: 0.8164
Epoch 52/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4408 - accuracy: 0.8670 - val_loss: 0.6027 - val_accuracy: 0.7639
Epoch 53/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4469 - accuracy: 0.8555 - val_loss: 0.4869 - val_accuracy: 0.8459
Epoch 54/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4062 - accuracy: 0.8670 - val_loss: 0.5367 - val_accuracy: 0.8295
Epoch 55/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4455 - accuracy: 0.8588 - val_loss: 0.4162 - val_accuracy: 0.8393
Epoch 56/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5190 - accuracy: 0.8424 - val_loss: 0.4207 - val_accuracy: 0.8557
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5184 - accuracy: 0.8292 - val_loss: 0.5265 - val_accuracy: 0.8230
Epoch 58/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4432 - accuracy: 0.8571 - val_loss: 0.5262 - val_accuracy: 0.8066
Epoch 59/100
5/5 [==============================] - 0s 11ms/step - loss: 0.3990 - accuracy: 0.8686 - val_loss: 0.4525 - val_accuracy: 0.8328
Epoch 60/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4171 - accuracy: 0.8522 - val_loss: 0.4500 - val_accuracy: 0.8197
Epoch 61/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4251 - accuracy: 0.8604 - val_loss: 0.4076 - val_accuracy: 0.8557
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4030 - accuracy: 0.8637 - val_loss: 0.5942 - val_accuracy: 0.8164
Epoch 63/100
5/5 [==============================] - 0s 13ms/step - loss: 0.9068 - accuracy: 0.7323 - val_loss: 0.6583 - val_accuracy: 0.8131
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5003 - accuracy: 0.8588 - val_loss: 0.4511 - val_accuracy: 0.8525
Epoch 65/100
5/5 [==============================] - 0s 24ms/step - loss: 0.4213 - accuracy: 0.8555 - val_loss: 0.4561 - val_accuracy: 0.8262
Epoch 66/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4213 - accuracy: 0.8539 - val_loss: 0.4325 - val_accuracy: 0.8230
Epoch 67/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3889 - accuracy: 0.8637 - val_loss: 0.5008 - val_accuracy: 0.8230
Epoch 68/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4087 - accuracy: 0.8654 - val_loss: 0.5238 - val_accuracy: 0.8164
Epoch 69/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4157 - accuracy: 0.8604 - val_loss: 0.4756 - val_accuracy: 0.8164
Epoch 70/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4152 - accuracy: 0.8539 - val_loss: 0.4407 - val_accuracy: 0.8492
Epoch 71/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4734 - accuracy: 0.8489 - val_loss: 0.6237 - val_accuracy: 0.8164
Epoch 72/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5228 - accuracy: 0.8374 - val_loss: 0.4863 - val_accuracy: 0.8164
Epoch 73/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4201 - accuracy: 0.8539 - val_loss: 0.4799 - val_accuracy: 0.8164
Epoch 74/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4121 - accuracy: 0.8686 - val_loss: 0.4495 - val_accuracy: 0.8361
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4531 - accuracy: 0.8473 - val_loss: 0.5269 - val_accuracy: 0.8164
Epoch 76/100
5/5 [==============================] - 0s 11ms/step - loss: 0.3969 - accuracy: 0.8686 - val_loss: 0.4139 - val_accuracy: 0.8623
Epoch 77/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4011 - accuracy: 0.8703 - val_loss: 0.3924 - val_accuracy: 0.8623
Epoch 78/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4344 - accuracy: 0.8571 - val_loss: 0.5565 - val_accuracy: 0.8033
Epoch 79/100
5/5 [==============================] - 0s 9ms/step - loss: 1.2473 - accuracy: 0.6798 - val_loss: 0.7253 - val_accuracy: 0.8164
Epoch 80/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4712 - accuracy: 0.8637 - val_loss: 0.4370 - val_accuracy: 0.8164
Epoch 81/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4159 - accuracy: 0.8588 - val_loss: 0.4255 - val_accuracy: 0.8525
Epoch 82/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3989 - accuracy: 0.8637 - val_loss: 0.4263 - val_accuracy: 0.8295
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4049 - accuracy: 0.8703 - val_loss: 0.5024 - val_accuracy: 0.8164
Epoch 84/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4125 - accuracy: 0.8686 - val_loss: 0.4316 - val_accuracy: 0.8197
Epoch 85/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3965 - accuracy: 0.8703 - val_loss: 0.4912 - val_accuracy: 0.8164
Epoch 86/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4095 - accuracy: 0.8555 - val_loss: 0.5750 - val_accuracy: 0.8164
Epoch 87/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4307 - accuracy: 0.8621 - val_loss: 0.4270 - val_accuracy: 0.8230
Epoch 88/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4087 - accuracy: 0.8539 - val_loss: 0.5844 - val_accuracy: 0.8164
Epoch 89/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4943 - accuracy: 0.8539 - val_loss: 0.5203 - val_accuracy: 0.8131
Epoch 90/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5056 - accuracy: 0.8407 - val_loss: 0.4628 - val_accuracy: 0.8197
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3971 - accuracy: 0.8703 - val_loss: 0.4369 - val_accuracy: 0.8262
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4296 - accuracy: 0.8686 - val_loss: 0.4340 - val_accuracy: 0.8459
Epoch 93/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4191 - accuracy: 0.8473 - val_loss: 0.4778 - val_accuracy: 0.8131
Epoch 94/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4037 - accuracy: 0.8588 - val_loss: 0.4975 - val_accuracy: 0.8393
Epoch 95/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4389 - accuracy: 0.8522 - val_loss: 0.4704 - val_accuracy: 0.8164
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6758 - accuracy: 0.7586 - val_loss: 0.5863 - val_accuracy: 0.8164
Epoch 97/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8451 - accuracy: 0.7915 - val_loss: 0.7831 - val_accuracy: 0.8164
Epoch 98/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4358 - accuracy: 0.8654 - val_loss: 0.4358 - val_accuracy: 0.8557
Epoch 99/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4224 - accuracy: 0.8555 - val_loss: 0.4149 - val_accuracy: 0.8492
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4430 - accuracy: 0.8654 - val_loss: 0.4686 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.9, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 2s 63ms/step - loss: 1.9636 - accuracy: 0.5977 - val_loss: 0.9830 - val_accuracy: 0.8852
Epoch 2/100
5/5 [==============================] - 0s 14ms/step - loss: 1.0010 - accuracy: 0.7915 - val_loss: 0.9924 - val_accuracy: 0.8721
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7204 - accuracy: 0.8473 - val_loss: 0.6165 - val_accuracy: 0.8721
Epoch 4/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6365 - accuracy: 0.8374 - val_loss: 0.6380 - val_accuracy: 0.8721
Epoch 5/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6203 - accuracy: 0.8161 - val_loss: 0.6013 - val_accuracy: 0.8721
Epoch 6/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6178 - accuracy: 0.8292 - val_loss: 0.4472 - val_accuracy: 0.8754
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4990 - accuracy: 0.8358 - val_loss: 0.5986 - val_accuracy: 0.7541
Epoch 8/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8566 - accuracy: 0.7570 - val_loss: 0.4993 - val_accuracy: 0.8689
Epoch 9/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5625 - accuracy: 0.8342 - val_loss: 0.4995 - val_accuracy: 0.8721
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4894 - accuracy: 0.8440 - val_loss: 0.4208 - val_accuracy: 0.8721
Epoch 11/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4928 - accuracy: 0.8473 - val_loss: 0.4714 - val_accuracy: 0.8721
Epoch 12/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7957 - accuracy: 0.7159 - val_loss: 0.5950 - val_accuracy: 0.8721
Epoch 13/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6640 - accuracy: 0.8358 - val_loss: 0.3568 - val_accuracy: 0.9049
Epoch 14/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5083 - accuracy: 0.8391 - val_loss: 0.3984 - val_accuracy: 0.8721
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5091 - accuracy: 0.8342 - val_loss: 0.3426 - val_accuracy: 0.8852
Epoch 16/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4717 - accuracy: 0.8358 - val_loss: 0.4821 - val_accuracy: 0.8721
Epoch 17/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5768 - accuracy: 0.8292 - val_loss: 0.3762 - val_accuracy: 0.8918
Epoch 18/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5045 - accuracy: 0.8243 - val_loss: 0.3600 - val_accuracy: 0.8852
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4851 - accuracy: 0.8456 - val_loss: 0.3715 - val_accuracy: 0.8721
Epoch 20/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4912 - accuracy: 0.8243 - val_loss: 0.3825 - val_accuracy: 0.8885
Epoch 21/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6647 - accuracy: 0.7783 - val_loss: 0.5075 - val_accuracy: 0.8721
Epoch 22/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5724 - accuracy: 0.8391 - val_loss: 0.3863 - val_accuracy: 0.8984
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4705 - accuracy: 0.8473 - val_loss: 0.3797 - val_accuracy: 0.8721
Epoch 24/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5043 - accuracy: 0.8095 - val_loss: 0.4735 - val_accuracy: 0.8721
Epoch 25/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4921 - accuracy: 0.8539 - val_loss: 0.5922 - val_accuracy: 0.8262
Epoch 26/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5627 - accuracy: 0.8177 - val_loss: 0.3842 - val_accuracy: 0.8721
Epoch 27/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5065 - accuracy: 0.8309 - val_loss: 0.3774 - val_accuracy: 0.8656
Epoch 28/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5976 - accuracy: 0.8177 - val_loss: 0.4407 - val_accuracy: 0.8787
Epoch 29/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4909 - accuracy: 0.8489 - val_loss: 0.3876 - val_accuracy: 0.8721
Epoch 30/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4627 - accuracy: 0.8358 - val_loss: 0.3381 - val_accuracy: 0.8885
Epoch 31/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4794 - accuracy: 0.8342 - val_loss: 0.3575 - val_accuracy: 0.8951
Epoch 32/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4557 - accuracy: 0.8391 - val_loss: 0.3475 - val_accuracy: 0.8918
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4799 - accuracy: 0.8391 - val_loss: 0.3507 - val_accuracy: 0.8852
Epoch 34/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4664 - accuracy: 0.8276 - val_loss: 0.5544 - val_accuracy: 0.8721
Epoch 35/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9619 - accuracy: 0.7110 - val_loss: 0.7474 - val_accuracy: 0.7836
Epoch 36/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5691 - accuracy: 0.8259 - val_loss: 0.3989 - val_accuracy: 0.8689
Epoch 37/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4366 - accuracy: 0.8539 - val_loss: 0.3969 - val_accuracy: 0.8525
Epoch 38/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4718 - accuracy: 0.8407 - val_loss: 0.3725 - val_accuracy: 0.8754
Epoch 39/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4361 - accuracy: 0.8489 - val_loss: 0.3902 - val_accuracy: 0.8525
Epoch 40/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4583 - accuracy: 0.8555 - val_loss: 0.3567 - val_accuracy: 0.8918
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4911 - accuracy: 0.8407 - val_loss: 0.3627 - val_accuracy: 0.8820
Epoch 42/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4545 - accuracy: 0.8571 - val_loss: 0.3681 - val_accuracy: 0.8820
Epoch 43/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5609 - accuracy: 0.8062 - val_loss: 0.5135 - val_accuracy: 0.8721
Epoch 44/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5737 - accuracy: 0.8391 - val_loss: 0.3373 - val_accuracy: 0.8918
Epoch 45/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4497 - accuracy: 0.8555 - val_loss: 0.3188 - val_accuracy: 0.8951
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4692 - accuracy: 0.8342 - val_loss: 0.3640 - val_accuracy: 0.8557
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5445 - accuracy: 0.8210 - val_loss: 0.4147 - val_accuracy: 0.8721
Epoch 48/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5544 - accuracy: 0.8309 - val_loss: 0.3932 - val_accuracy: 0.8689
Epoch 49/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4470 - accuracy: 0.8440 - val_loss: 0.3663 - val_accuracy: 0.8951
Epoch 50/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4638 - accuracy: 0.8506 - val_loss: 0.3599 - val_accuracy: 0.8852
Epoch 51/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5551 - accuracy: 0.8374 - val_loss: 0.3917 - val_accuracy: 0.8721
Epoch 52/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5276 - accuracy: 0.8342 - val_loss: 0.3510 - val_accuracy: 0.8852
Epoch 53/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4841 - accuracy: 0.8391 - val_loss: 0.4525 - val_accuracy: 0.8721
Epoch 54/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4867 - accuracy: 0.8473 - val_loss: 0.3376 - val_accuracy: 0.8852
Epoch 55/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4302 - accuracy: 0.8506 - val_loss: 0.3579 - val_accuracy: 0.8754
Epoch 56/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4870 - accuracy: 0.8391 - val_loss: 0.5291 - val_accuracy: 0.8721
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4693 - accuracy: 0.8342 - val_loss: 0.4683 - val_accuracy: 0.8557
Epoch 58/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6028 - accuracy: 0.7964 - val_loss: 0.8995 - val_accuracy: 0.6721
Epoch 59/100
5/5 [==============================] - 0s 15ms/step - loss: 0.6367 - accuracy: 0.7964 - val_loss: 0.4418 - val_accuracy: 0.8721
Epoch 60/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5439 - accuracy: 0.8292 - val_loss: 0.3861 - val_accuracy: 0.8721
Epoch 61/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4767 - accuracy: 0.8407 - val_loss: 0.4071 - val_accuracy: 0.8721
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4435 - accuracy: 0.8456 - val_loss: 0.3691 - val_accuracy: 0.8984
Epoch 63/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4666 - accuracy: 0.8407 - val_loss: 0.3228 - val_accuracy: 0.8885
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4648 - accuracy: 0.8325 - val_loss: 0.3469 - val_accuracy: 0.8918
Epoch 65/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4511 - accuracy: 0.8473 - val_loss: 0.3485 - val_accuracy: 0.9016
Epoch 66/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4577 - accuracy: 0.8374 - val_loss: 0.4207 - val_accuracy: 0.8393
Epoch 67/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9364 - accuracy: 0.6995 - val_loss: 0.6388 - val_accuracy: 0.8721
Epoch 68/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6045 - accuracy: 0.8243 - val_loss: 0.4226 - val_accuracy: 0.8459
Epoch 69/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4843 - accuracy: 0.8391 - val_loss: 0.3647 - val_accuracy: 0.8820
Epoch 70/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4468 - accuracy: 0.8473 - val_loss: 0.3381 - val_accuracy: 0.8918
Epoch 71/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4588 - accuracy: 0.8391 - val_loss: 0.3272 - val_accuracy: 0.8852
Epoch 72/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4229 - accuracy: 0.8604 - val_loss: 0.3750 - val_accuracy: 0.8721
Epoch 73/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4575 - accuracy: 0.8407 - val_loss: 0.3187 - val_accuracy: 0.8918
Epoch 74/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4539 - accuracy: 0.8342 - val_loss: 0.3903 - val_accuracy: 0.8459
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4950 - accuracy: 0.8358 - val_loss: 0.5459 - val_accuracy: 0.7607
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4921 - accuracy: 0.8424 - val_loss: 0.3372 - val_accuracy: 0.8984
Epoch 77/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4495 - accuracy: 0.8489 - val_loss: 0.5164 - val_accuracy: 0.7902
Epoch 78/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5301 - accuracy: 0.8243 - val_loss: 0.4432 - val_accuracy: 0.8787
Epoch 79/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5000 - accuracy: 0.8456 - val_loss: 0.3818 - val_accuracy: 0.8852
Epoch 80/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4572 - accuracy: 0.8374 - val_loss: 0.3394 - val_accuracy: 0.8885
Epoch 81/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4659 - accuracy: 0.8424 - val_loss: 0.4288 - val_accuracy: 0.8721
Epoch 82/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5091 - accuracy: 0.8342 - val_loss: 0.3653 - val_accuracy: 0.8951
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4444 - accuracy: 0.8456 - val_loss: 0.4017 - val_accuracy: 0.8459
Epoch 84/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4564 - accuracy: 0.8407 - val_loss: 0.4145 - val_accuracy: 0.8721
Epoch 85/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5450 - accuracy: 0.8342 - val_loss: 0.4364 - val_accuracy: 0.8361
Epoch 86/100
5/5 [==============================] - 0s 10ms/step - loss: 0.7310 - accuracy: 0.7750 - val_loss: 0.4474 - val_accuracy: 0.8721
Epoch 87/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4777 - accuracy: 0.8440 - val_loss: 0.3234 - val_accuracy: 0.8951
Epoch 88/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4321 - accuracy: 0.8621 - val_loss: 0.3955 - val_accuracy: 0.8721
Epoch 89/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4583 - accuracy: 0.8358 - val_loss: 0.4055 - val_accuracy: 0.8721
Epoch 90/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4606 - accuracy: 0.8456 - val_loss: 0.3496 - val_accuracy: 0.8721
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4541 - accuracy: 0.8259 - val_loss: 0.4352 - val_accuracy: 0.8721
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4991 - accuracy: 0.8325 - val_loss: 0.4605 - val_accuracy: 0.8689
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6582 - accuracy: 0.8276 - val_loss: 0.4002 - val_accuracy: 0.8328
Epoch 94/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5186 - accuracy: 0.8325 - val_loss: 0.3246 - val_accuracy: 0.8820
Epoch 95/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4401 - accuracy: 0.8358 - val_loss: 0.3318 - val_accuracy: 0.8820
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4692 - accuracy: 0.8555 - val_loss: 0.3448 - val_accuracy: 0.8787
Epoch 97/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4464 - accuracy: 0.8358 - val_loss: 0.3493 - val_accuracy: 0.8820
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4424 - accuracy: 0.8588 - val_loss: 0.3842 - val_accuracy: 0.8426
Epoch 99/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5129 - accuracy: 0.8391 - val_loss: 0.3804 - val_accuracy: 0.8984
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6431 - accuracy: 0.8276 - val_loss: 0.5074 - val_accuracy: 0.8066
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.9, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
5/5 [==============================] - 1s 66ms/step - loss: 2.4968 - accuracy: 0.6016 - val_loss: 1.3125 - val_accuracy: 0.8421
Epoch 2/100
5/5 [==============================] - 0s 12ms/step - loss: 1.0249 - accuracy: 0.8311 - val_loss: 1.0044 - val_accuracy: 0.7467
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8265 - accuracy: 0.8213 - val_loss: 0.8214 - val_accuracy: 0.8421
Epoch 4/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6477 - accuracy: 0.8590 - val_loss: 0.6202 - val_accuracy: 0.8520
Epoch 5/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5901 - accuracy: 0.8672 - val_loss: 0.5606 - val_accuracy: 0.8322
Epoch 6/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5197 - accuracy: 0.8574 - val_loss: 0.6057 - val_accuracy: 0.8553
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5033 - accuracy: 0.8721 - val_loss: 0.6534 - val_accuracy: 0.8586
Epoch 8/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5640 - accuracy: 0.8525 - val_loss: 0.5848 - val_accuracy: 0.8059
Epoch 9/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4819 - accuracy: 0.8689 - val_loss: 0.5225 - val_accuracy: 0.8618
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4410 - accuracy: 0.8639 - val_loss: 0.4803 - val_accuracy: 0.8553
Epoch 11/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4509 - accuracy: 0.8574 - val_loss: 0.7025 - val_accuracy: 0.8618
Epoch 12/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6244 - accuracy: 0.8246 - val_loss: 0.6260 - val_accuracy: 0.8059
Epoch 13/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4689 - accuracy: 0.8607 - val_loss: 0.5010 - val_accuracy: 0.8355
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4746 - accuracy: 0.8492 - val_loss: 0.4936 - val_accuracy: 0.8355
Epoch 15/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4601 - accuracy: 0.8623 - val_loss: 0.4788 - val_accuracy: 0.8322
Epoch 16/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4130 - accuracy: 0.8623 - val_loss: 0.6502 - val_accuracy: 0.7336
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6109 - accuracy: 0.8164 - val_loss: 0.6391 - val_accuracy: 0.8355
Epoch 18/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5505 - accuracy: 0.8475 - val_loss: 0.5154 - val_accuracy: 0.8191
Epoch 19/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4168 - accuracy: 0.8574 - val_loss: 0.4791 - val_accuracy: 0.8520
Epoch 20/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4357 - accuracy: 0.8623 - val_loss: 0.4836 - val_accuracy: 0.8618
Epoch 21/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4040 - accuracy: 0.8705 - val_loss: 0.6903 - val_accuracy: 0.7763
Epoch 22/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4880 - accuracy: 0.8443 - val_loss: 0.6207 - val_accuracy: 0.7796
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4225 - accuracy: 0.8689 - val_loss: 0.5170 - val_accuracy: 0.8059
Epoch 24/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4159 - accuracy: 0.8492 - val_loss: 0.5211 - val_accuracy: 0.8257
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5390 - accuracy: 0.8443 - val_loss: 0.5376 - val_accuracy: 0.8322
Epoch 26/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3996 - accuracy: 0.8852 - val_loss: 0.5314 - val_accuracy: 0.8125
Epoch 27/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5320 - accuracy: 0.8295 - val_loss: 0.5928 - val_accuracy: 0.8618
Epoch 28/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4817 - accuracy: 0.8459 - val_loss: 0.6951 - val_accuracy: 0.7697
Epoch 29/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4371 - accuracy: 0.8623 - val_loss: 0.4895 - val_accuracy: 0.8421
Epoch 30/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4213 - accuracy: 0.8672 - val_loss: 0.5072 - val_accuracy: 0.8191
Epoch 31/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4997 - accuracy: 0.8393 - val_loss: 0.6059 - val_accuracy: 0.7697
Epoch 32/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4213 - accuracy: 0.8557 - val_loss: 0.6607 - val_accuracy: 0.7566
Epoch 33/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6002 - accuracy: 0.7672 - val_loss: 0.6838 - val_accuracy: 0.8520
Epoch 34/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4778 - accuracy: 0.8639 - val_loss: 0.5843 - val_accuracy: 0.7862
Epoch 35/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4713 - accuracy: 0.8590 - val_loss: 0.5462 - val_accuracy: 0.7993
Epoch 36/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3916 - accuracy: 0.8672 - val_loss: 0.6550 - val_accuracy: 0.7697
Epoch 37/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4021 - accuracy: 0.8672 - val_loss: 0.5033 - val_accuracy: 0.8322
Epoch 38/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4057 - accuracy: 0.8590 - val_loss: 0.6621 - val_accuracy: 0.7664
Epoch 39/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4370 - accuracy: 0.8508 - val_loss: 0.6954 - val_accuracy: 0.7368
Epoch 40/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4742 - accuracy: 0.8508 - val_loss: 0.5205 - val_accuracy: 0.8289
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4282 - accuracy: 0.8639 - val_loss: 0.4439 - val_accuracy: 0.8553
Epoch 42/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4035 - accuracy: 0.8623 - val_loss: 0.7878 - val_accuracy: 0.7336
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4071 - accuracy: 0.8639 - val_loss: 0.7825 - val_accuracy: 0.7566
Epoch 44/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4648 - accuracy: 0.8672 - val_loss: 0.4512 - val_accuracy: 0.8520
Epoch 45/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3940 - accuracy: 0.8754 - val_loss: 0.6147 - val_accuracy: 0.7664
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4081 - accuracy: 0.8689 - val_loss: 0.4452 - val_accuracy: 0.8322
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5042 - accuracy: 0.8098 - val_loss: 1.4678 - val_accuracy: 0.6447
Epoch 48/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7043 - accuracy: 0.8131 - val_loss: 0.6270 - val_accuracy: 0.8026
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4264 - accuracy: 0.8590 - val_loss: 0.4794 - val_accuracy: 0.8289
Epoch 50/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3992 - accuracy: 0.8689 - val_loss: 0.4722 - val_accuracy: 0.8388
Epoch 51/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3765 - accuracy: 0.8639 - val_loss: 0.8115 - val_accuracy: 0.7138
Epoch 52/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4091 - accuracy: 0.8475 - val_loss: 0.4397 - val_accuracy: 0.8553
Epoch 53/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4512 - accuracy: 0.8377 - val_loss: 0.4973 - val_accuracy: 0.8092
Epoch 54/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4246 - accuracy: 0.8574 - val_loss: 0.6803 - val_accuracy: 0.7500
Epoch 55/100
5/5 [==============================] - 0s 11ms/step - loss: 0.3928 - accuracy: 0.8623 - val_loss: 0.5226 - val_accuracy: 0.8092
Epoch 56/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4266 - accuracy: 0.8623 - val_loss: 0.7137 - val_accuracy: 0.7599
Epoch 57/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7182 - accuracy: 0.7574 - val_loss: 0.5902 - val_accuracy: 0.8059
Epoch 58/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5019 - accuracy: 0.8557 - val_loss: 0.5861 - val_accuracy: 0.8125
Epoch 59/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4379 - accuracy: 0.8492 - val_loss: 0.8278 - val_accuracy: 0.7500
Epoch 60/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4152 - accuracy: 0.8639 - val_loss: 0.8888 - val_accuracy: 0.7270
Epoch 61/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4445 - accuracy: 0.8443 - val_loss: 0.4530 - val_accuracy: 0.8322
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4008 - accuracy: 0.8623 - val_loss: 0.4525 - val_accuracy: 0.8322
Epoch 63/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4050 - accuracy: 0.8639 - val_loss: 0.5397 - val_accuracy: 0.7730
Epoch 64/100
5/5 [==============================] - 0s 23ms/step - loss: 0.3848 - accuracy: 0.8459 - val_loss: 0.7421 - val_accuracy: 0.7237
Epoch 65/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3767 - accuracy: 0.8705 - val_loss: 0.4914 - val_accuracy: 0.8289
Epoch 66/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4146 - accuracy: 0.8721 - val_loss: 0.4474 - val_accuracy: 0.8454
Epoch 67/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4710 - accuracy: 0.8475 - val_loss: 1.4046 - val_accuracy: 0.6743
Epoch 68/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6746 - accuracy: 0.8246 - val_loss: 0.5525 - val_accuracy: 0.8322
Epoch 69/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4565 - accuracy: 0.8344 - val_loss: 0.6222 - val_accuracy: 0.7566
Epoch 70/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4047 - accuracy: 0.8541 - val_loss: 0.6711 - val_accuracy: 0.7632
Epoch 71/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4419 - accuracy: 0.8623 - val_loss: 0.4433 - val_accuracy: 0.8586
Epoch 72/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4211 - accuracy: 0.8525 - val_loss: 0.4393 - val_accuracy: 0.8586
Epoch 73/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5195 - accuracy: 0.8361 - val_loss: 0.8125 - val_accuracy: 0.6776
Epoch 74/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5412 - accuracy: 0.8311 - val_loss: 0.9385 - val_accuracy: 0.6743
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4449 - accuracy: 0.8459 - val_loss: 0.4308 - val_accuracy: 0.8487
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3952 - accuracy: 0.8574 - val_loss: 0.7077 - val_accuracy: 0.7237
Epoch 77/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4171 - accuracy: 0.8525 - val_loss: 0.6215 - val_accuracy: 0.7500
Epoch 78/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4012 - accuracy: 0.8557 - val_loss: 0.4290 - val_accuracy: 0.8618
Epoch 79/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4162 - accuracy: 0.8557 - val_loss: 0.4887 - val_accuracy: 0.8289
Epoch 80/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4281 - accuracy: 0.8475 - val_loss: 0.5778 - val_accuracy: 0.7763
Epoch 81/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7704 - accuracy: 0.7377 - val_loss: 2.2117 - val_accuracy: 0.5691
Epoch 82/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6110 - accuracy: 0.8361 - val_loss: 0.5471 - val_accuracy: 0.8191
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4067 - accuracy: 0.8639 - val_loss: 0.5295 - val_accuracy: 0.8158
Epoch 84/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3895 - accuracy: 0.8705 - val_loss: 0.5093 - val_accuracy: 0.7928
Epoch 85/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3828 - accuracy: 0.8721 - val_loss: 0.4910 - val_accuracy: 0.8224
Epoch 86/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4021 - accuracy: 0.8541 - val_loss: 0.6576 - val_accuracy: 0.7401
Epoch 87/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3782 - accuracy: 0.8754 - val_loss: 0.5087 - val_accuracy: 0.8026
Epoch 88/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4170 - accuracy: 0.8492 - val_loss: 0.4368 - val_accuracy: 0.8553
Epoch 89/100
5/5 [==============================] - 0s 11ms/step - loss: 0.3978 - accuracy: 0.8639 - val_loss: 0.5136 - val_accuracy: 0.7895
Epoch 90/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4210 - accuracy: 0.8574 - val_loss: 0.7595 - val_accuracy: 0.7237
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5465 - accuracy: 0.8066 - val_loss: 0.6539 - val_accuracy: 0.8586
Epoch 92/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7044 - accuracy: 0.8016 - val_loss: 0.5845 - val_accuracy: 0.7895
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4390 - accuracy: 0.8607 - val_loss: 0.4673 - val_accuracy: 0.8289
Epoch 94/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4018 - accuracy: 0.8656 - val_loss: 0.4431 - val_accuracy: 0.8553
Epoch 95/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3893 - accuracy: 0.8656 - val_loss: 0.4514 - val_accuracy: 0.8487
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3743 - accuracy: 0.8787 - val_loss: 0.4749 - val_accuracy: 0.8191
Epoch 97/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3719 - accuracy: 0.8705 - val_loss: 0.6027 - val_accuracy: 0.7862
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3742 - accuracy: 0.8623 - val_loss: 0.4397 - val_accuracy: 0.8454
Epoch 99/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4475 - accuracy: 0.8508 - val_loss: 0.7339 - val_accuracy: 0.7796
Epoch 100/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4234 - accuracy: 0.8590 - val_loss: 0.6033 - val_accuracy: 0.7697
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 2
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 259ms/step - loss: 4.4416 - accuracy: 0.3317 - val_loss: 3.9847 - val_accuracy: 0.2984
Epoch 2/100
2/2 [==============================] - 0s 37ms/step - loss: 4.2902 - accuracy: 0.3366 - val_loss: 3.8031 - val_accuracy: 0.5344
Epoch 3/100
2/2 [==============================] - 0s 40ms/step - loss: 4.0322 - accuracy: 0.4483 - val_loss: 3.5508 - val_accuracy: 0.7344
Epoch 4/100
2/2 [==============================] - 0s 38ms/step - loss: 3.7150 - accuracy: 0.5287 - val_loss: 3.2593 - val_accuracy: 0.8262
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 3.3913 - accuracy: 0.6486 - val_loss: 2.9510 - val_accuracy: 0.8393
Epoch 6/100
2/2 [==============================] - 0s 41ms/step - loss: 3.1050 - accuracy: 0.7011 - val_loss: 2.6412 - val_accuracy: 0.8230
Epoch 7/100
2/2 [==============================] - 0s 37ms/step - loss: 2.8125 - accuracy: 0.7406 - val_loss: 2.3454 - val_accuracy: 0.8295
Epoch 8/100
2/2 [==============================] - 0s 43ms/step - loss: 2.4921 - accuracy: 0.7668 - val_loss: 2.0740 - val_accuracy: 0.8230
Epoch 9/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1853 - accuracy: 0.7947 - val_loss: 1.8368 - val_accuracy: 0.8164
Epoch 10/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8700 - accuracy: 0.7964 - val_loss: 1.6367 - val_accuracy: 0.8164
Epoch 11/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5473 - accuracy: 0.8276 - val_loss: 1.4708 - val_accuracy: 0.8164
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3018 - accuracy: 0.8555 - val_loss: 1.3346 - val_accuracy: 0.8164
Epoch 13/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1015 - accuracy: 0.8686 - val_loss: 1.2262 - val_accuracy: 0.8164
Epoch 14/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9433 - accuracy: 0.8670 - val_loss: 1.1410 - val_accuracy: 0.8164
Epoch 15/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8685 - accuracy: 0.8654 - val_loss: 1.0847 - val_accuracy: 0.8164
Epoch 16/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7641 - accuracy: 0.8654 - val_loss: 1.0749 - val_accuracy: 0.8164
Epoch 17/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6974 - accuracy: 0.8719 - val_loss: 1.1290 - val_accuracy: 0.8164
Epoch 18/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7333 - accuracy: 0.8736 - val_loss: 1.2302 - val_accuracy: 0.8164
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8216 - accuracy: 0.8670 - val_loss: 1.3488 - val_accuracy: 0.8164
Epoch 20/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9570 - accuracy: 0.8654 - val_loss: 1.4748 - val_accuracy: 0.8164
Epoch 21/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1202 - accuracy: 0.8670 - val_loss: 1.5968 - val_accuracy: 0.8164
Epoch 22/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2528 - accuracy: 0.8752 - val_loss: 1.7114 - val_accuracy: 0.8164
Epoch 23/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3893 - accuracy: 0.8637 - val_loss: 1.8155 - val_accuracy: 0.8164
Epoch 24/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5444 - accuracy: 0.8621 - val_loss: 1.9061 - val_accuracy: 0.8164
Epoch 25/100
2/2 [==============================] - 0s 36ms/step - loss: 1.6400 - accuracy: 0.8736 - val_loss: 1.9832 - val_accuracy: 0.8164
Epoch 26/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8369 - accuracy: 0.8440 - val_loss: 2.0523 - val_accuracy: 0.8164
Epoch 27/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9238 - accuracy: 0.8391 - val_loss: 2.1138 - val_accuracy: 0.8164
Epoch 28/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0183 - accuracy: 0.8456 - val_loss: 2.1641 - val_accuracy: 0.8164
Epoch 29/100
2/2 [==============================] - 0s 42ms/step - loss: 2.1085 - accuracy: 0.8062 - val_loss: 2.1989 - val_accuracy: 0.8164
Epoch 30/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1601 - accuracy: 0.8243 - val_loss: 2.2127 - val_accuracy: 0.8164
Epoch 31/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1644 - accuracy: 0.8325 - val_loss: 2.2044 - val_accuracy: 0.8164
Epoch 32/100
2/2 [==============================] - 0s 41ms/step - loss: 2.1113 - accuracy: 0.8489 - val_loss: 2.1797 - val_accuracy: 0.8164
Epoch 33/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0456 - accuracy: 0.8637 - val_loss: 2.1443 - val_accuracy: 0.8164
Epoch 34/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9493 - accuracy: 0.8637 - val_loss: 2.0969 - val_accuracy: 0.8164
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8654 - accuracy: 0.8736 - val_loss: 2.0334 - val_accuracy: 0.8164
Epoch 36/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7781 - accuracy: 0.8736 - val_loss: 1.9527 - val_accuracy: 0.8164
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 1.6240 - accuracy: 0.8768 - val_loss: 1.8571 - val_accuracy: 0.8164
Epoch 38/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5259 - accuracy: 0.8736 - val_loss: 1.7514 - val_accuracy: 0.8164
Epoch 39/100
2/2 [==============================] - 0s 70ms/step - loss: 1.3924 - accuracy: 0.8834 - val_loss: 1.6347 - val_accuracy: 0.8164
Epoch 40/100
2/2 [==============================] - 0s 29ms/step - loss: 1.2363 - accuracy: 0.8818 - val_loss: 1.5088 - val_accuracy: 0.8164
Epoch 41/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1375 - accuracy: 0.8686 - val_loss: 1.3948 - val_accuracy: 0.8164
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0544 - accuracy: 0.8621 - val_loss: 1.2988 - val_accuracy: 0.8164
Epoch 43/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9201 - accuracy: 0.8654 - val_loss: 1.2249 - val_accuracy: 0.8164
Epoch 44/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8091 - accuracy: 0.8719 - val_loss: 1.1831 - val_accuracy: 0.8164
Epoch 45/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7307 - accuracy: 0.8736 - val_loss: 1.1517 - val_accuracy: 0.8164
Epoch 46/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7675 - accuracy: 0.8703 - val_loss: 1.1079 - val_accuracy: 0.8164
Epoch 47/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7064 - accuracy: 0.8801 - val_loss: 1.0610 - val_accuracy: 0.8164
Epoch 48/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7039 - accuracy: 0.8703 - val_loss: 1.0344 - val_accuracy: 0.8164
Epoch 49/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8181 - accuracy: 0.8374 - val_loss: 1.0473 - val_accuracy: 0.8164
Epoch 50/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8581 - accuracy: 0.8407 - val_loss: 1.0974 - val_accuracy: 0.8164
Epoch 51/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9740 - accuracy: 0.8243 - val_loss: 1.1736 - val_accuracy: 0.8164
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0573 - accuracy: 0.8177 - val_loss: 1.2672 - val_accuracy: 0.8164
Epoch 53/100
2/2 [==============================] - 0s 49ms/step - loss: 1.1389 - accuracy: 0.8243 - val_loss: 1.3666 - val_accuracy: 0.8164
Epoch 54/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2433 - accuracy: 0.8506 - val_loss: 1.4700 - val_accuracy: 0.8164
Epoch 55/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3445 - accuracy: 0.8571 - val_loss: 1.5518 - val_accuracy: 0.8164
Epoch 56/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3704 - accuracy: 0.8506 - val_loss: 1.5912 - val_accuracy: 0.8164
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 1.4029 - accuracy: 0.8506 - val_loss: 1.5987 - val_accuracy: 0.8164
Epoch 58/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4269 - accuracy: 0.8736 - val_loss: 1.5909 - val_accuracy: 0.8164
Epoch 59/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4455 - accuracy: 0.8440 - val_loss: 1.5816 - val_accuracy: 0.8164
Epoch 60/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4103 - accuracy: 0.8670 - val_loss: 1.5789 - val_accuracy: 0.8164
Epoch 61/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4473 - accuracy: 0.8424 - val_loss: 1.5817 - val_accuracy: 0.8164
Epoch 62/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3997 - accuracy: 0.8703 - val_loss: 1.5814 - val_accuracy: 0.8164
Epoch 63/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3754 - accuracy: 0.8670 - val_loss: 1.5678 - val_accuracy: 0.8164
Epoch 64/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3266 - accuracy: 0.8752 - val_loss: 1.5426 - val_accuracy: 0.8164
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2802 - accuracy: 0.8834 - val_loss: 1.4948 - val_accuracy: 0.8164
Epoch 66/100
2/2 [==============================] - 0s 38ms/step - loss: 1.2039 - accuracy: 0.8670 - val_loss: 1.4205 - val_accuracy: 0.8164
Epoch 67/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1638 - accuracy: 0.8703 - val_loss: 1.3433 - val_accuracy: 0.8164
Epoch 68/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0950 - accuracy: 0.8736 - val_loss: 1.2624 - val_accuracy: 0.8164
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9843 - accuracy: 0.8785 - val_loss: 1.1743 - val_accuracy: 0.8164
Epoch 70/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9499 - accuracy: 0.8801 - val_loss: 1.0976 - val_accuracy: 0.8164
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8716 - accuracy: 0.8654 - val_loss: 1.0406 - val_accuracy: 0.8164
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8286 - accuracy: 0.8686 - val_loss: 1.0044 - val_accuracy: 0.8164
Epoch 73/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7647 - accuracy: 0.8719 - val_loss: 0.9727 - val_accuracy: 0.8164
Epoch 74/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7076 - accuracy: 0.8834 - val_loss: 0.9381 - val_accuracy: 0.8164
Epoch 75/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6876 - accuracy: 0.8621 - val_loss: 0.9200 - val_accuracy: 0.8164
Epoch 76/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6690 - accuracy: 0.8703 - val_loss: 0.9313 - val_accuracy: 0.8164
Epoch 77/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7009 - accuracy: 0.8768 - val_loss: 0.9614 - val_accuracy: 0.8164
Epoch 78/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7625 - accuracy: 0.8555 - val_loss: 1.0050 - val_accuracy: 0.8164
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7410 - accuracy: 0.8719 - val_loss: 1.0576 - val_accuracy: 0.8164
Epoch 80/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8146 - accuracy: 0.8604 - val_loss: 1.0940 - val_accuracy: 0.8164
Epoch 81/100
2/2 [==============================] - 0s 43ms/step - loss: 0.8276 - accuracy: 0.8703 - val_loss: 1.0990 - val_accuracy: 0.8164
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8527 - accuracy: 0.8752 - val_loss: 1.0889 - val_accuracy: 0.8164
Epoch 83/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9020 - accuracy: 0.8654 - val_loss: 1.0814 - val_accuracy: 0.8164
Epoch 84/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9519 - accuracy: 0.8522 - val_loss: 1.0886 - val_accuracy: 0.8164
Epoch 85/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0060 - accuracy: 0.8555 - val_loss: 1.1174 - val_accuracy: 0.8164
Epoch 86/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0272 - accuracy: 0.8522 - val_loss: 1.1648 - val_accuracy: 0.8164
Epoch 87/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9926 - accuracy: 0.8604 - val_loss: 1.2240 - val_accuracy: 0.8164
Epoch 88/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0446 - accuracy: 0.8686 - val_loss: 1.2717 - val_accuracy: 0.8164
Epoch 89/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0747 - accuracy: 0.8621 - val_loss: 1.2885 - val_accuracy: 0.8164
Epoch 90/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0488 - accuracy: 0.8654 - val_loss: 1.2547 - val_accuracy: 0.8164
Epoch 91/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0118 - accuracy: 0.8555 - val_loss: 1.1870 - val_accuracy: 0.8164
Epoch 92/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9449 - accuracy: 0.8785 - val_loss: 1.1009 - val_accuracy: 0.8164
Epoch 93/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9682 - accuracy: 0.8506 - val_loss: 1.0480 - val_accuracy: 0.8164
Epoch 94/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9867 - accuracy: 0.8276 - val_loss: 1.0485 - val_accuracy: 0.8164
Epoch 95/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9380 - accuracy: 0.8440 - val_loss: 1.1240 - val_accuracy: 0.8164
Epoch 96/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8812 - accuracy: 0.8604 - val_loss: 1.2381 - val_accuracy: 0.8164
Epoch 97/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8867 - accuracy: 0.8752 - val_loss: 1.3058 - val_accuracy: 0.8164
Epoch 98/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9267 - accuracy: 0.8654 - val_loss: 1.2834 - val_accuracy: 0.8164
Epoch 99/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8866 - accuracy: 0.8736 - val_loss: 1.1674 - val_accuracy: 0.8164
Epoch 100/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8307 - accuracy: 0.8637 - val_loss: 0.9995 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 255ms/step - loss: 4.2106 - accuracy: 0.4302 - val_loss: 3.7430 - val_accuracy: 0.4885
Epoch 2/100
2/2 [==============================] - 0s 41ms/step - loss: 4.1404 - accuracy: 0.4581 - val_loss: 3.5763 - val_accuracy: 0.6328
Epoch 3/100
2/2 [==============================] - 0s 40ms/step - loss: 3.9844 - accuracy: 0.4417 - val_loss: 3.3415 - val_accuracy: 0.8098
Epoch 4/100
2/2 [==============================] - 0s 40ms/step - loss: 3.6425 - accuracy: 0.5452 - val_loss: 3.0633 - val_accuracy: 0.8623
Epoch 5/100
2/2 [==============================] - 0s 40ms/step - loss: 3.2579 - accuracy: 0.6585 - val_loss: 2.7664 - val_accuracy: 0.8787
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 2.9358 - accuracy: 0.7028 - val_loss: 2.4710 - val_accuracy: 0.8721
Epoch 7/100
2/2 [==============================] - 0s 40ms/step - loss: 2.6186 - accuracy: 0.7471 - val_loss: 2.1902 - val_accuracy: 0.8721
Epoch 8/100
2/2 [==============================] - 0s 40ms/step - loss: 2.3666 - accuracy: 0.7422 - val_loss: 1.9303 - val_accuracy: 0.8721
Epoch 9/100
2/2 [==============================] - 0s 42ms/step - loss: 2.0833 - accuracy: 0.7997 - val_loss: 1.6905 - val_accuracy: 0.8721
Epoch 10/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7393 - accuracy: 0.8358 - val_loss: 1.4717 - val_accuracy: 0.8721
Epoch 11/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5377 - accuracy: 0.8374 - val_loss: 1.2759 - val_accuracy: 0.8721
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3052 - accuracy: 0.8407 - val_loss: 1.1079 - val_accuracy: 0.8721
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1102 - accuracy: 0.8473 - val_loss: 0.9729 - val_accuracy: 0.8721
Epoch 14/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9388 - accuracy: 0.8670 - val_loss: 0.8762 - val_accuracy: 0.8721
Epoch 15/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8117 - accuracy: 0.8571 - val_loss: 0.8208 - val_accuracy: 0.8721
Epoch 16/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7625 - accuracy: 0.8473 - val_loss: 0.8218 - val_accuracy: 0.8721
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7743 - accuracy: 0.8456 - val_loss: 0.8782 - val_accuracy: 0.8721
Epoch 18/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8611 - accuracy: 0.8407 - val_loss: 0.9712 - val_accuracy: 0.8721
Epoch 19/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9503 - accuracy: 0.8407 - val_loss: 1.0799 - val_accuracy: 0.8721
Epoch 20/100
2/2 [==============================] - 0s 40ms/step - loss: 1.0183 - accuracy: 0.8456 - val_loss: 1.1930 - val_accuracy: 0.8721
Epoch 21/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1634 - accuracy: 0.8407 - val_loss: 1.3066 - val_accuracy: 0.8721
Epoch 22/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2751 - accuracy: 0.8489 - val_loss: 1.4173 - val_accuracy: 0.8721
Epoch 23/100
2/2 [==============================] - 0s 39ms/step - loss: 1.4025 - accuracy: 0.8539 - val_loss: 1.5243 - val_accuracy: 0.8721
Epoch 24/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5356 - accuracy: 0.8374 - val_loss: 1.6246 - val_accuracy: 0.8721
Epoch 25/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6883 - accuracy: 0.8374 - val_loss: 1.7170 - val_accuracy: 0.8721
Epoch 26/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7967 - accuracy: 0.8325 - val_loss: 1.8025 - val_accuracy: 0.8721
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 1.8912 - accuracy: 0.8194 - val_loss: 1.8818 - val_accuracy: 0.8721
Epoch 28/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9879 - accuracy: 0.8112 - val_loss: 1.9495 - val_accuracy: 0.8721
Epoch 29/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0344 - accuracy: 0.8046 - val_loss: 1.9950 - val_accuracy: 0.8721
Epoch 30/100
2/2 [==============================] - 0s 42ms/step - loss: 2.0810 - accuracy: 0.8112 - val_loss: 2.0074 - val_accuracy: 0.8721
Epoch 31/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0660 - accuracy: 0.8292 - val_loss: 1.9829 - val_accuracy: 0.8721
Epoch 32/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0370 - accuracy: 0.8309 - val_loss: 1.9329 - val_accuracy: 0.8721
Epoch 33/100
2/2 [==============================] - 0s 41ms/step - loss: 1.9785 - accuracy: 0.8391 - val_loss: 1.8709 - val_accuracy: 0.8721
Epoch 34/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8817 - accuracy: 0.8440 - val_loss: 1.8043 - val_accuracy: 0.8721
Epoch 35/100
2/2 [==============================] - 0s 41ms/step - loss: 1.7979 - accuracy: 0.8506 - val_loss: 1.7293 - val_accuracy: 0.8721
Epoch 36/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7402 - accuracy: 0.8424 - val_loss: 1.6400 - val_accuracy: 0.8721
Epoch 37/100
2/2 [==============================] - 0s 39ms/step - loss: 1.6119 - accuracy: 0.8407 - val_loss: 1.5363 - val_accuracy: 0.8721
Epoch 38/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4832 - accuracy: 0.8473 - val_loss: 1.4210 - val_accuracy: 0.8721
Epoch 39/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3625 - accuracy: 0.8506 - val_loss: 1.3037 - val_accuracy: 0.8721
Epoch 40/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2259 - accuracy: 0.8588 - val_loss: 1.1904 - val_accuracy: 0.8721
Epoch 41/100
2/2 [==============================] - 0s 42ms/step - loss: 1.1058 - accuracy: 0.8506 - val_loss: 1.0839 - val_accuracy: 0.8721
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0087 - accuracy: 0.8456 - val_loss: 0.9899 - val_accuracy: 0.8721
Epoch 43/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9041 - accuracy: 0.8621 - val_loss: 0.9200 - val_accuracy: 0.8721
Epoch 44/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8419 - accuracy: 0.8489 - val_loss: 0.8702 - val_accuracy: 0.8721
Epoch 45/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8093 - accuracy: 0.8391 - val_loss: 0.8305 - val_accuracy: 0.8721
Epoch 46/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7977 - accuracy: 0.8473 - val_loss: 0.7942 - val_accuracy: 0.8721
Epoch 47/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7842 - accuracy: 0.8522 - val_loss: 0.7610 - val_accuracy: 0.8721
Epoch 48/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8085 - accuracy: 0.8325 - val_loss: 0.7479 - val_accuracy: 0.8721
Epoch 49/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8545 - accuracy: 0.8128 - val_loss: 0.7814 - val_accuracy: 0.8721
Epoch 50/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9035 - accuracy: 0.8095 - val_loss: 0.8447 - val_accuracy: 0.8721
Epoch 51/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9646 - accuracy: 0.8210 - val_loss: 0.9178 - val_accuracy: 0.8721
Epoch 52/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0011 - accuracy: 0.8456 - val_loss: 0.9923 - val_accuracy: 0.8721
Epoch 53/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1129 - accuracy: 0.8144 - val_loss: 1.0650 - val_accuracy: 0.8721
Epoch 54/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1684 - accuracy: 0.8309 - val_loss: 1.1338 - val_accuracy: 0.8721
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 1.2186 - accuracy: 0.8456 - val_loss: 1.1922 - val_accuracy: 0.8721
Epoch 56/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2621 - accuracy: 0.8473 - val_loss: 1.2342 - val_accuracy: 0.8721
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2636 - accuracy: 0.8391 - val_loss: 1.2644 - val_accuracy: 0.8721
Epoch 58/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3071 - accuracy: 0.8391 - val_loss: 1.2814 - val_accuracy: 0.8721
Epoch 59/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3207 - accuracy: 0.8456 - val_loss: 1.2873 - val_accuracy: 0.8721
Epoch 60/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2895 - accuracy: 0.8456 - val_loss: 1.2839 - val_accuracy: 0.8721
Epoch 61/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3116 - accuracy: 0.8391 - val_loss: 1.2727 - val_accuracy: 0.8721
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 1.2948 - accuracy: 0.8473 - val_loss: 1.2584 - val_accuracy: 0.8721
Epoch 63/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2513 - accuracy: 0.8506 - val_loss: 1.2428 - val_accuracy: 0.8721
Epoch 64/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2228 - accuracy: 0.8555 - val_loss: 1.2169 - val_accuracy: 0.8721
Epoch 65/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1806 - accuracy: 0.8539 - val_loss: 1.1734 - val_accuracy: 0.8721
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1561 - accuracy: 0.8473 - val_loss: 1.1181 - val_accuracy: 0.8721
Epoch 67/100
2/2 [==============================] - 0s 42ms/step - loss: 1.1241 - accuracy: 0.8407 - val_loss: 1.0584 - val_accuracy: 0.8721
Epoch 68/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0467 - accuracy: 0.8473 - val_loss: 0.9911 - val_accuracy: 0.8721
Epoch 69/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9835 - accuracy: 0.8456 - val_loss: 0.9244 - val_accuracy: 0.8721
Epoch 70/100
2/2 [==============================] - 0s 29ms/step - loss: 0.9312 - accuracy: 0.8374 - val_loss: 0.8717 - val_accuracy: 0.8721
Epoch 71/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8764 - accuracy: 0.8506 - val_loss: 0.8399 - val_accuracy: 0.8721
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8482 - accuracy: 0.8259 - val_loss: 0.8207 - val_accuracy: 0.8721
Epoch 73/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8222 - accuracy: 0.8407 - val_loss: 0.7996 - val_accuracy: 0.8721
Epoch 74/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7866 - accuracy: 0.8506 - val_loss: 0.7701 - val_accuracy: 0.8721
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7576 - accuracy: 0.8456 - val_loss: 0.7340 - val_accuracy: 0.8721
Epoch 76/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7530 - accuracy: 0.8473 - val_loss: 0.7147 - val_accuracy: 0.8721
Epoch 77/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7454 - accuracy: 0.8342 - val_loss: 0.7197 - val_accuracy: 0.8721
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7454 - accuracy: 0.8522 - val_loss: 0.7426 - val_accuracy: 0.8721
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7863 - accuracy: 0.8391 - val_loss: 0.7783 - val_accuracy: 0.8721
Epoch 80/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8012 - accuracy: 0.8358 - val_loss: 0.8186 - val_accuracy: 0.8721
Epoch 81/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8564 - accuracy: 0.8407 - val_loss: 0.8528 - val_accuracy: 0.8721
Epoch 82/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8851 - accuracy: 0.8325 - val_loss: 0.8783 - val_accuracy: 0.8721
Epoch 83/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8938 - accuracy: 0.8342 - val_loss: 0.9042 - val_accuracy: 0.8721
Epoch 84/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9028 - accuracy: 0.8522 - val_loss: 0.9256 - val_accuracy: 0.8721
Epoch 85/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9495 - accuracy: 0.8440 - val_loss: 0.9347 - val_accuracy: 0.8721
Epoch 86/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9822 - accuracy: 0.8506 - val_loss: 0.9399 - val_accuracy: 0.8721
Epoch 87/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9780 - accuracy: 0.8506 - val_loss: 0.9543 - val_accuracy: 0.8721
Epoch 88/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0569 - accuracy: 0.8259 - val_loss: 0.9772 - val_accuracy: 0.8721
Epoch 89/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0562 - accuracy: 0.8473 - val_loss: 1.0044 - val_accuracy: 0.8721
Epoch 90/100
2/2 [==============================] - 0s 92ms/step - loss: 1.0293 - accuracy: 0.8555 - val_loss: 1.0267 - val_accuracy: 0.8721
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0636 - accuracy: 0.8374 - val_loss: 1.0282 - val_accuracy: 0.8721
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0292 - accuracy: 0.8473 - val_loss: 1.0015 - val_accuracy: 0.8721
Epoch 93/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9660 - accuracy: 0.8604 - val_loss: 0.9455 - val_accuracy: 0.8721
Epoch 94/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9852 - accuracy: 0.8456 - val_loss: 0.8858 - val_accuracy: 0.8721
Epoch 95/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9362 - accuracy: 0.8391 - val_loss: 0.8477 - val_accuracy: 0.8721
Epoch 96/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9015 - accuracy: 0.8309 - val_loss: 0.8299 - val_accuracy: 0.8721
Epoch 97/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8546 - accuracy: 0.8440 - val_loss: 0.8348 - val_accuracy: 0.8721
Epoch 98/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8364 - accuracy: 0.8440 - val_loss: 0.8454 - val_accuracy: 0.8721
Epoch 99/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8109 - accuracy: 0.8440 - val_loss: 0.8276 - val_accuracy: 0.8721
Epoch 100/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7885 - accuracy: 0.8539 - val_loss: 0.7712 - val_accuracy: 0.8721
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 243ms/step - loss: 4.2706 - accuracy: 0.3049 - val_loss: 3.7342 - val_accuracy: 0.4770
Epoch 2/100
2/2 [==============================] - 0s 38ms/step - loss: 4.1286 - accuracy: 0.3426 - val_loss: 3.5977 - val_accuracy: 0.6118
Epoch 3/100
2/2 [==============================] - 0s 41ms/step - loss: 3.8742 - accuracy: 0.4180 - val_loss: 3.4016 - val_accuracy: 0.7401
Epoch 4/100
2/2 [==============================] - 0s 42ms/step - loss: 3.5671 - accuracy: 0.5164 - val_loss: 3.1636 - val_accuracy: 0.7730
Epoch 5/100
2/2 [==============================] - 0s 41ms/step - loss: 3.2906 - accuracy: 0.6230 - val_loss: 2.8940 - val_accuracy: 0.7961
Epoch 6/100
2/2 [==============================] - 0s 39ms/step - loss: 3.0186 - accuracy: 0.7066 - val_loss: 2.6031 - val_accuracy: 0.8257
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 2.6827 - accuracy: 0.7820 - val_loss: 2.3063 - val_accuracy: 0.8355
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 2.4161 - accuracy: 0.7836 - val_loss: 2.0152 - val_accuracy: 0.8553
Epoch 9/100
2/2 [==============================] - 0s 41ms/step - loss: 2.1541 - accuracy: 0.8000 - val_loss: 1.7437 - val_accuracy: 0.8618
Epoch 10/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8218 - accuracy: 0.8197 - val_loss: 1.5031 - val_accuracy: 0.8586
Epoch 11/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5047 - accuracy: 0.8410 - val_loss: 1.3007 - val_accuracy: 0.8618
Epoch 12/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2343 - accuracy: 0.8574 - val_loss: 1.1394 - val_accuracy: 0.8618
Epoch 13/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0619 - accuracy: 0.8639 - val_loss: 1.0149 - val_accuracy: 0.8618
Epoch 14/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9017 - accuracy: 0.8607 - val_loss: 0.9239 - val_accuracy: 0.8618
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7915 - accuracy: 0.8607 - val_loss: 0.8704 - val_accuracy: 0.8618
Epoch 16/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7272 - accuracy: 0.8541 - val_loss: 0.8678 - val_accuracy: 0.8618
Epoch 17/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6828 - accuracy: 0.8639 - val_loss: 0.9264 - val_accuracy: 0.8618
Epoch 18/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7432 - accuracy: 0.8623 - val_loss: 1.0299 - val_accuracy: 0.8618
Epoch 19/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8349 - accuracy: 0.8574 - val_loss: 1.1562 - val_accuracy: 0.8618
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9409 - accuracy: 0.8607 - val_loss: 1.2926 - val_accuracy: 0.8618
Epoch 21/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0613 - accuracy: 0.8656 - val_loss: 1.4327 - val_accuracy: 0.8618
Epoch 22/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1730 - accuracy: 0.8754 - val_loss: 1.5682 - val_accuracy: 0.8618
Epoch 23/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3337 - accuracy: 0.8787 - val_loss: 1.6935 - val_accuracy: 0.8618
Epoch 24/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4351 - accuracy: 0.8803 - val_loss: 1.8059 - val_accuracy: 0.8618
Epoch 25/100
2/2 [==============================] - 0s 44ms/step - loss: 1.5925 - accuracy: 0.8787 - val_loss: 1.9046 - val_accuracy: 0.8618
Epoch 26/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7006 - accuracy: 0.8770 - val_loss: 1.9867 - val_accuracy: 0.8618
Epoch 27/100
2/2 [==============================] - 0s 44ms/step - loss: 1.8227 - accuracy: 0.8738 - val_loss: 2.0489 - val_accuracy: 0.8618
Epoch 28/100
2/2 [==============================] - 0s 38ms/step - loss: 1.9061 - accuracy: 0.8557 - val_loss: 2.0913 - val_accuracy: 0.8618
Epoch 29/100
2/2 [==============================] - 0s 39ms/step - loss: 1.9781 - accuracy: 0.8426 - val_loss: 2.1131 - val_accuracy: 0.8618
Epoch 30/100
2/2 [==============================] - 0s 43ms/step - loss: 2.0440 - accuracy: 0.8393 - val_loss: 2.1120 - val_accuracy: 0.8618
Epoch 31/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0060 - accuracy: 0.8574 - val_loss: 2.0868 - val_accuracy: 0.8618
Epoch 32/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0028 - accuracy: 0.8656 - val_loss: 2.0401 - val_accuracy: 0.8618
Epoch 33/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9366 - accuracy: 0.8623 - val_loss: 1.9747 - val_accuracy: 0.8618
Epoch 34/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9592 - accuracy: 0.8361 - val_loss: 1.8905 - val_accuracy: 0.8618
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 1.8338 - accuracy: 0.8459 - val_loss: 1.7912 - val_accuracy: 0.8618
Epoch 36/100
2/2 [==============================] - 0s 40ms/step - loss: 1.7694 - accuracy: 0.8377 - val_loss: 1.6825 - val_accuracy: 0.8618
Epoch 37/100
2/2 [==============================] - 0s 42ms/step - loss: 1.6027 - accuracy: 0.8721 - val_loss: 1.5713 - val_accuracy: 0.8618
Epoch 38/100
2/2 [==============================] - 0s 41ms/step - loss: 1.4824 - accuracy: 0.8574 - val_loss: 1.4623 - val_accuracy: 0.8618
Epoch 39/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3419 - accuracy: 0.8803 - val_loss: 1.3551 - val_accuracy: 0.8618
Epoch 40/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2559 - accuracy: 0.8525 - val_loss: 1.2509 - val_accuracy: 0.8618
Epoch 41/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1437 - accuracy: 0.8656 - val_loss: 1.1600 - val_accuracy: 0.8618
Epoch 42/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0277 - accuracy: 0.8705 - val_loss: 1.0889 - val_accuracy: 0.8618
Epoch 43/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9094 - accuracy: 0.8836 - val_loss: 1.0399 - val_accuracy: 0.8618
Epoch 44/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8154 - accuracy: 0.8738 - val_loss: 1.0170 - val_accuracy: 0.8618
Epoch 45/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7833 - accuracy: 0.8705 - val_loss: 1.0089 - val_accuracy: 0.8618
Epoch 46/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8168 - accuracy: 0.8656 - val_loss: 1.0022 - val_accuracy: 0.8618
Epoch 47/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7763 - accuracy: 0.8639 - val_loss: 1.0024 - val_accuracy: 0.8618
Epoch 48/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7702 - accuracy: 0.8557 - val_loss: 1.0106 - val_accuracy: 0.8618
Epoch 49/100
2/2 [==============================] - 0s 44ms/step - loss: 0.7568 - accuracy: 0.8705 - val_loss: 1.0322 - val_accuracy: 0.8618
Epoch 50/100
2/2 [==============================] - 0s 41ms/step - loss: 0.8616 - accuracy: 0.8410 - val_loss: 1.0773 - val_accuracy: 0.8618
Epoch 51/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9280 - accuracy: 0.8393 - val_loss: 1.1472 - val_accuracy: 0.8618
Epoch 52/100
2/2 [==============================] - 0s 41ms/step - loss: 1.0084 - accuracy: 0.8443 - val_loss: 1.2243 - val_accuracy: 0.8618
Epoch 53/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0982 - accuracy: 0.8410 - val_loss: 1.2889 - val_accuracy: 0.8618
Epoch 54/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1314 - accuracy: 0.8541 - val_loss: 1.3403 - val_accuracy: 0.8618
Epoch 55/100
2/2 [==============================] - 0s 44ms/step - loss: 1.2109 - accuracy: 0.8361 - val_loss: 1.4010 - val_accuracy: 0.8618
Epoch 56/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3010 - accuracy: 0.8230 - val_loss: 1.4597 - val_accuracy: 0.8618
Epoch 57/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3353 - accuracy: 0.8525 - val_loss: 1.4985 - val_accuracy: 0.8618
Epoch 58/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3825 - accuracy: 0.8492 - val_loss: 1.5106 - val_accuracy: 0.8618
Epoch 59/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3797 - accuracy: 0.8639 - val_loss: 1.5077 - val_accuracy: 0.8618
Epoch 60/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3798 - accuracy: 0.8689 - val_loss: 1.5022 - val_accuracy: 0.8618
Epoch 61/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4114 - accuracy: 0.8607 - val_loss: 1.5058 - val_accuracy: 0.8618
Epoch 62/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3853 - accuracy: 0.8770 - val_loss: 1.5201 - val_accuracy: 0.8618
Epoch 63/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3557 - accuracy: 0.8689 - val_loss: 1.5277 - val_accuracy: 0.8618
Epoch 64/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3263 - accuracy: 0.8820 - val_loss: 1.5048 - val_accuracy: 0.8618
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2840 - accuracy: 0.8770 - val_loss: 1.4532 - val_accuracy: 0.8618
Epoch 66/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2443 - accuracy: 0.8721 - val_loss: 1.3761 - val_accuracy: 0.8618
Epoch 67/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1611 - accuracy: 0.8721 - val_loss: 1.2836 - val_accuracy: 0.8618
Epoch 68/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0939 - accuracy: 0.8754 - val_loss: 1.1915 - val_accuracy: 0.8618
Epoch 69/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0313 - accuracy: 0.8721 - val_loss: 1.1182 - val_accuracy: 0.8618
Epoch 70/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9961 - accuracy: 0.8787 - val_loss: 1.0657 - val_accuracy: 0.8618
Epoch 71/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9020 - accuracy: 0.8721 - val_loss: 1.0246 - val_accuracy: 0.8618
Epoch 72/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8124 - accuracy: 0.8803 - val_loss: 0.9821 - val_accuracy: 0.8618
Epoch 73/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7614 - accuracy: 0.8820 - val_loss: 0.9359 - val_accuracy: 0.8618
Epoch 74/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7668 - accuracy: 0.8656 - val_loss: 0.8950 - val_accuracy: 0.8618
Epoch 75/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7104 - accuracy: 0.8574 - val_loss: 0.8625 - val_accuracy: 0.8618
Epoch 76/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7280 - accuracy: 0.8590 - val_loss: 0.8324 - val_accuracy: 0.8618
Epoch 77/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7039 - accuracy: 0.8459 - val_loss: 0.8140 - val_accuracy: 0.8618
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7026 - accuracy: 0.8705 - val_loss: 0.8013 - val_accuracy: 0.8618
Epoch 79/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7203 - accuracy: 0.8607 - val_loss: 0.8050 - val_accuracy: 0.8618
Epoch 80/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7817 - accuracy: 0.8459 - val_loss: 0.8320 - val_accuracy: 0.8618
Epoch 81/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8021 - accuracy: 0.8557 - val_loss: 0.8733 - val_accuracy: 0.8618
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8407 - accuracy: 0.8607 - val_loss: 0.9300 - val_accuracy: 0.8618
Epoch 83/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8799 - accuracy: 0.8689 - val_loss: 0.9879 - val_accuracy: 0.8618
Epoch 84/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9189 - accuracy: 0.8590 - val_loss: 1.0282 - val_accuracy: 0.8618
Epoch 85/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9313 - accuracy: 0.8557 - val_loss: 1.0512 - val_accuracy: 0.8618
Epoch 86/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9531 - accuracy: 0.8639 - val_loss: 1.0639 - val_accuracy: 0.8586
Epoch 87/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9614 - accuracy: 0.8705 - val_loss: 1.0689 - val_accuracy: 0.8586
Epoch 88/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9785 - accuracy: 0.8672 - val_loss: 1.0754 - val_accuracy: 0.8586
Epoch 89/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9698 - accuracy: 0.8656 - val_loss: 1.0822 - val_accuracy: 0.8618
Epoch 90/100
2/2 [==============================] - 0s 39ms/step - loss: 1.0289 - accuracy: 0.8607 - val_loss: 1.0943 - val_accuracy: 0.8618
Epoch 91/100
2/2 [==============================] - 0s 40ms/step - loss: 0.9926 - accuracy: 0.8754 - val_loss: 1.1114 - val_accuracy: 0.8618
Epoch 92/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9946 - accuracy: 0.8738 - val_loss: 1.1305 - val_accuracy: 0.8618
Epoch 93/100
2/2 [==============================] - 0s 38ms/step - loss: 0.9810 - accuracy: 0.8656 - val_loss: 1.1390 - val_accuracy: 0.8618
Epoch 94/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9567 - accuracy: 0.8721 - val_loss: 1.1214 - val_accuracy: 0.8618
Epoch 95/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8917 - accuracy: 0.8967 - val_loss: 1.0881 - val_accuracy: 0.8618
Epoch 96/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8925 - accuracy: 0.8869 - val_loss: 1.0489 - val_accuracy: 0.8618
Epoch 97/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8586 - accuracy: 0.8770 - val_loss: 1.0099 - val_accuracy: 0.8618
Epoch 98/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8432 - accuracy: 0.8623 - val_loss: 0.9807 - val_accuracy: 0.8618
Epoch 99/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8300 - accuracy: 0.8574 - val_loss: 0.9595 - val_accuracy: 0.8618
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7982 - accuracy: 0.8656 - val_loss: 0.9364 - val_accuracy: 0.8618
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Experiment number: 3
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 66ms/step - loss: 5.2346 - accuracy: 0.4072 - val_loss: 5.2010 - val_accuracy: 0.5508
Epoch 2/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2270 - accuracy: 0.3777 - val_loss: 5.2002 - val_accuracy: 0.5475
Epoch 3/100
5/5 [==============================] - 0s 11ms/step - loss: 5.2285 - accuracy: 0.4072 - val_loss: 5.1995 - val_accuracy: 0.5541
Epoch 4/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2381 - accuracy: 0.3826 - val_loss: 5.1988 - val_accuracy: 0.5541
Epoch 5/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2254 - accuracy: 0.4368 - val_loss: 5.1981 - val_accuracy: 0.5508
Epoch 6/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2359 - accuracy: 0.3826 - val_loss: 5.1973 - val_accuracy: 0.5508
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2320 - accuracy: 0.3990 - val_loss: 5.1967 - val_accuracy: 0.5410
Epoch 8/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2292 - accuracy: 0.4122 - val_loss: 5.1960 - val_accuracy: 0.5377
Epoch 9/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2338 - accuracy: 0.4023 - val_loss: 5.1953 - val_accuracy: 0.5410
Epoch 10/100
5/5 [==============================] - 0s 11ms/step - loss: 5.2381 - accuracy: 0.3908 - val_loss: 5.1947 - val_accuracy: 0.5443
Epoch 11/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2297 - accuracy: 0.3990 - val_loss: 5.1940 - val_accuracy: 0.5377
Epoch 12/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2357 - accuracy: 0.3793 - val_loss: 5.1934 - val_accuracy: 0.5410
Epoch 13/100
5/5 [==============================] - 0s 11ms/step - loss: 5.2256 - accuracy: 0.3908 - val_loss: 5.1928 - val_accuracy: 0.5344
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2219 - accuracy: 0.4056 - val_loss: 5.1922 - val_accuracy: 0.5377
Epoch 15/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2205 - accuracy: 0.4105 - val_loss: 5.1915 - val_accuracy: 0.5410
Epoch 16/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2206 - accuracy: 0.4122 - val_loss: 5.1909 - val_accuracy: 0.5344
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2238 - accuracy: 0.3908 - val_loss: 5.1902 - val_accuracy: 0.5344
Epoch 18/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2332 - accuracy: 0.3596 - val_loss: 5.1896 - val_accuracy: 0.5377
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2142 - accuracy: 0.4286 - val_loss: 5.1890 - val_accuracy: 0.5377
Epoch 20/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2336 - accuracy: 0.3875 - val_loss: 5.1884 - val_accuracy: 0.5344
Epoch 21/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2233 - accuracy: 0.3810 - val_loss: 5.1877 - val_accuracy: 0.5344
Epoch 22/100
5/5 [==============================] - 0s 11ms/step - loss: 5.2184 - accuracy: 0.4154 - val_loss: 5.1871 - val_accuracy: 0.5311
Epoch 23/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2090 - accuracy: 0.4007 - val_loss: 5.1865 - val_accuracy: 0.5311
Epoch 24/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2161 - accuracy: 0.3941 - val_loss: 5.1859 - val_accuracy: 0.5279
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2155 - accuracy: 0.3892 - val_loss: 5.1852 - val_accuracy: 0.5279
Epoch 26/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2211 - accuracy: 0.3957 - val_loss: 5.1846 - val_accuracy: 0.5279
Epoch 27/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2082 - accuracy: 0.3974 - val_loss: 5.1839 - val_accuracy: 0.5180
Epoch 28/100
5/5 [==============================] - 0s 13ms/step - loss: 5.2075 - accuracy: 0.4122 - val_loss: 5.1833 - val_accuracy: 0.5180
Epoch 29/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2096 - accuracy: 0.4072 - val_loss: 5.1826 - val_accuracy: 0.5213
Epoch 30/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2011 - accuracy: 0.4138 - val_loss: 5.1819 - val_accuracy: 0.5180
Epoch 31/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2123 - accuracy: 0.4039 - val_loss: 5.1812 - val_accuracy: 0.5148
Epoch 32/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2035 - accuracy: 0.3990 - val_loss: 5.1806 - val_accuracy: 0.5115
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2135 - accuracy: 0.4007 - val_loss: 5.1799 - val_accuracy: 0.5049
Epoch 34/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1960 - accuracy: 0.4007 - val_loss: 5.1792 - val_accuracy: 0.5016
Epoch 35/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2069 - accuracy: 0.3941 - val_loss: 5.1785 - val_accuracy: 0.4984
Epoch 36/100
5/5 [==============================] - 0s 13ms/step - loss: 5.2047 - accuracy: 0.3842 - val_loss: 5.1778 - val_accuracy: 0.5016
Epoch 37/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1990 - accuracy: 0.3957 - val_loss: 5.1772 - val_accuracy: 0.5016
Epoch 38/100
5/5 [==============================] - 0s 13ms/step - loss: 5.2019 - accuracy: 0.4007 - val_loss: 5.1764 - val_accuracy: 0.5016
Epoch 39/100
5/5 [==============================] - 0s 12ms/step - loss: 5.2037 - accuracy: 0.4056 - val_loss: 5.1757 - val_accuracy: 0.5016
Epoch 40/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1966 - accuracy: 0.4105 - val_loss: 5.1750 - val_accuracy: 0.4984
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1972 - accuracy: 0.3957 - val_loss: 5.1742 - val_accuracy: 0.4984
Epoch 42/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1982 - accuracy: 0.3990 - val_loss: 5.1735 - val_accuracy: 0.4984
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1877 - accuracy: 0.4286 - val_loss: 5.1727 - val_accuracy: 0.4918
Epoch 44/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1898 - accuracy: 0.3810 - val_loss: 5.1720 - val_accuracy: 0.4918
Epoch 45/100
5/5 [==============================] - 0s 16ms/step - loss: 5.1962 - accuracy: 0.4007 - val_loss: 5.1712 - val_accuracy: 0.4918
Epoch 46/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1840 - accuracy: 0.4056 - val_loss: 5.1705 - val_accuracy: 0.4951
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1956 - accuracy: 0.3941 - val_loss: 5.1696 - val_accuracy: 0.4951
Epoch 48/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1878 - accuracy: 0.4105 - val_loss: 5.1688 - val_accuracy: 0.4951
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1871 - accuracy: 0.4023 - val_loss: 5.1680 - val_accuracy: 0.4951
Epoch 50/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1847 - accuracy: 0.4138 - val_loss: 5.1672 - val_accuracy: 0.4951
Epoch 51/100
5/5 [==============================] - 0s 26ms/step - loss: 5.1865 - accuracy: 0.4056 - val_loss: 5.1664 - val_accuracy: 0.4951
Epoch 52/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1790 - accuracy: 0.4089 - val_loss: 5.1656 - val_accuracy: 0.4951
Epoch 53/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1745 - accuracy: 0.4007 - val_loss: 5.1647 - val_accuracy: 0.4951
Epoch 54/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1842 - accuracy: 0.3941 - val_loss: 5.1639 - val_accuracy: 0.4918
Epoch 55/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1834 - accuracy: 0.4154 - val_loss: 5.1631 - val_accuracy: 0.4918
Epoch 56/100
5/5 [==============================] - 0s 15ms/step - loss: 5.1844 - accuracy: 0.4187 - val_loss: 5.1622 - val_accuracy: 0.4852
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1837 - accuracy: 0.4056 - val_loss: 5.1614 - val_accuracy: 0.4820
Epoch 58/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1683 - accuracy: 0.4302 - val_loss: 5.1606 - val_accuracy: 0.4820
Epoch 59/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1787 - accuracy: 0.3924 - val_loss: 5.1598 - val_accuracy: 0.4820
Epoch 60/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1770 - accuracy: 0.4105 - val_loss: 5.1589 - val_accuracy: 0.4820
Epoch 61/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1755 - accuracy: 0.4204 - val_loss: 5.1580 - val_accuracy: 0.4820
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1697 - accuracy: 0.4187 - val_loss: 5.1571 - val_accuracy: 0.4820
Epoch 63/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1706 - accuracy: 0.4351 - val_loss: 5.1562 - val_accuracy: 0.4820
Epoch 64/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1750 - accuracy: 0.4171 - val_loss: 5.1554 - val_accuracy: 0.4820
Epoch 65/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1713 - accuracy: 0.4122 - val_loss: 5.1546 - val_accuracy: 0.4820
Epoch 66/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1707 - accuracy: 0.4122 - val_loss: 5.1536 - val_accuracy: 0.4820
Epoch 67/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1655 - accuracy: 0.4204 - val_loss: 5.1527 - val_accuracy: 0.4820
Epoch 68/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1668 - accuracy: 0.4007 - val_loss: 5.1518 - val_accuracy: 0.4820
Epoch 69/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1660 - accuracy: 0.4253 - val_loss: 5.1508 - val_accuracy: 0.4820
Epoch 70/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1628 - accuracy: 0.4039 - val_loss: 5.1498 - val_accuracy: 0.4820
Epoch 71/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1552 - accuracy: 0.4286 - val_loss: 5.1489 - val_accuracy: 0.4820
Epoch 72/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1565 - accuracy: 0.4171 - val_loss: 5.1479 - val_accuracy: 0.4820
Epoch 73/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1664 - accuracy: 0.4089 - val_loss: 5.1470 - val_accuracy: 0.4820
Epoch 74/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1602 - accuracy: 0.4138 - val_loss: 5.1461 - val_accuracy: 0.4820
Epoch 75/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1638 - accuracy: 0.4154 - val_loss: 5.1451 - val_accuracy: 0.4820
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1593 - accuracy: 0.4236 - val_loss: 5.1442 - val_accuracy: 0.4820
Epoch 77/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1612 - accuracy: 0.4204 - val_loss: 5.1432 - val_accuracy: 0.4820
Epoch 78/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1579 - accuracy: 0.4220 - val_loss: 5.1423 - val_accuracy: 0.4820
Epoch 79/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1572 - accuracy: 0.4204 - val_loss: 5.1413 - val_accuracy: 0.4820
Epoch 80/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1525 - accuracy: 0.4171 - val_loss: 5.1404 - val_accuracy: 0.4820
Epoch 81/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1528 - accuracy: 0.4039 - val_loss: 5.1394 - val_accuracy: 0.4820
Epoch 82/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1565 - accuracy: 0.4269 - val_loss: 5.1384 - val_accuracy: 0.4820
Epoch 83/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1519 - accuracy: 0.4122 - val_loss: 5.1374 - val_accuracy: 0.4820
Epoch 84/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1526 - accuracy: 0.4023 - val_loss: 5.1366 - val_accuracy: 0.4787
Epoch 85/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1436 - accuracy: 0.4483 - val_loss: 5.1356 - val_accuracy: 0.4754
Epoch 86/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1463 - accuracy: 0.4187 - val_loss: 5.1347 - val_accuracy: 0.4754
Epoch 87/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1540 - accuracy: 0.4023 - val_loss: 5.1337 - val_accuracy: 0.4754
Epoch 88/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1398 - accuracy: 0.4565 - val_loss: 5.1327 - val_accuracy: 0.4754
Epoch 89/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1455 - accuracy: 0.4204 - val_loss: 5.1317 - val_accuracy: 0.4754
Epoch 90/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1434 - accuracy: 0.4187 - val_loss: 5.1307 - val_accuracy: 0.4754
Epoch 91/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1372 - accuracy: 0.4253 - val_loss: 5.1298 - val_accuracy: 0.4754
Epoch 92/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1470 - accuracy: 0.4072 - val_loss: 5.1288 - val_accuracy: 0.4754
Epoch 93/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1427 - accuracy: 0.4302 - val_loss: 5.1279 - val_accuracy: 0.4754
Epoch 94/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1350 - accuracy: 0.4187 - val_loss: 5.1268 - val_accuracy: 0.4754
Epoch 95/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1367 - accuracy: 0.4187 - val_loss: 5.1259 - val_accuracy: 0.4754
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1334 - accuracy: 0.4335 - val_loss: 5.1249 - val_accuracy: 0.4754
Epoch 97/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1350 - accuracy: 0.4351 - val_loss: 5.1239 - val_accuracy: 0.4754
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1357 - accuracy: 0.4089 - val_loss: 5.1229 - val_accuracy: 0.4754
Epoch 99/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1298 - accuracy: 0.4220 - val_loss: 5.1219 - val_accuracy: 0.4754
Epoch 100/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1357 - accuracy: 0.4204 - val_loss: 5.1210 - val_accuracy: 0.4754
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 62ms/step - loss: 5.4319 - accuracy: 0.2250 - val_loss: 5.3703 - val_accuracy: 0.5246
Epoch 2/100
5/5 [==============================] - 0s 11ms/step - loss: 5.4339 - accuracy: 0.2397 - val_loss: 5.3706 - val_accuracy: 0.5148
Epoch 3/100
5/5 [==============================] - 0s 13ms/step - loss: 5.4210 - accuracy: 0.2808 - val_loss: 5.3709 - val_accuracy: 0.5115
Epoch 4/100
5/5 [==============================] - 0s 12ms/step - loss: 5.4243 - accuracy: 0.2562 - val_loss: 5.3711 - val_accuracy: 0.4984
Epoch 5/100
5/5 [==============================] - 0s 11ms/step - loss: 5.4334 - accuracy: 0.2578 - val_loss: 5.3714 - val_accuracy: 0.4787
Epoch 6/100
5/5 [==============================] - 0s 11ms/step - loss: 5.4203 - accuracy: 0.2529 - val_loss: 5.3716 - val_accuracy: 0.4787
Epoch 7/100
5/5 [==============================] - 0s 11ms/step - loss: 5.4222 - accuracy: 0.2397 - val_loss: 5.3717 - val_accuracy: 0.4754
Epoch 8/100
5/5 [==============================] - 0s 11ms/step - loss: 5.4161 - accuracy: 0.2611 - val_loss: 5.3718 - val_accuracy: 0.4689
Epoch 9/100
5/5 [==============================] - 0s 28ms/step - loss: 5.4168 - accuracy: 0.2644 - val_loss: 5.3718 - val_accuracy: 0.4557
Epoch 10/100
5/5 [==============================] - 0s 14ms/step - loss: 5.4179 - accuracy: 0.2545 - val_loss: 5.3719 - val_accuracy: 0.4426
Epoch 11/100
5/5 [==============================] - 0s 14ms/step - loss: 5.4080 - accuracy: 0.2857 - val_loss: 5.3719 - val_accuracy: 0.4295
Epoch 12/100
5/5 [==============================] - 0s 12ms/step - loss: 5.4158 - accuracy: 0.2529 - val_loss: 5.3719 - val_accuracy: 0.4164
Epoch 13/100
5/5 [==============================] - 0s 13ms/step - loss: 5.4167 - accuracy: 0.2430 - val_loss: 5.3719 - val_accuracy: 0.4131
Epoch 14/100
5/5 [==============================] - 0s 13ms/step - loss: 5.4155 - accuracy: 0.2463 - val_loss: 5.3718 - val_accuracy: 0.4066
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 5.4109 - accuracy: 0.2430 - val_loss: 5.3717 - val_accuracy: 0.4033
Epoch 16/100
5/5 [==============================] - 0s 13ms/step - loss: 5.4132 - accuracy: 0.2397 - val_loss: 5.3715 - val_accuracy: 0.3902
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 5.4052 - accuracy: 0.2824 - val_loss: 5.3713 - val_accuracy: 0.3770
Epoch 18/100
5/5 [==============================] - 0s 12ms/step - loss: 5.4053 - accuracy: 0.2578 - val_loss: 5.3711 - val_accuracy: 0.3639
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3997 - accuracy: 0.2759 - val_loss: 5.3710 - val_accuracy: 0.3574
Epoch 20/100
5/5 [==============================] - 0s 15ms/step - loss: 5.4081 - accuracy: 0.2496 - val_loss: 5.3707 - val_accuracy: 0.3541
Epoch 21/100
5/5 [==============================] - 0s 11ms/step - loss: 5.4044 - accuracy: 0.2447 - val_loss: 5.3705 - val_accuracy: 0.3541
Epoch 22/100
5/5 [==============================] - 0s 14ms/step - loss: 5.3985 - accuracy: 0.2824 - val_loss: 5.3702 - val_accuracy: 0.3475
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 5.4077 - accuracy: 0.2479 - val_loss: 5.3698 - val_accuracy: 0.3475
Epoch 24/100
5/5 [==============================] - 0s 13ms/step - loss: 5.4038 - accuracy: 0.2742 - val_loss: 5.3695 - val_accuracy: 0.3443
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 5.4015 - accuracy: 0.2759 - val_loss: 5.3692 - val_accuracy: 0.3410
Epoch 26/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3933 - accuracy: 0.2808 - val_loss: 5.3688 - val_accuracy: 0.3344
Epoch 27/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3906 - accuracy: 0.2742 - val_loss: 5.3684 - val_accuracy: 0.3311
Epoch 28/100
5/5 [==============================] - 0s 10ms/step - loss: 5.3883 - accuracy: 0.2824 - val_loss: 5.3680 - val_accuracy: 0.3311
Epoch 29/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3961 - accuracy: 0.2742 - val_loss: 5.3675 - val_accuracy: 0.3279
Epoch 30/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3931 - accuracy: 0.2742 - val_loss: 5.3671 - val_accuracy: 0.3246
Epoch 31/100
5/5 [==============================] - 0s 9ms/step - loss: 5.3954 - accuracy: 0.2512 - val_loss: 5.3666 - val_accuracy: 0.3213
Epoch 32/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3907 - accuracy: 0.2824 - val_loss: 5.3661 - val_accuracy: 0.3148
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3875 - accuracy: 0.2759 - val_loss: 5.3656 - val_accuracy: 0.3082
Epoch 34/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3917 - accuracy: 0.2808 - val_loss: 5.3650 - val_accuracy: 0.3016
Epoch 35/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3895 - accuracy: 0.2677 - val_loss: 5.3644 - val_accuracy: 0.2918
Epoch 36/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3930 - accuracy: 0.2775 - val_loss: 5.3639 - val_accuracy: 0.2852
Epoch 37/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3927 - accuracy: 0.2562 - val_loss: 5.3633 - val_accuracy: 0.2852
Epoch 38/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3797 - accuracy: 0.2726 - val_loss: 5.3627 - val_accuracy: 0.2852
Epoch 39/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3829 - accuracy: 0.2775 - val_loss: 5.3620 - val_accuracy: 0.2820
Epoch 40/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3838 - accuracy: 0.2677 - val_loss: 5.3614 - val_accuracy: 0.2820
Epoch 41/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3790 - accuracy: 0.2529 - val_loss: 5.3608 - val_accuracy: 0.2820
Epoch 42/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3732 - accuracy: 0.2956 - val_loss: 5.3601 - val_accuracy: 0.2820
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3771 - accuracy: 0.2594 - val_loss: 5.3594 - val_accuracy: 0.2787
Epoch 44/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3737 - accuracy: 0.2890 - val_loss: 5.3587 - val_accuracy: 0.2787
Epoch 45/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3798 - accuracy: 0.2644 - val_loss: 5.3580 - val_accuracy: 0.2754
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3683 - accuracy: 0.3005 - val_loss: 5.3572 - val_accuracy: 0.2721
Epoch 47/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3771 - accuracy: 0.2989 - val_loss: 5.3565 - val_accuracy: 0.2689
Epoch 48/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3719 - accuracy: 0.2923 - val_loss: 5.3557 - val_accuracy: 0.2656
Epoch 49/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3710 - accuracy: 0.2956 - val_loss: 5.3550 - val_accuracy: 0.2656
Epoch 50/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3660 - accuracy: 0.2857 - val_loss: 5.3542 - val_accuracy: 0.2656
Epoch 51/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3738 - accuracy: 0.2611 - val_loss: 5.3534 - val_accuracy: 0.2656
Epoch 52/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3785 - accuracy: 0.2693 - val_loss: 5.3526 - val_accuracy: 0.2689
Epoch 53/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3722 - accuracy: 0.2545 - val_loss: 5.3518 - val_accuracy: 0.2689
Epoch 54/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3705 - accuracy: 0.2578 - val_loss: 5.3510 - val_accuracy: 0.2689
Epoch 55/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3719 - accuracy: 0.2562 - val_loss: 5.3502 - val_accuracy: 0.2689
Epoch 56/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3669 - accuracy: 0.2791 - val_loss: 5.3493 - val_accuracy: 0.2689
Epoch 57/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3631 - accuracy: 0.2890 - val_loss: 5.3484 - val_accuracy: 0.2689
Epoch 58/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3664 - accuracy: 0.2775 - val_loss: 5.3476 - val_accuracy: 0.2689
Epoch 59/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3621 - accuracy: 0.2841 - val_loss: 5.3467 - val_accuracy: 0.2689
Epoch 60/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3694 - accuracy: 0.2644 - val_loss: 5.3458 - val_accuracy: 0.2656
Epoch 61/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3566 - accuracy: 0.2791 - val_loss: 5.3450 - val_accuracy: 0.2656
Epoch 62/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3581 - accuracy: 0.2709 - val_loss: 5.3441 - val_accuracy: 0.2656
Epoch 63/100
5/5 [==============================] - 0s 9ms/step - loss: 5.3609 - accuracy: 0.2890 - val_loss: 5.3431 - val_accuracy: 0.2656
Epoch 64/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3544 - accuracy: 0.2890 - val_loss: 5.3422 - val_accuracy: 0.2656
Epoch 65/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3516 - accuracy: 0.2906 - val_loss: 5.3413 - val_accuracy: 0.2689
Epoch 66/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3630 - accuracy: 0.2677 - val_loss: 5.3403 - val_accuracy: 0.2689
Epoch 67/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3513 - accuracy: 0.2841 - val_loss: 5.3394 - val_accuracy: 0.2689
Epoch 68/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3496 - accuracy: 0.3038 - val_loss: 5.3385 - val_accuracy: 0.2656
Epoch 69/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3482 - accuracy: 0.2759 - val_loss: 5.3375 - val_accuracy: 0.2656
Epoch 70/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3531 - accuracy: 0.2939 - val_loss: 5.3366 - val_accuracy: 0.2689
Epoch 71/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3514 - accuracy: 0.3038 - val_loss: 5.3356 - val_accuracy: 0.2689
Epoch 72/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3459 - accuracy: 0.3103 - val_loss: 5.3347 - val_accuracy: 0.2689
Epoch 73/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3438 - accuracy: 0.3284 - val_loss: 5.3337 - val_accuracy: 0.2689
Epoch 74/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3470 - accuracy: 0.2906 - val_loss: 5.3327 - val_accuracy: 0.2689
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3460 - accuracy: 0.2775 - val_loss: 5.3318 - val_accuracy: 0.2721
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3433 - accuracy: 0.2906 - val_loss: 5.3308 - val_accuracy: 0.2721
Epoch 77/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3350 - accuracy: 0.3054 - val_loss: 5.3298 - val_accuracy: 0.2721
Epoch 78/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3446 - accuracy: 0.2775 - val_loss: 5.3289 - val_accuracy: 0.2754
Epoch 79/100
5/5 [==============================] - 0s 14ms/step - loss: 5.3385 - accuracy: 0.2989 - val_loss: 5.3279 - val_accuracy: 0.2754
Epoch 80/100
5/5 [==============================] - 0s 9ms/step - loss: 5.3349 - accuracy: 0.2890 - val_loss: 5.3268 - val_accuracy: 0.2754
Epoch 81/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3352 - accuracy: 0.2742 - val_loss: 5.3259 - val_accuracy: 0.2754
Epoch 82/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3350 - accuracy: 0.2956 - val_loss: 5.3249 - val_accuracy: 0.2754
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3339 - accuracy: 0.2956 - val_loss: 5.3239 - val_accuracy: 0.2754
Epoch 84/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3402 - accuracy: 0.2874 - val_loss: 5.3228 - val_accuracy: 0.2754
Epoch 85/100
5/5 [==============================] - 0s 9ms/step - loss: 5.3338 - accuracy: 0.2989 - val_loss: 5.3218 - val_accuracy: 0.2754
Epoch 86/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3327 - accuracy: 0.3103 - val_loss: 5.3208 - val_accuracy: 0.2754
Epoch 87/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3418 - accuracy: 0.2709 - val_loss: 5.3198 - val_accuracy: 0.2754
Epoch 88/100
5/5 [==============================] - 0s 16ms/step - loss: 5.3258 - accuracy: 0.3350 - val_loss: 5.3188 - val_accuracy: 0.2787
Epoch 89/100
5/5 [==============================] - 0s 13ms/step - loss: 5.3338 - accuracy: 0.2857 - val_loss: 5.3177 - val_accuracy: 0.2787
Epoch 90/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3235 - accuracy: 0.3235 - val_loss: 5.3167 - val_accuracy: 0.2787
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3251 - accuracy: 0.3169 - val_loss: 5.3156 - val_accuracy: 0.2787
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3225 - accuracy: 0.2890 - val_loss: 5.3146 - val_accuracy: 0.2787
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3193 - accuracy: 0.3317 - val_loss: 5.3136 - val_accuracy: 0.2787
Epoch 94/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3194 - accuracy: 0.3186 - val_loss: 5.3125 - val_accuracy: 0.2820
Epoch 95/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3224 - accuracy: 0.2956 - val_loss: 5.3115 - val_accuracy: 0.2820
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3234 - accuracy: 0.2923 - val_loss: 5.3104 - val_accuracy: 0.2820
Epoch 97/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3262 - accuracy: 0.2972 - val_loss: 5.3094 - val_accuracy: 0.2820
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3155 - accuracy: 0.3038 - val_loss: 5.3084 - val_accuracy: 0.2852
Epoch 99/100
5/5 [==============================] - 0s 11ms/step - loss: 5.3169 - accuracy: 0.3251 - val_loss: 5.3073 - val_accuracy: 0.2885
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 5.3090 - accuracy: 0.3153 - val_loss: 5.3063 - val_accuracy: 0.2852
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
5/5 [==============================] - 1s 61ms/step - loss: 5.1521 - accuracy: 0.3410 - val_loss: 5.1726 - val_accuracy: 0.1349
Epoch 2/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1490 - accuracy: 0.3426 - val_loss: 5.1710 - val_accuracy: 0.1382
Epoch 3/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1457 - accuracy: 0.3246 - val_loss: 5.1694 - val_accuracy: 0.1447
Epoch 4/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1472 - accuracy: 0.3721 - val_loss: 5.1678 - val_accuracy: 0.1480
Epoch 5/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1496 - accuracy: 0.3574 - val_loss: 5.1662 - val_accuracy: 0.1513
Epoch 6/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1488 - accuracy: 0.3164 - val_loss: 5.1647 - val_accuracy: 0.1546
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1370 - accuracy: 0.3607 - val_loss: 5.1632 - val_accuracy: 0.1678
Epoch 8/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1462 - accuracy: 0.3443 - val_loss: 5.1616 - val_accuracy: 0.1711
Epoch 9/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1370 - accuracy: 0.3508 - val_loss: 5.1601 - val_accuracy: 0.1743
Epoch 10/100
5/5 [==============================] - 0s 9ms/step - loss: 5.1396 - accuracy: 0.3426 - val_loss: 5.1586 - val_accuracy: 0.1776
Epoch 11/100
5/5 [==============================] - 0s 9ms/step - loss: 5.1449 - accuracy: 0.3426 - val_loss: 5.1572 - val_accuracy: 0.1743
Epoch 12/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1388 - accuracy: 0.3148 - val_loss: 5.1557 - val_accuracy: 0.1875
Epoch 13/100
5/5 [==============================] - 0s 14ms/step - loss: 5.1360 - accuracy: 0.3328 - val_loss: 5.1542 - val_accuracy: 0.1941
Epoch 14/100
5/5 [==============================] - 0s 10ms/step - loss: 5.1330 - accuracy: 0.3475 - val_loss: 5.1528 - val_accuracy: 0.1908
Epoch 15/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1349 - accuracy: 0.3443 - val_loss: 5.1513 - val_accuracy: 0.1941
Epoch 16/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1332 - accuracy: 0.3574 - val_loss: 5.1499 - val_accuracy: 0.1974
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1360 - accuracy: 0.3525 - val_loss: 5.1485 - val_accuracy: 0.1974
Epoch 18/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1342 - accuracy: 0.3557 - val_loss: 5.1470 - val_accuracy: 0.2039
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1308 - accuracy: 0.3607 - val_loss: 5.1457 - val_accuracy: 0.2072
Epoch 20/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1317 - accuracy: 0.3557 - val_loss: 5.1442 - val_accuracy: 0.2105
Epoch 21/100
5/5 [==============================] - 0s 14ms/step - loss: 5.1275 - accuracy: 0.3590 - val_loss: 5.1429 - val_accuracy: 0.2105
Epoch 22/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1326 - accuracy: 0.3164 - val_loss: 5.1415 - val_accuracy: 0.2105
Epoch 23/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1308 - accuracy: 0.3492 - val_loss: 5.1402 - val_accuracy: 0.2105
Epoch 24/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1186 - accuracy: 0.3426 - val_loss: 5.1389 - val_accuracy: 0.2105
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1230 - accuracy: 0.3311 - val_loss: 5.1375 - val_accuracy: 0.2237
Epoch 26/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1282 - accuracy: 0.3508 - val_loss: 5.1362 - val_accuracy: 0.2270
Epoch 27/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1284 - accuracy: 0.3393 - val_loss: 5.1349 - val_accuracy: 0.2270
Epoch 28/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1178 - accuracy: 0.3689 - val_loss: 5.1336 - val_accuracy: 0.2303
Epoch 29/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1198 - accuracy: 0.3639 - val_loss: 5.1323 - val_accuracy: 0.2336
Epoch 30/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1208 - accuracy: 0.3705 - val_loss: 5.1310 - val_accuracy: 0.2336
Epoch 31/100
5/5 [==============================] - 0s 10ms/step - loss: 5.1170 - accuracy: 0.3541 - val_loss: 5.1297 - val_accuracy: 0.2368
Epoch 32/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1110 - accuracy: 0.3541 - val_loss: 5.1285 - val_accuracy: 0.2368
Epoch 33/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1178 - accuracy: 0.3656 - val_loss: 5.1272 - val_accuracy: 0.2500
Epoch 34/100
5/5 [==============================] - 0s 16ms/step - loss: 5.1115 - accuracy: 0.3508 - val_loss: 5.1259 - val_accuracy: 0.2566
Epoch 35/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1166 - accuracy: 0.3492 - val_loss: 5.1247 - val_accuracy: 0.2566
Epoch 36/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1071 - accuracy: 0.3770 - val_loss: 5.1234 - val_accuracy: 0.2566
Epoch 37/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1087 - accuracy: 0.3754 - val_loss: 5.1222 - val_accuracy: 0.2566
Epoch 38/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1072 - accuracy: 0.3525 - val_loss: 5.1210 - val_accuracy: 0.2566
Epoch 39/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1156 - accuracy: 0.3475 - val_loss: 5.1197 - val_accuracy: 0.2599
Epoch 40/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1012 - accuracy: 0.3852 - val_loss: 5.1185 - val_accuracy: 0.2664
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1147 - accuracy: 0.3475 - val_loss: 5.1173 - val_accuracy: 0.2664
Epoch 42/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1104 - accuracy: 0.3541 - val_loss: 5.1161 - val_accuracy: 0.2664
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0969 - accuracy: 0.3803 - val_loss: 5.1149 - val_accuracy: 0.2697
Epoch 44/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1062 - accuracy: 0.3525 - val_loss: 5.1137 - val_accuracy: 0.2664
Epoch 45/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0961 - accuracy: 0.3705 - val_loss: 5.1126 - val_accuracy: 0.2697
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1005 - accuracy: 0.3443 - val_loss: 5.1114 - val_accuracy: 0.2697
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0988 - accuracy: 0.3639 - val_loss: 5.1102 - val_accuracy: 0.2730
Epoch 48/100
5/5 [==============================] - 0s 10ms/step - loss: 5.1064 - accuracy: 0.3770 - val_loss: 5.1091 - val_accuracy: 0.2730
Epoch 49/100
5/5 [==============================] - 0s 11ms/step - loss: 5.1026 - accuracy: 0.3557 - val_loss: 5.1079 - val_accuracy: 0.2730
Epoch 50/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0900 - accuracy: 0.3902 - val_loss: 5.1067 - val_accuracy: 0.2763
Epoch 51/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0945 - accuracy: 0.3508 - val_loss: 5.1056 - val_accuracy: 0.2763
Epoch 52/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0980 - accuracy: 0.3541 - val_loss: 5.1045 - val_accuracy: 0.2763
Epoch 53/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0966 - accuracy: 0.3557 - val_loss: 5.1034 - val_accuracy: 0.2763
Epoch 54/100
5/5 [==============================] - 0s 10ms/step - loss: 5.0939 - accuracy: 0.3541 - val_loss: 5.1023 - val_accuracy: 0.2763
Epoch 55/100
5/5 [==============================] - 0s 13ms/step - loss: 5.0942 - accuracy: 0.3607 - val_loss: 5.1012 - val_accuracy: 0.2763
Epoch 56/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0852 - accuracy: 0.3803 - val_loss: 5.1000 - val_accuracy: 0.2796
Epoch 57/100
5/5 [==============================] - 0s 13ms/step - loss: 5.1010 - accuracy: 0.3508 - val_loss: 5.0989 - val_accuracy: 0.2796
Epoch 58/100
5/5 [==============================] - 0s 13ms/step - loss: 5.0828 - accuracy: 0.3557 - val_loss: 5.0978 - val_accuracy: 0.2796
Epoch 59/100
5/5 [==============================] - 0s 11ms/step - loss: 5.0827 - accuracy: 0.3836 - val_loss: 5.0967 - val_accuracy: 0.2796
Epoch 60/100
5/5 [==============================] - 0s 13ms/step - loss: 5.0926 - accuracy: 0.3492 - val_loss: 5.0956 - val_accuracy: 0.2796
Epoch 61/100
5/5 [==============================] - 0s 13ms/step - loss: 5.0831 - accuracy: 0.3541 - val_loss: 5.0945 - val_accuracy: 0.2829
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0889 - accuracy: 0.3721 - val_loss: 5.0934 - val_accuracy: 0.2829
Epoch 63/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0845 - accuracy: 0.3574 - val_loss: 5.0924 - val_accuracy: 0.2895
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0836 - accuracy: 0.3475 - val_loss: 5.0913 - val_accuracy: 0.2895
Epoch 65/100
5/5 [==============================] - 0s 15ms/step - loss: 5.0839 - accuracy: 0.3738 - val_loss: 5.0902 - val_accuracy: 0.2928
Epoch 66/100
5/5 [==============================] - 0s 14ms/step - loss: 5.0812 - accuracy: 0.3738 - val_loss: 5.0891 - val_accuracy: 0.2928
Epoch 67/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0790 - accuracy: 0.3574 - val_loss: 5.0881 - val_accuracy: 0.2961
Epoch 68/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0802 - accuracy: 0.3721 - val_loss: 5.0870 - val_accuracy: 0.2993
Epoch 69/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0782 - accuracy: 0.3590 - val_loss: 5.0859 - val_accuracy: 0.2993
Epoch 70/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0793 - accuracy: 0.3475 - val_loss: 5.0848 - val_accuracy: 0.3026
Epoch 71/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0787 - accuracy: 0.3607 - val_loss: 5.0837 - val_accuracy: 0.3026
Epoch 72/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0737 - accuracy: 0.3721 - val_loss: 5.0826 - val_accuracy: 0.3026
Epoch 73/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0715 - accuracy: 0.3672 - val_loss: 5.0815 - val_accuracy: 0.3026
Epoch 74/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0680 - accuracy: 0.3607 - val_loss: 5.0805 - val_accuracy: 0.3026
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0671 - accuracy: 0.3902 - val_loss: 5.0794 - val_accuracy: 0.3026
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0674 - accuracy: 0.3869 - val_loss: 5.0784 - val_accuracy: 0.3059
Epoch 77/100
5/5 [==============================] - 0s 11ms/step - loss: 5.0686 - accuracy: 0.3836 - val_loss: 5.0773 - val_accuracy: 0.3092
Epoch 78/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0717 - accuracy: 0.3672 - val_loss: 5.0762 - val_accuracy: 0.3092
Epoch 79/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0648 - accuracy: 0.3770 - val_loss: 5.0752 - val_accuracy: 0.3125
Epoch 80/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0637 - accuracy: 0.3803 - val_loss: 5.0741 - val_accuracy: 0.3125
Epoch 81/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0700 - accuracy: 0.3738 - val_loss: 5.0731 - val_accuracy: 0.3158
Epoch 82/100
5/5 [==============================] - 0s 11ms/step - loss: 5.0640 - accuracy: 0.3574 - val_loss: 5.0720 - val_accuracy: 0.3158
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0523 - accuracy: 0.3852 - val_loss: 5.0710 - val_accuracy: 0.3191
Epoch 84/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0575 - accuracy: 0.3869 - val_loss: 5.0700 - val_accuracy: 0.3191
Epoch 85/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0610 - accuracy: 0.4016 - val_loss: 5.0689 - val_accuracy: 0.3224
Epoch 86/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0639 - accuracy: 0.3705 - val_loss: 5.0679 - val_accuracy: 0.3224
Epoch 87/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0602 - accuracy: 0.3557 - val_loss: 5.0668 - val_accuracy: 0.3224
Epoch 88/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0586 - accuracy: 0.3721 - val_loss: 5.0658 - val_accuracy: 0.3224
Epoch 89/100
5/5 [==============================] - 0s 11ms/step - loss: 5.0520 - accuracy: 0.3820 - val_loss: 5.0648 - val_accuracy: 0.3224
Epoch 90/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0586 - accuracy: 0.3754 - val_loss: 5.0637 - val_accuracy: 0.3224
Epoch 91/100
5/5 [==============================] - 0s 11ms/step - loss: 5.0506 - accuracy: 0.3902 - val_loss: 5.0626 - val_accuracy: 0.3224
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0536 - accuracy: 0.3557 - val_loss: 5.0616 - val_accuracy: 0.3224
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0537 - accuracy: 0.3836 - val_loss: 5.0606 - val_accuracy: 0.3224
Epoch 94/100
5/5 [==============================] - 0s 11ms/step - loss: 5.0548 - accuracy: 0.3787 - val_loss: 5.0596 - val_accuracy: 0.3224
Epoch 95/100
5/5 [==============================] - 0s 13ms/step - loss: 5.0526 - accuracy: 0.3623 - val_loss: 5.0585 - val_accuracy: 0.3224
Epoch 96/100
5/5 [==============================] - 0s 14ms/step - loss: 5.0504 - accuracy: 0.4115 - val_loss: 5.0575 - val_accuracy: 0.3224
Epoch 97/100
5/5 [==============================] - 0s 13ms/step - loss: 5.0444 - accuracy: 0.3902 - val_loss: 5.0564 - val_accuracy: 0.3257
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0467 - accuracy: 0.3852 - val_loss: 5.0554 - val_accuracy: 0.3257
Epoch 99/100
5/5 [==============================] - 0s 11ms/step - loss: 5.0413 - accuracy: 0.3754 - val_loss: 5.0544 - val_accuracy: 0.3257
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 5.0459 - accuracy: 0.3672 - val_loss: 5.0534 - val_accuracy: 0.3257
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Experiment number: 4
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 252ms/step - loss: 4.3646 - accuracy: 0.2791 - val_loss: 2.9952 - val_accuracy: 0.4754
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 4.3909 - accuracy: 0.2594 - val_loss: 2.9988 - val_accuracy: 0.4623
Epoch 3/100
2/2 [==============================] - 0s 47ms/step - loss: 4.3900 - accuracy: 0.2693 - val_loss: 3.0016 - val_accuracy: 0.4590
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 4.4091 - accuracy: 0.2594 - val_loss: 3.0031 - val_accuracy: 0.4590
Epoch 5/100
2/2 [==============================] - 0s 47ms/step - loss: 4.3248 - accuracy: 0.2677 - val_loss: 3.0045 - val_accuracy: 0.4557
Epoch 6/100
2/2 [==============================] - 0s 47ms/step - loss: 4.4013 - accuracy: 0.2562 - val_loss: 3.0055 - val_accuracy: 0.4525
Epoch 7/100
2/2 [==============================] - 0s 54ms/step - loss: 4.3327 - accuracy: 0.2759 - val_loss: 3.0062 - val_accuracy: 0.4492
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 4.3814 - accuracy: 0.2430 - val_loss: 3.0061 - val_accuracy: 0.4459
Epoch 9/100
2/2 [==============================] - 0s 34ms/step - loss: 4.2222 - accuracy: 0.2824 - val_loss: 3.0059 - val_accuracy: 0.4426
Epoch 10/100
2/2 [==============================] - 0s 33ms/step - loss: 4.2611 - accuracy: 0.2709 - val_loss: 3.0056 - val_accuracy: 0.4393
Epoch 11/100
2/2 [==============================] - 0s 48ms/step - loss: 4.2999 - accuracy: 0.2726 - val_loss: 3.0051 - val_accuracy: 0.4393
Epoch 12/100
2/2 [==============================] - 0s 53ms/step - loss: 4.2808 - accuracy: 0.2693 - val_loss: 3.0046 - val_accuracy: 0.4361
Epoch 13/100
2/2 [==============================] - 0s 45ms/step - loss: 4.2776 - accuracy: 0.2545 - val_loss: 3.0042 - val_accuracy: 0.4361
Epoch 14/100
2/2 [==============================] - 0s 47ms/step - loss: 4.2104 - accuracy: 0.2611 - val_loss: 3.0033 - val_accuracy: 0.4361
Epoch 15/100
2/2 [==============================] - 0s 28ms/step - loss: 4.2618 - accuracy: 0.2578 - val_loss: 3.0026 - val_accuracy: 0.4361
Epoch 16/100
2/2 [==============================] - 0s 34ms/step - loss: 4.2256 - accuracy: 0.2660 - val_loss: 3.0019 - val_accuracy: 0.4328
Epoch 17/100
2/2 [==============================] - 0s 36ms/step - loss: 4.1180 - accuracy: 0.2890 - val_loss: 3.0010 - val_accuracy: 0.4328
Epoch 18/100
2/2 [==============================] - 0s 48ms/step - loss: 4.1762 - accuracy: 0.2611 - val_loss: 2.9995 - val_accuracy: 0.4295
Epoch 19/100
2/2 [==============================] - 0s 47ms/step - loss: 4.1290 - accuracy: 0.2824 - val_loss: 2.9987 - val_accuracy: 0.4262
Epoch 20/100
2/2 [==============================] - 0s 33ms/step - loss: 4.1372 - accuracy: 0.2578 - val_loss: 2.9974 - val_accuracy: 0.4230
Epoch 21/100
2/2 [==============================] - 0s 34ms/step - loss: 4.1137 - accuracy: 0.2857 - val_loss: 2.9961 - val_accuracy: 0.4230
Epoch 22/100
2/2 [==============================] - 0s 47ms/step - loss: 4.0851 - accuracy: 0.2677 - val_loss: 2.9948 - val_accuracy: 0.4230
Epoch 23/100
2/2 [==============================] - 0s 48ms/step - loss: 4.1419 - accuracy: 0.2496 - val_loss: 2.9933 - val_accuracy: 0.4230
Epoch 24/100
2/2 [==============================] - 0s 43ms/step - loss: 4.0520 - accuracy: 0.2890 - val_loss: 2.9916 - val_accuracy: 0.4197
Epoch 25/100
2/2 [==============================] - 0s 50ms/step - loss: 4.0579 - accuracy: 0.2939 - val_loss: 2.9898 - val_accuracy: 0.4197
Epoch 26/100
2/2 [==============================] - 0s 39ms/step - loss: 4.0152 - accuracy: 0.2824 - val_loss: 2.9884 - val_accuracy: 0.4197
Epoch 27/100
2/2 [==============================] - 0s 37ms/step - loss: 4.0067 - accuracy: 0.2939 - val_loss: 2.9870 - val_accuracy: 0.4262
Epoch 28/100
2/2 [==============================] - 0s 36ms/step - loss: 4.0544 - accuracy: 0.2578 - val_loss: 2.9855 - val_accuracy: 0.4262
Epoch 29/100
2/2 [==============================] - 0s 35ms/step - loss: 4.0279 - accuracy: 0.2906 - val_loss: 2.9840 - val_accuracy: 0.4295
Epoch 30/100
2/2 [==============================] - 0s 33ms/step - loss: 3.9957 - accuracy: 0.3038 - val_loss: 2.9822 - val_accuracy: 0.4295
Epoch 31/100
2/2 [==============================] - 0s 34ms/step - loss: 3.9084 - accuracy: 0.2923 - val_loss: 2.9802 - val_accuracy: 0.4295
Epoch 32/100
2/2 [==============================] - 0s 36ms/step - loss: 3.9445 - accuracy: 0.3087 - val_loss: 2.9783 - val_accuracy: 0.4295
Epoch 33/100
2/2 [==============================] - 0s 43ms/step - loss: 3.8845 - accuracy: 0.3169 - val_loss: 2.9761 - val_accuracy: 0.4328
Epoch 34/100
2/2 [==============================] - 0s 31ms/step - loss: 3.8725 - accuracy: 0.2972 - val_loss: 2.9743 - val_accuracy: 0.4328
Epoch 35/100
2/2 [==============================] - 0s 31ms/step - loss: 3.8237 - accuracy: 0.3005 - val_loss: 2.9723 - val_accuracy: 0.4361
Epoch 36/100
2/2 [==============================] - 0s 31ms/step - loss: 3.8716 - accuracy: 0.2824 - val_loss: 2.9699 - val_accuracy: 0.4361
Epoch 37/100
2/2 [==============================] - 0s 32ms/step - loss: 3.8148 - accuracy: 0.3333 - val_loss: 2.9677 - val_accuracy: 0.4393
Epoch 38/100
2/2 [==============================] - 0s 32ms/step - loss: 3.8297 - accuracy: 0.3284 - val_loss: 2.9656 - val_accuracy: 0.4393
Epoch 39/100
2/2 [==============================] - 0s 31ms/step - loss: 3.8443 - accuracy: 0.2874 - val_loss: 2.9637 - val_accuracy: 0.4393
Epoch 40/100
2/2 [==============================] - 0s 31ms/step - loss: 3.7933 - accuracy: 0.3218 - val_loss: 2.9619 - val_accuracy: 0.4393
Epoch 41/100
2/2 [==============================] - 0s 31ms/step - loss: 3.7620 - accuracy: 0.3284 - val_loss: 2.9595 - val_accuracy: 0.4393
Epoch 42/100
2/2 [==============================] - 0s 31ms/step - loss: 3.7967 - accuracy: 0.2956 - val_loss: 2.9576 - val_accuracy: 0.4426
Epoch 43/100
2/2 [==============================] - 0s 47ms/step - loss: 3.7916 - accuracy: 0.2841 - val_loss: 2.9553 - val_accuracy: 0.4393
Epoch 44/100
2/2 [==============================] - 0s 51ms/step - loss: 3.8435 - accuracy: 0.3021 - val_loss: 2.9531 - val_accuracy: 0.4393
Epoch 45/100
2/2 [==============================] - 0s 40ms/step - loss: 3.8302 - accuracy: 0.3087 - val_loss: 2.9510 - val_accuracy: 0.4393
Epoch 46/100
2/2 [==============================] - 0s 48ms/step - loss: 3.7400 - accuracy: 0.3153 - val_loss: 2.9483 - val_accuracy: 0.4426
Epoch 47/100
2/2 [==============================] - 0s 49ms/step - loss: 3.7822 - accuracy: 0.3103 - val_loss: 2.9458 - val_accuracy: 0.4525
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 3.7164 - accuracy: 0.3350 - val_loss: 2.9429 - val_accuracy: 0.4525
Epoch 49/100
2/2 [==============================] - 0s 36ms/step - loss: 3.6919 - accuracy: 0.3317 - val_loss: 2.9405 - val_accuracy: 0.4525
Epoch 50/100
2/2 [==============================] - 0s 34ms/step - loss: 3.7493 - accuracy: 0.3218 - val_loss: 2.9387 - val_accuracy: 0.4525
Epoch 51/100
2/2 [==============================] - 0s 36ms/step - loss: 3.6791 - accuracy: 0.3103 - val_loss: 2.9365 - val_accuracy: 0.4590
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 3.7114 - accuracy: 0.3284 - val_loss: 2.9341 - val_accuracy: 0.4590
Epoch 53/100
2/2 [==============================] - 0s 36ms/step - loss: 3.6720 - accuracy: 0.3202 - val_loss: 2.9317 - val_accuracy: 0.4590
Epoch 54/100
2/2 [==============================] - 0s 37ms/step - loss: 3.6750 - accuracy: 0.3038 - val_loss: 2.9294 - val_accuracy: 0.4656
Epoch 55/100
2/2 [==============================] - 0s 50ms/step - loss: 3.6399 - accuracy: 0.3169 - val_loss: 2.9274 - val_accuracy: 0.4656
Epoch 56/100
2/2 [==============================] - 0s 50ms/step - loss: 3.7300 - accuracy: 0.3153 - val_loss: 2.9251 - val_accuracy: 0.4656
Epoch 57/100
2/2 [==============================] - 0s 48ms/step - loss: 3.6986 - accuracy: 0.3350 - val_loss: 2.9226 - val_accuracy: 0.4656
Epoch 58/100
2/2 [==============================] - 0s 50ms/step - loss: 3.5887 - accuracy: 0.3415 - val_loss: 2.9200 - val_accuracy: 0.4656
Epoch 59/100
2/2 [==============================] - 0s 50ms/step - loss: 3.6321 - accuracy: 0.3153 - val_loss: 2.9172 - val_accuracy: 0.4689
Epoch 60/100
2/2 [==============================] - 0s 50ms/step - loss: 3.5564 - accuracy: 0.3432 - val_loss: 2.9148 - val_accuracy: 0.4689
Epoch 61/100
2/2 [==============================] - 0s 36ms/step - loss: 3.6825 - accuracy: 0.2890 - val_loss: 2.9121 - val_accuracy: 0.4656
Epoch 62/100
2/2 [==============================] - 0s 51ms/step - loss: 3.5199 - accuracy: 0.3498 - val_loss: 2.9095 - val_accuracy: 0.4689
Epoch 63/100
2/2 [==============================] - 0s 51ms/step - loss: 3.5230 - accuracy: 0.3645 - val_loss: 2.9070 - val_accuracy: 0.4689
Epoch 64/100
2/2 [==============================] - 0s 50ms/step - loss: 3.5579 - accuracy: 0.3235 - val_loss: 2.9048 - val_accuracy: 0.4656
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 3.5549 - accuracy: 0.3333 - val_loss: 2.9023 - val_accuracy: 0.4689
Epoch 66/100
2/2 [==============================] - 0s 34ms/step - loss: 3.5297 - accuracy: 0.3383 - val_loss: 2.8996 - val_accuracy: 0.4689
Epoch 67/100
2/2 [==============================] - 0s 30ms/step - loss: 3.4655 - accuracy: 0.3744 - val_loss: 2.8970 - val_accuracy: 0.4721
Epoch 68/100
2/2 [==============================] - 0s 35ms/step - loss: 3.4846 - accuracy: 0.3563 - val_loss: 2.8942 - val_accuracy: 0.4721
Epoch 69/100
2/2 [==============================] - 0s 46ms/step - loss: 3.5098 - accuracy: 0.3629 - val_loss: 2.8912 - val_accuracy: 0.4721
Epoch 70/100
2/2 [==============================] - 0s 32ms/step - loss: 3.5290 - accuracy: 0.3432 - val_loss: 2.8876 - val_accuracy: 0.4754
Epoch 71/100
2/2 [==============================] - 0s 31ms/step - loss: 3.5355 - accuracy: 0.3350 - val_loss: 2.8851 - val_accuracy: 0.4754
Epoch 72/100
2/2 [==============================] - 0s 32ms/step - loss: 3.5435 - accuracy: 0.3317 - val_loss: 2.8826 - val_accuracy: 0.4754
Epoch 73/100
2/2 [==============================] - 0s 31ms/step - loss: 3.5498 - accuracy: 0.3317 - val_loss: 2.8794 - val_accuracy: 0.4787
Epoch 74/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4868 - accuracy: 0.3498 - val_loss: 2.8765 - val_accuracy: 0.4787
Epoch 75/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4666 - accuracy: 0.3383 - val_loss: 2.8735 - val_accuracy: 0.4787
Epoch 76/100
2/2 [==============================] - 0s 29ms/step - loss: 3.5228 - accuracy: 0.3415 - val_loss: 2.8704 - val_accuracy: 0.4820
Epoch 77/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4125 - accuracy: 0.3563 - val_loss: 2.8673 - val_accuracy: 0.4885
Epoch 78/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4443 - accuracy: 0.3777 - val_loss: 2.8638 - val_accuracy: 0.4820
Epoch 79/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3589 - accuracy: 0.4023 - val_loss: 2.8607 - val_accuracy: 0.4820
Epoch 80/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4015 - accuracy: 0.3744 - val_loss: 2.8574 - val_accuracy: 0.4820
Epoch 81/100
2/2 [==============================] - 0s 32ms/step - loss: 3.3256 - accuracy: 0.4122 - val_loss: 2.8539 - val_accuracy: 0.4820
Epoch 82/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3115 - accuracy: 0.3941 - val_loss: 2.8510 - val_accuracy: 0.4852
Epoch 83/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3767 - accuracy: 0.3596 - val_loss: 2.8481 - val_accuracy: 0.4852
Epoch 84/100
2/2 [==============================] - 0s 44ms/step - loss: 3.4812 - accuracy: 0.3383 - val_loss: 2.8451 - val_accuracy: 0.4820
Epoch 85/100
2/2 [==============================] - 0s 33ms/step - loss: 3.3290 - accuracy: 0.3547 - val_loss: 2.8423 - val_accuracy: 0.4820
Epoch 86/100
2/2 [==============================] - 0s 33ms/step - loss: 3.2590 - accuracy: 0.3924 - val_loss: 2.8391 - val_accuracy: 0.4885
Epoch 87/100
2/2 [==============================] - 0s 33ms/step - loss: 3.3798 - accuracy: 0.3695 - val_loss: 2.8361 - val_accuracy: 0.4885
Epoch 88/100
2/2 [==============================] - 0s 34ms/step - loss: 3.3735 - accuracy: 0.3645 - val_loss: 2.8333 - val_accuracy: 0.4918
Epoch 89/100
2/2 [==============================] - 0s 34ms/step - loss: 3.3766 - accuracy: 0.3924 - val_loss: 2.8303 - val_accuracy: 0.4918
Epoch 90/100
2/2 [==============================] - 0s 32ms/step - loss: 3.3413 - accuracy: 0.3859 - val_loss: 2.8274 - val_accuracy: 0.4918
Epoch 91/100
2/2 [==============================] - 0s 35ms/step - loss: 3.3317 - accuracy: 0.3744 - val_loss: 2.8243 - val_accuracy: 0.4951
Epoch 92/100
2/2 [==============================] - 0s 34ms/step - loss: 3.4008 - accuracy: 0.3678 - val_loss: 2.8212 - val_accuracy: 0.4951
Epoch 93/100
2/2 [==============================] - 0s 35ms/step - loss: 3.3672 - accuracy: 0.3547 - val_loss: 2.8183 - val_accuracy: 0.4984
Epoch 94/100
2/2 [==============================] - 0s 51ms/step - loss: 3.3576 - accuracy: 0.3842 - val_loss: 2.8146 - val_accuracy: 0.4951
Epoch 95/100
2/2 [==============================] - 0s 48ms/step - loss: 3.2727 - accuracy: 0.4105 - val_loss: 2.8118 - val_accuracy: 0.4951
Epoch 96/100
2/2 [==============================] - 0s 34ms/step - loss: 3.3147 - accuracy: 0.3908 - val_loss: 2.8083 - val_accuracy: 0.5049
Epoch 97/100
2/2 [==============================] - 0s 33ms/step - loss: 3.2344 - accuracy: 0.4236 - val_loss: 2.8053 - val_accuracy: 0.5115
Epoch 98/100
2/2 [==============================] - 0s 33ms/step - loss: 3.2666 - accuracy: 0.3990 - val_loss: 2.8026 - val_accuracy: 0.5115
Epoch 99/100
2/2 [==============================] - 0s 33ms/step - loss: 3.3091 - accuracy: 0.3842 - val_loss: 2.7991 - val_accuracy: 0.5180
Epoch 100/100
2/2 [==============================] - 0s 28ms/step - loss: 3.2448 - accuracy: 0.4122 - val_loss: 2.7958 - val_accuracy: 0.5115
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 2s 251ms/step - loss: 3.6069 - accuracy: 0.3103 - val_loss: 2.7870 - val_accuracy: 0.7869
Epoch 2/100
2/2 [==============================] - 0s 33ms/step - loss: 3.5917 - accuracy: 0.3169 - val_loss: 2.7894 - val_accuracy: 0.7902
Epoch 3/100
2/2 [==============================] - 0s 33ms/step - loss: 3.6081 - accuracy: 0.3169 - val_loss: 2.7910 - val_accuracy: 0.7902
Epoch 4/100
2/2 [==============================] - 0s 44ms/step - loss: 3.6481 - accuracy: 0.3103 - val_loss: 2.7923 - val_accuracy: 0.7836
Epoch 5/100
2/2 [==============================] - 0s 35ms/step - loss: 3.6439 - accuracy: 0.3186 - val_loss: 2.7931 - val_accuracy: 0.7803
Epoch 6/100
2/2 [==============================] - 0s 40ms/step - loss: 3.5212 - accuracy: 0.3645 - val_loss: 2.7936 - val_accuracy: 0.7803
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 3.5519 - accuracy: 0.3383 - val_loss: 2.7939 - val_accuracy: 0.7770
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 3.6164 - accuracy: 0.3218 - val_loss: 2.7940 - val_accuracy: 0.7705
Epoch 9/100
2/2 [==============================] - 0s 33ms/step - loss: 3.5400 - accuracy: 0.3333 - val_loss: 2.7936 - val_accuracy: 0.7705
Epoch 10/100
2/2 [==============================] - 0s 32ms/step - loss: 3.6315 - accuracy: 0.3251 - val_loss: 2.7932 - val_accuracy: 0.7672
Epoch 11/100
2/2 [==============================] - 0s 33ms/step - loss: 3.5667 - accuracy: 0.3333 - val_loss: 2.7925 - val_accuracy: 0.7607
Epoch 12/100
2/2 [==============================] - 0s 42ms/step - loss: 3.5802 - accuracy: 0.3383 - val_loss: 2.7921 - val_accuracy: 0.7508
Epoch 13/100
2/2 [==============================] - 0s 30ms/step - loss: 3.5604 - accuracy: 0.3136 - val_loss: 2.7913 - val_accuracy: 0.7508
Epoch 14/100
2/2 [==============================] - 0s 37ms/step - loss: 3.6157 - accuracy: 0.3432 - val_loss: 2.7905 - val_accuracy: 0.7410
Epoch 15/100
2/2 [==============================] - 0s 35ms/step - loss: 3.5996 - accuracy: 0.3333 - val_loss: 2.7895 - val_accuracy: 0.7410
Epoch 16/100
2/2 [==============================] - 0s 34ms/step - loss: 3.5156 - accuracy: 0.3350 - val_loss: 2.7884 - val_accuracy: 0.7410
Epoch 17/100
2/2 [==============================] - 0s 35ms/step - loss: 3.4430 - accuracy: 0.3744 - val_loss: 2.7875 - val_accuracy: 0.7410
Epoch 18/100
2/2 [==============================] - 0s 40ms/step - loss: 3.4679 - accuracy: 0.3777 - val_loss: 2.7863 - val_accuracy: 0.7410
Epoch 19/100
2/2 [==============================] - 0s 33ms/step - loss: 3.4766 - accuracy: 0.3727 - val_loss: 2.7853 - val_accuracy: 0.7377
Epoch 20/100
2/2 [==============================] - 0s 34ms/step - loss: 3.5252 - accuracy: 0.3629 - val_loss: 2.7840 - val_accuracy: 0.7410
Epoch 21/100
2/2 [==============================] - 0s 32ms/step - loss: 3.4961 - accuracy: 0.3596 - val_loss: 2.7829 - val_accuracy: 0.7377
Epoch 22/100
2/2 [==============================] - 0s 34ms/step - loss: 3.5152 - accuracy: 0.3202 - val_loss: 2.7820 - val_accuracy: 0.7344
Epoch 23/100
2/2 [==============================] - 0s 34ms/step - loss: 3.4574 - accuracy: 0.3498 - val_loss: 2.7808 - val_accuracy: 0.7344
Epoch 24/100
2/2 [==============================] - 0s 34ms/step - loss: 3.5190 - accuracy: 0.3448 - val_loss: 2.7798 - val_accuracy: 0.7311
Epoch 25/100
2/2 [==============================] - 0s 33ms/step - loss: 3.4345 - accuracy: 0.3580 - val_loss: 2.7787 - val_accuracy: 0.7311
Epoch 26/100
2/2 [==============================] - 0s 42ms/step - loss: 3.5162 - accuracy: 0.3629 - val_loss: 2.7776 - val_accuracy: 0.7246
Epoch 27/100
2/2 [==============================] - 0s 42ms/step - loss: 3.4669 - accuracy: 0.3530 - val_loss: 2.7765 - val_accuracy: 0.7246
Epoch 28/100
2/2 [==============================] - 0s 32ms/step - loss: 3.4983 - accuracy: 0.3547 - val_loss: 2.7753 - val_accuracy: 0.7246
Epoch 29/100
2/2 [==============================] - 0s 34ms/step - loss: 3.3772 - accuracy: 0.3695 - val_loss: 2.7741 - val_accuracy: 0.7246
Epoch 30/100
2/2 [==============================] - 0s 34ms/step - loss: 3.5224 - accuracy: 0.3448 - val_loss: 2.7726 - val_accuracy: 0.7213
Epoch 31/100
2/2 [==============================] - 0s 33ms/step - loss: 3.3723 - accuracy: 0.3629 - val_loss: 2.7713 - val_accuracy: 0.7246
Epoch 32/100
2/2 [==============================] - 0s 34ms/step - loss: 3.3657 - accuracy: 0.3875 - val_loss: 2.7696 - val_accuracy: 0.7246
Epoch 33/100
2/2 [==============================] - 0s 33ms/step - loss: 3.4348 - accuracy: 0.3563 - val_loss: 2.7685 - val_accuracy: 0.7213
Epoch 34/100
2/2 [==============================] - 0s 33ms/step - loss: 3.3586 - accuracy: 0.3826 - val_loss: 2.7667 - val_accuracy: 0.7180
Epoch 35/100
2/2 [==============================] - 0s 32ms/step - loss: 3.3887 - accuracy: 0.3908 - val_loss: 2.7650 - val_accuracy: 0.7148
Epoch 36/100
2/2 [==============================] - 0s 32ms/step - loss: 3.3565 - accuracy: 0.3711 - val_loss: 2.7639 - val_accuracy: 0.7180
Epoch 37/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4007 - accuracy: 0.3629 - val_loss: 2.7626 - val_accuracy: 0.7180
Epoch 38/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3619 - accuracy: 0.3826 - val_loss: 2.7611 - val_accuracy: 0.7213
Epoch 39/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3913 - accuracy: 0.3744 - val_loss: 2.7596 - val_accuracy: 0.7213
Epoch 40/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3672 - accuracy: 0.3974 - val_loss: 2.7582 - val_accuracy: 0.7180
Epoch 41/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4156 - accuracy: 0.3957 - val_loss: 2.7567 - val_accuracy: 0.7180
Epoch 42/100
2/2 [==============================] - 0s 48ms/step - loss: 3.3419 - accuracy: 0.3892 - val_loss: 2.7554 - val_accuracy: 0.7082
Epoch 43/100
2/2 [==============================] - 0s 50ms/step - loss: 3.3408 - accuracy: 0.3941 - val_loss: 2.7538 - val_accuracy: 0.7082
Epoch 44/100
2/2 [==============================] - 0s 45ms/step - loss: 3.3406 - accuracy: 0.4056 - val_loss: 2.7521 - val_accuracy: 0.7082
Epoch 45/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3646 - accuracy: 0.3744 - val_loss: 2.7508 - val_accuracy: 0.7082
Epoch 46/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4205 - accuracy: 0.3678 - val_loss: 2.7491 - val_accuracy: 0.7082
Epoch 47/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3267 - accuracy: 0.3941 - val_loss: 2.7473 - val_accuracy: 0.7082
Epoch 48/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3258 - accuracy: 0.4187 - val_loss: 2.7456 - val_accuracy: 0.7082
Epoch 49/100
2/2 [==============================] - 0s 48ms/step - loss: 3.4141 - accuracy: 0.3580 - val_loss: 2.7438 - val_accuracy: 0.7082
Epoch 50/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3154 - accuracy: 0.3990 - val_loss: 2.7422 - val_accuracy: 0.7082
Epoch 51/100
2/2 [==============================] - 0s 50ms/step - loss: 3.3201 - accuracy: 0.3941 - val_loss: 2.7406 - val_accuracy: 0.7016
Epoch 52/100
2/2 [==============================] - 0s 37ms/step - loss: 3.3449 - accuracy: 0.3695 - val_loss: 2.7389 - val_accuracy: 0.6984
Epoch 53/100
2/2 [==============================] - 0s 35ms/step - loss: 3.3036 - accuracy: 0.3957 - val_loss: 2.7371 - val_accuracy: 0.6984
Epoch 54/100
2/2 [==============================] - 0s 33ms/step - loss: 3.3231 - accuracy: 0.3793 - val_loss: 2.7353 - val_accuracy: 0.6984
Epoch 55/100
2/2 [==============================] - 0s 34ms/step - loss: 3.2375 - accuracy: 0.4269 - val_loss: 2.7335 - val_accuracy: 0.6984
Epoch 56/100
2/2 [==============================] - 0s 50ms/step - loss: 3.2607 - accuracy: 0.4253 - val_loss: 2.7315 - val_accuracy: 0.6951
Epoch 57/100
2/2 [==============================] - 0s 46ms/step - loss: 3.3270 - accuracy: 0.3859 - val_loss: 2.7298 - val_accuracy: 0.6918
Epoch 58/100
2/2 [==============================] - 0s 48ms/step - loss: 3.2551 - accuracy: 0.4154 - val_loss: 2.7279 - val_accuracy: 0.6951
Epoch 59/100
2/2 [==============================] - 0s 41ms/step - loss: 3.2189 - accuracy: 0.4335 - val_loss: 2.7259 - val_accuracy: 0.6951
Epoch 60/100
2/2 [==============================] - 0s 41ms/step - loss: 3.2241 - accuracy: 0.4105 - val_loss: 2.7243 - val_accuracy: 0.6951
Epoch 61/100
2/2 [==============================] - 0s 50ms/step - loss: 3.2390 - accuracy: 0.4007 - val_loss: 2.7223 - val_accuracy: 0.6951
Epoch 62/100
2/2 [==============================] - 0s 93ms/step - loss: 3.2411 - accuracy: 0.3777 - val_loss: 2.7203 - val_accuracy: 0.6951
Epoch 63/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2345 - accuracy: 0.4417 - val_loss: 2.7184 - val_accuracy: 0.6951
Epoch 64/100
2/2 [==============================] - 0s 33ms/step - loss: 3.2058 - accuracy: 0.4236 - val_loss: 2.7168 - val_accuracy: 0.6951
Epoch 65/100
2/2 [==============================] - 0s 36ms/step - loss: 3.2266 - accuracy: 0.3974 - val_loss: 2.7151 - val_accuracy: 0.6951
Epoch 66/100
2/2 [==============================] - 0s 41ms/step - loss: 3.2523 - accuracy: 0.4204 - val_loss: 2.7133 - val_accuracy: 0.6951
Epoch 67/100
2/2 [==============================] - 0s 50ms/step - loss: 3.1973 - accuracy: 0.4368 - val_loss: 2.7112 - val_accuracy: 0.6951
Epoch 68/100
2/2 [==============================] - 0s 50ms/step - loss: 3.1395 - accuracy: 0.4598 - val_loss: 2.7093 - val_accuracy: 0.6918
Epoch 69/100
2/2 [==============================] - 0s 49ms/step - loss: 3.1944 - accuracy: 0.4253 - val_loss: 2.7075 - val_accuracy: 0.6820
Epoch 70/100
2/2 [==============================] - 0s 50ms/step - loss: 3.2097 - accuracy: 0.4187 - val_loss: 2.7053 - val_accuracy: 0.6787
Epoch 71/100
2/2 [==============================] - 0s 46ms/step - loss: 3.2251 - accuracy: 0.4269 - val_loss: 2.7031 - val_accuracy: 0.6787
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2221 - accuracy: 0.4335 - val_loss: 2.7013 - val_accuracy: 0.6787
Epoch 73/100
2/2 [==============================] - 0s 44ms/step - loss: 3.2104 - accuracy: 0.3924 - val_loss: 2.6994 - val_accuracy: 0.6787
Epoch 74/100
2/2 [==============================] - 0s 37ms/step - loss: 3.2009 - accuracy: 0.4072 - val_loss: 2.6974 - val_accuracy: 0.6754
Epoch 75/100
2/2 [==============================] - 0s 32ms/step - loss: 3.2197 - accuracy: 0.4187 - val_loss: 2.6956 - val_accuracy: 0.6754
Epoch 76/100
2/2 [==============================] - 0s 31ms/step - loss: 3.2052 - accuracy: 0.4105 - val_loss: 2.6936 - val_accuracy: 0.6754
Epoch 77/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1758 - accuracy: 0.4351 - val_loss: 2.6916 - val_accuracy: 0.6754
Epoch 78/100
2/2 [==============================] - 0s 31ms/step - loss: 3.0819 - accuracy: 0.4762 - val_loss: 2.6892 - val_accuracy: 0.6754
Epoch 79/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1375 - accuracy: 0.4516 - val_loss: 2.6871 - val_accuracy: 0.6787
Epoch 80/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1437 - accuracy: 0.4253 - val_loss: 2.6851 - val_accuracy: 0.6787
Epoch 81/100
2/2 [==============================] - 0s 32ms/step - loss: 3.2079 - accuracy: 0.4204 - val_loss: 2.6831 - val_accuracy: 0.6787
Epoch 82/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1955 - accuracy: 0.4319 - val_loss: 2.6808 - val_accuracy: 0.6787
Epoch 83/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1595 - accuracy: 0.4433 - val_loss: 2.6785 - val_accuracy: 0.6852
Epoch 84/100
2/2 [==============================] - 0s 31ms/step - loss: 3.0737 - accuracy: 0.4548 - val_loss: 2.6764 - val_accuracy: 0.6820
Epoch 85/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1130 - accuracy: 0.4483 - val_loss: 2.6742 - val_accuracy: 0.6820
Epoch 86/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1787 - accuracy: 0.4122 - val_loss: 2.6719 - val_accuracy: 0.6820
Epoch 87/100
2/2 [==============================] - 0s 33ms/step - loss: 3.0955 - accuracy: 0.4663 - val_loss: 2.6695 - val_accuracy: 0.6852
Epoch 88/100
2/2 [==============================] - 0s 32ms/step - loss: 3.0959 - accuracy: 0.4466 - val_loss: 2.6670 - val_accuracy: 0.6885
Epoch 89/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1513 - accuracy: 0.4204 - val_loss: 2.6650 - val_accuracy: 0.6885
Epoch 90/100
2/2 [==============================] - 0s 31ms/step - loss: 3.0997 - accuracy: 0.4466 - val_loss: 2.6632 - val_accuracy: 0.6885
Epoch 91/100
2/2 [==============================] - 0s 35ms/step - loss: 3.1076 - accuracy: 0.4466 - val_loss: 2.6608 - val_accuracy: 0.6885
Epoch 92/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1578 - accuracy: 0.4516 - val_loss: 2.6587 - val_accuracy: 0.6885
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0469 - accuracy: 0.4729 - val_loss: 2.6566 - val_accuracy: 0.6852
Epoch 94/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0775 - accuracy: 0.4483 - val_loss: 2.6548 - val_accuracy: 0.6820
Epoch 95/100
2/2 [==============================] - 0s 48ms/step - loss: 3.1782 - accuracy: 0.4187 - val_loss: 2.6528 - val_accuracy: 0.6820
Epoch 96/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0452 - accuracy: 0.4745 - val_loss: 2.6505 - val_accuracy: 0.6820
Epoch 97/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0828 - accuracy: 0.4680 - val_loss: 2.6480 - val_accuracy: 0.6820
Epoch 98/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0757 - accuracy: 0.4745 - val_loss: 2.6458 - val_accuracy: 0.6820
Epoch 99/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0549 - accuracy: 0.4565 - val_loss: 2.6436 - val_accuracy: 0.6754
Epoch 100/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0404 - accuracy: 0.4598 - val_loss: 2.6413 - val_accuracy: 0.6754
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 255ms/step - loss: 3.6805 - accuracy: 0.3689 - val_loss: 3.2726 - val_accuracy: 0.1875
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 3.7110 - accuracy: 0.3557 - val_loss: 3.2702 - val_accuracy: 0.1974
Epoch 3/100
2/2 [==============================] - 0s 48ms/step - loss: 3.6544 - accuracy: 0.3705 - val_loss: 3.2670 - val_accuracy: 0.2072
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 3.6186 - accuracy: 0.3984 - val_loss: 3.2634 - val_accuracy: 0.2072
Epoch 5/100
2/2 [==============================] - 0s 78ms/step - loss: 3.6335 - accuracy: 0.3836 - val_loss: 3.2594 - val_accuracy: 0.2072
Epoch 6/100
2/2 [==============================] - 0s 47ms/step - loss: 3.7367 - accuracy: 0.3623 - val_loss: 3.2553 - val_accuracy: 0.2171
Epoch 7/100
2/2 [==============================] - 0s 47ms/step - loss: 3.6142 - accuracy: 0.4213 - val_loss: 3.2508 - val_accuracy: 0.2270
Epoch 8/100
2/2 [==============================] - 0s 31ms/step - loss: 3.6872 - accuracy: 0.3607 - val_loss: 3.2459 - val_accuracy: 0.2270
Epoch 9/100
2/2 [==============================] - 0s 47ms/step - loss: 3.6602 - accuracy: 0.3836 - val_loss: 3.2412 - val_accuracy: 0.2303
Epoch 10/100
2/2 [==============================] - 0s 47ms/step - loss: 3.5514 - accuracy: 0.3902 - val_loss: 3.2363 - val_accuracy: 0.2368
Epoch 11/100
2/2 [==============================] - 0s 47ms/step - loss: 3.6231 - accuracy: 0.4066 - val_loss: 3.2310 - val_accuracy: 0.2401
Epoch 12/100
2/2 [==============================] - 0s 47ms/step - loss: 3.6021 - accuracy: 0.3885 - val_loss: 3.2261 - val_accuracy: 0.2401
Epoch 13/100
2/2 [==============================] - 0s 45ms/step - loss: 3.7466 - accuracy: 0.3672 - val_loss: 3.2208 - val_accuracy: 0.2467
Epoch 14/100
2/2 [==============================] - 0s 47ms/step - loss: 3.5372 - accuracy: 0.3869 - val_loss: 3.2155 - val_accuracy: 0.2467
Epoch 15/100
2/2 [==============================] - 0s 47ms/step - loss: 3.6334 - accuracy: 0.3803 - val_loss: 3.2102 - val_accuracy: 0.2500
Epoch 16/100
2/2 [==============================] - 0s 47ms/step - loss: 3.5339 - accuracy: 0.4180 - val_loss: 3.2047 - val_accuracy: 0.2599
Epoch 17/100
2/2 [==============================] - 0s 47ms/step - loss: 3.5771 - accuracy: 0.3787 - val_loss: 3.1995 - val_accuracy: 0.2730
Epoch 18/100
2/2 [==============================] - 0s 47ms/step - loss: 3.5940 - accuracy: 0.3721 - val_loss: 3.1940 - val_accuracy: 0.2730
Epoch 19/100
2/2 [==============================] - 0s 49ms/step - loss: 3.5754 - accuracy: 0.3967 - val_loss: 3.1885 - val_accuracy: 0.2796
Epoch 20/100
2/2 [==============================] - 0s 47ms/step - loss: 3.5805 - accuracy: 0.4197 - val_loss: 3.1834 - val_accuracy: 0.2829
Epoch 21/100
2/2 [==============================] - 0s 47ms/step - loss: 3.5810 - accuracy: 0.3787 - val_loss: 3.1779 - val_accuracy: 0.2928
Epoch 22/100
2/2 [==============================] - 0s 47ms/step - loss: 3.6115 - accuracy: 0.3852 - val_loss: 3.1727 - val_accuracy: 0.3026
Epoch 23/100
2/2 [==============================] - 0s 31ms/step - loss: 3.5188 - accuracy: 0.3984 - val_loss: 3.1675 - val_accuracy: 0.3059
Epoch 24/100
2/2 [==============================] - 0s 32ms/step - loss: 3.5221 - accuracy: 0.4082 - val_loss: 3.1622 - val_accuracy: 0.3059
Epoch 25/100
2/2 [==============================] - 0s 31ms/step - loss: 3.5572 - accuracy: 0.4148 - val_loss: 3.1570 - val_accuracy: 0.3158
Epoch 26/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4775 - accuracy: 0.4164 - val_loss: 3.1522 - val_accuracy: 0.3257
Epoch 27/100
2/2 [==============================] - 0s 31ms/step - loss: 3.5537 - accuracy: 0.3902 - val_loss: 3.1468 - val_accuracy: 0.3454
Epoch 28/100
2/2 [==============================] - 0s 32ms/step - loss: 3.4876 - accuracy: 0.4049 - val_loss: 3.1420 - val_accuracy: 0.3454
Epoch 29/100
2/2 [==============================] - 0s 33ms/step - loss: 3.4820 - accuracy: 0.4311 - val_loss: 3.1366 - val_accuracy: 0.3454
Epoch 30/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4779 - accuracy: 0.4279 - val_loss: 3.1315 - val_accuracy: 0.3520
Epoch 31/100
2/2 [==============================] - 0s 31ms/step - loss: 3.5236 - accuracy: 0.4049 - val_loss: 3.1261 - val_accuracy: 0.3520
Epoch 32/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4733 - accuracy: 0.3984 - val_loss: 3.1212 - val_accuracy: 0.3618
Epoch 33/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4605 - accuracy: 0.4213 - val_loss: 3.1164 - val_accuracy: 0.3750
Epoch 34/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4752 - accuracy: 0.4246 - val_loss: 3.1117 - val_accuracy: 0.3783
Epoch 35/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4106 - accuracy: 0.4590 - val_loss: 3.1064 - val_accuracy: 0.3816
Epoch 36/100
2/2 [==============================] - 0s 48ms/step - loss: 3.5048 - accuracy: 0.4246 - val_loss: 3.1013 - val_accuracy: 0.3849
Epoch 37/100
2/2 [==============================] - 0s 51ms/step - loss: 3.4438 - accuracy: 0.4443 - val_loss: 3.0963 - val_accuracy: 0.3882
Epoch 38/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4790 - accuracy: 0.4033 - val_loss: 3.0915 - val_accuracy: 0.3947
Epoch 39/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4608 - accuracy: 0.4131 - val_loss: 3.0864 - val_accuracy: 0.3980
Epoch 40/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4224 - accuracy: 0.4328 - val_loss: 3.0817 - val_accuracy: 0.4013
Epoch 41/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3806 - accuracy: 0.4459 - val_loss: 3.0769 - val_accuracy: 0.4046
Epoch 42/100
2/2 [==============================] - 0s 43ms/step - loss: 3.3792 - accuracy: 0.4525 - val_loss: 3.0720 - val_accuracy: 0.4046
Epoch 43/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4778 - accuracy: 0.4016 - val_loss: 3.0674 - val_accuracy: 0.4112
Epoch 44/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3997 - accuracy: 0.4180 - val_loss: 3.0623 - val_accuracy: 0.4145
Epoch 45/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4367 - accuracy: 0.4115 - val_loss: 3.0571 - val_accuracy: 0.4178
Epoch 46/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4006 - accuracy: 0.4361 - val_loss: 3.0521 - val_accuracy: 0.4309
Epoch 47/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3588 - accuracy: 0.4721 - val_loss: 3.0476 - val_accuracy: 0.4507
Epoch 48/100
2/2 [==============================] - 0s 47ms/step - loss: 3.4370 - accuracy: 0.4377 - val_loss: 3.0428 - val_accuracy: 0.4507
Epoch 49/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3514 - accuracy: 0.4328 - val_loss: 3.0383 - val_accuracy: 0.4539
Epoch 50/100
2/2 [==============================] - 0s 31ms/step - loss: 3.4141 - accuracy: 0.4344 - val_loss: 3.0335 - val_accuracy: 0.4605
Epoch 51/100
2/2 [==============================] - 0s 32ms/step - loss: 3.3794 - accuracy: 0.4557 - val_loss: 3.0289 - val_accuracy: 0.4671
Epoch 52/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3633 - accuracy: 0.4475 - val_loss: 3.0244 - val_accuracy: 0.4671
Epoch 53/100
2/2 [==============================] - 0s 32ms/step - loss: 3.2819 - accuracy: 0.4721 - val_loss: 3.0201 - val_accuracy: 0.4737
Epoch 54/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3323 - accuracy: 0.4508 - val_loss: 3.0159 - val_accuracy: 0.4770
Epoch 55/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3881 - accuracy: 0.4557 - val_loss: 3.0117 - val_accuracy: 0.4770
Epoch 56/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2967 - accuracy: 0.4508 - val_loss: 3.0069 - val_accuracy: 0.4836
Epoch 57/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3427 - accuracy: 0.4705 - val_loss: 3.0029 - val_accuracy: 0.4868
Epoch 58/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3270 - accuracy: 0.4410 - val_loss: 2.9983 - val_accuracy: 0.4868
Epoch 59/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3541 - accuracy: 0.4377 - val_loss: 2.9940 - val_accuracy: 0.4901
Epoch 60/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3111 - accuracy: 0.4492 - val_loss: 2.9899 - val_accuracy: 0.5000
Epoch 61/100
2/2 [==============================] - 0s 31ms/step - loss: 3.2422 - accuracy: 0.4262 - val_loss: 2.9857 - val_accuracy: 0.4967
Epoch 62/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3008 - accuracy: 0.4705 - val_loss: 2.9817 - val_accuracy: 0.4967
Epoch 63/100
2/2 [==============================] - 0s 31ms/step - loss: 3.3168 - accuracy: 0.4557 - val_loss: 2.9775 - val_accuracy: 0.5033
Epoch 64/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3272 - accuracy: 0.4492 - val_loss: 2.9733 - val_accuracy: 0.5066
Epoch 65/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2497 - accuracy: 0.4590 - val_loss: 2.9693 - val_accuracy: 0.5132
Epoch 66/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3016 - accuracy: 0.4639 - val_loss: 2.9651 - val_accuracy: 0.5164
Epoch 67/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2969 - accuracy: 0.4607 - val_loss: 2.9611 - val_accuracy: 0.5164
Epoch 68/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2896 - accuracy: 0.4787 - val_loss: 2.9570 - val_accuracy: 0.5164
Epoch 69/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2284 - accuracy: 0.4557 - val_loss: 2.9530 - val_accuracy: 0.5197
Epoch 70/100
2/2 [==============================] - 0s 31ms/step - loss: 3.2882 - accuracy: 0.4705 - val_loss: 2.9488 - val_accuracy: 0.5197
Epoch 71/100
2/2 [==============================] - 0s 31ms/step - loss: 3.2352 - accuracy: 0.4803 - val_loss: 2.9449 - val_accuracy: 0.5197
Epoch 72/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1822 - accuracy: 0.5197 - val_loss: 2.9412 - val_accuracy: 0.5230
Epoch 73/100
2/2 [==============================] - 0s 31ms/step - loss: 3.2775 - accuracy: 0.4475 - val_loss: 2.9373 - val_accuracy: 0.5263
Epoch 74/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1981 - accuracy: 0.4639 - val_loss: 2.9327 - val_accuracy: 0.5263
Epoch 75/100
2/2 [==============================] - 0s 32ms/step - loss: 3.2500 - accuracy: 0.4885 - val_loss: 2.9288 - val_accuracy: 0.5263
Epoch 76/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2711 - accuracy: 0.4393 - val_loss: 2.9249 - val_accuracy: 0.5263
Epoch 77/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2835 - accuracy: 0.4590 - val_loss: 2.9208 - val_accuracy: 0.5329
Epoch 78/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2488 - accuracy: 0.4508 - val_loss: 2.9171 - val_accuracy: 0.5329
Epoch 79/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1372 - accuracy: 0.4918 - val_loss: 2.9132 - val_accuracy: 0.5329
Epoch 80/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1983 - accuracy: 0.4984 - val_loss: 2.9097 - val_accuracy: 0.5362
Epoch 81/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1605 - accuracy: 0.4803 - val_loss: 2.9055 - val_accuracy: 0.5395
Epoch 82/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2097 - accuracy: 0.4705 - val_loss: 2.9018 - val_accuracy: 0.5395
Epoch 83/100
2/2 [==============================] - 0s 48ms/step - loss: 3.2290 - accuracy: 0.4459 - val_loss: 2.8979 - val_accuracy: 0.5395
Epoch 84/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2126 - accuracy: 0.4820 - val_loss: 2.8943 - val_accuracy: 0.5428
Epoch 85/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1966 - accuracy: 0.4885 - val_loss: 2.8904 - val_accuracy: 0.5428
Epoch 86/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1073 - accuracy: 0.4967 - val_loss: 2.8871 - val_accuracy: 0.5395
Epoch 87/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1231 - accuracy: 0.5033 - val_loss: 2.8841 - val_accuracy: 0.5428
Epoch 88/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1902 - accuracy: 0.4787 - val_loss: 2.8806 - val_accuracy: 0.5461
Epoch 89/100
2/2 [==============================] - 0s 33ms/step - loss: 3.1813 - accuracy: 0.4836 - val_loss: 2.8773 - val_accuracy: 0.5493
Epoch 90/100
2/2 [==============================] - 0s 32ms/step - loss: 3.0706 - accuracy: 0.5213 - val_loss: 2.8736 - val_accuracy: 0.5493
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 3.1478 - accuracy: 0.4934 - val_loss: 2.8694 - val_accuracy: 0.5493
Epoch 92/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1864 - accuracy: 0.4787 - val_loss: 2.8656 - val_accuracy: 0.5493
Epoch 93/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1215 - accuracy: 0.4902 - val_loss: 2.8616 - val_accuracy: 0.5493
Epoch 94/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1380 - accuracy: 0.5066 - val_loss: 2.8581 - val_accuracy: 0.5493
Epoch 95/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1343 - accuracy: 0.4852 - val_loss: 2.8544 - val_accuracy: 0.5526
Epoch 96/100
2/2 [==============================] - 0s 50ms/step - loss: 3.0444 - accuracy: 0.5246 - val_loss: 2.8509 - val_accuracy: 0.5592
Epoch 97/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1182 - accuracy: 0.4885 - val_loss: 2.8470 - val_accuracy: 0.5592
Epoch 98/100
2/2 [==============================] - 0s 48ms/step - loss: 3.0281 - accuracy: 0.5230 - val_loss: 2.8437 - val_accuracy: 0.5625
Epoch 99/100
2/2 [==============================] - 0s 33ms/step - loss: 3.0100 - accuracy: 0.5443 - val_loss: 2.8398 - val_accuracy: 0.5691
Epoch 100/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1008 - accuracy: 0.5213 - val_loss: 2.8367 - val_accuracy: 0.5691
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 5
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 128, 'learning_rate_decay': 1e-05, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 238ms/step - loss: 3.5521 - accuracy: 0.3366 - val_loss: 2.5362 - val_accuracy: 0.7475
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1368 - accuracy: 0.5649 - val_loss: 3.1137 - val_accuracy: 0.8131
Epoch 3/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0270 - accuracy: 0.8259 - val_loss: 3.2206 - val_accuracy: 0.8131
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1710 - accuracy: 0.8506 - val_loss: 3.1737 - val_accuracy: 0.8262
Epoch 5/100
2/2 [==============================] - 0s 31ms/step - loss: 2.9377 - accuracy: 0.8752 - val_loss: 2.9460 - val_accuracy: 0.8426
Epoch 6/100
2/2 [==============================] - 0s 31ms/step - loss: 2.7273 - accuracy: 0.8506 - val_loss: 2.7372 - val_accuracy: 0.8393
Epoch 7/100
2/2 [==============================] - 0s 47ms/step - loss: 2.4366 - accuracy: 0.8506 - val_loss: 2.5802 - val_accuracy: 0.8164
Epoch 8/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3009 - accuracy: 0.8456 - val_loss: 2.4286 - val_accuracy: 0.8164
Epoch 9/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1859 - accuracy: 0.8424 - val_loss: 2.3638 - val_accuracy: 0.8164
Epoch 10/100
2/2 [==============================] - 0s 31ms/step - loss: 2.0341 - accuracy: 0.8325 - val_loss: 2.2241 - val_accuracy: 0.8164
Epoch 11/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9171 - accuracy: 0.8539 - val_loss: 2.1177 - val_accuracy: 0.8164
Epoch 12/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7621 - accuracy: 0.8571 - val_loss: 1.9510 - val_accuracy: 0.8164
Epoch 13/100
2/2 [==============================] - 0s 30ms/step - loss: 1.7418 - accuracy: 0.8522 - val_loss: 2.0484 - val_accuracy: 0.8164
Epoch 14/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6258 - accuracy: 0.8736 - val_loss: 1.6851 - val_accuracy: 0.8197
Epoch 15/100
2/2 [==============================] - 0s 40ms/step - loss: 1.5255 - accuracy: 0.8342 - val_loss: 1.8121 - val_accuracy: 0.8164
Epoch 16/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4637 - accuracy: 0.8654 - val_loss: 1.6536 - val_accuracy: 0.8164
Epoch 17/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3968 - accuracy: 0.8604 - val_loss: 1.5167 - val_accuracy: 0.8164
Epoch 18/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3308 - accuracy: 0.8440 - val_loss: 1.7819 - val_accuracy: 0.8164
Epoch 19/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3281 - accuracy: 0.8703 - val_loss: 1.3698 - val_accuracy: 0.8164
Epoch 20/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2517 - accuracy: 0.8342 - val_loss: 1.6444 - val_accuracy: 0.8164
Epoch 21/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3020 - accuracy: 0.8686 - val_loss: 1.5584 - val_accuracy: 0.8164
Epoch 22/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3049 - accuracy: 0.8440 - val_loss: 1.2974 - val_accuracy: 0.7902
Epoch 23/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3937 - accuracy: 0.7291 - val_loss: 1.4932 - val_accuracy: 0.8164
Epoch 24/100
2/2 [==============================] - 0s 34ms/step - loss: 1.2566 - accuracy: 0.8703 - val_loss: 1.4599 - val_accuracy: 0.8164
Epoch 25/100
2/2 [==============================] - 0s 33ms/step - loss: 1.1748 - accuracy: 0.8686 - val_loss: 1.1576 - val_accuracy: 0.8557
Epoch 26/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1357 - accuracy: 0.8062 - val_loss: 1.2999 - val_accuracy: 0.8164
Epoch 27/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1103 - accuracy: 0.8719 - val_loss: 1.2447 - val_accuracy: 0.8164
Epoch 28/100
2/2 [==============================] - 0s 48ms/step - loss: 1.0621 - accuracy: 0.8555 - val_loss: 1.1178 - val_accuracy: 0.8525
Epoch 29/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0281 - accuracy: 0.8391 - val_loss: 1.2566 - val_accuracy: 0.8164
Epoch 30/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0028 - accuracy: 0.8670 - val_loss: 1.1568 - val_accuracy: 0.8164
Epoch 31/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9437 - accuracy: 0.8670 - val_loss: 1.0091 - val_accuracy: 0.8262
Epoch 32/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9289 - accuracy: 0.8259 - val_loss: 1.0607 - val_accuracy: 0.8164
Epoch 33/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8750 - accuracy: 0.8637 - val_loss: 1.0067 - val_accuracy: 0.8164
Epoch 34/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8538 - accuracy: 0.8588 - val_loss: 1.0050 - val_accuracy: 0.8492
Epoch 35/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8773 - accuracy: 0.8391 - val_loss: 0.9942 - val_accuracy: 0.8164
Epoch 36/100
2/2 [==============================] - 0s 52ms/step - loss: 0.8234 - accuracy: 0.8736 - val_loss: 0.9247 - val_accuracy: 0.8164
Epoch 37/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7745 - accuracy: 0.8703 - val_loss: 0.8804 - val_accuracy: 0.8361
Epoch 38/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7820 - accuracy: 0.8374 - val_loss: 0.9363 - val_accuracy: 0.8164
Epoch 39/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7660 - accuracy: 0.8686 - val_loss: 0.8995 - val_accuracy: 0.8164
Epoch 40/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7190 - accuracy: 0.8703 - val_loss: 0.8164 - val_accuracy: 0.8295
Epoch 41/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7696 - accuracy: 0.8342 - val_loss: 0.8740 - val_accuracy: 0.8164
Epoch 42/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7143 - accuracy: 0.8752 - val_loss: 0.9335 - val_accuracy: 0.8164
Epoch 43/100
2/2 [==============================] - 0s 52ms/step - loss: 0.7149 - accuracy: 0.8752 - val_loss: 0.8086 - val_accuracy: 0.8164
Epoch 44/100
2/2 [==============================] - 0s 42ms/step - loss: 0.6857 - accuracy: 0.8654 - val_loss: 0.7903 - val_accuracy: 0.8164
Epoch 45/100
2/2 [==============================] - 0s 55ms/step - loss: 0.6948 - accuracy: 0.8604 - val_loss: 0.8023 - val_accuracy: 0.8164
Epoch 46/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6776 - accuracy: 0.8867 - val_loss: 0.7643 - val_accuracy: 0.8230
Epoch 47/100
2/2 [==============================] - 0s 46ms/step - loss: 0.6899 - accuracy: 0.8670 - val_loss: 0.7601 - val_accuracy: 0.8230
Epoch 48/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6780 - accuracy: 0.8588 - val_loss: 0.7926 - val_accuracy: 0.8164
Epoch 49/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6604 - accuracy: 0.8703 - val_loss: 0.7985 - val_accuracy: 0.8164
Epoch 50/100
2/2 [==============================] - 0s 44ms/step - loss: 0.6398 - accuracy: 0.8785 - val_loss: 0.7708 - val_accuracy: 0.8164
Epoch 51/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6481 - accuracy: 0.8736 - val_loss: 0.7731 - val_accuracy: 0.8164
Epoch 52/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6486 - accuracy: 0.8654 - val_loss: 0.7859 - val_accuracy: 0.8164
Epoch 53/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6287 - accuracy: 0.8768 - val_loss: 0.7983 - val_accuracy: 0.8164
Epoch 54/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6260 - accuracy: 0.8785 - val_loss: 0.7789 - val_accuracy: 0.8164
Epoch 55/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6383 - accuracy: 0.8588 - val_loss: 0.7586 - val_accuracy: 0.8164
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6832 - accuracy: 0.8506 - val_loss: 0.7801 - val_accuracy: 0.8164
Epoch 57/100
2/2 [==============================] - 0s 46ms/step - loss: 0.6707 - accuracy: 0.8851 - val_loss: 0.7771 - val_accuracy: 0.8164
Epoch 58/100
2/2 [==============================] - 0s 30ms/step - loss: 0.6646 - accuracy: 0.8604 - val_loss: 0.7722 - val_accuracy: 0.8164
Epoch 59/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6374 - accuracy: 0.8686 - val_loss: 0.8124 - val_accuracy: 0.8164
Epoch 60/100
2/2 [==============================] - 0s 53ms/step - loss: 0.6453 - accuracy: 0.8719 - val_loss: 0.7635 - val_accuracy: 0.8164
Epoch 61/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6395 - accuracy: 0.8736 - val_loss: 0.7340 - val_accuracy: 0.8164
Epoch 62/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6056 - accuracy: 0.8703 - val_loss: 0.7326 - val_accuracy: 0.8164
Epoch 63/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5826 - accuracy: 0.8851 - val_loss: 0.7289 - val_accuracy: 0.8164
Epoch 64/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5785 - accuracy: 0.8686 - val_loss: 0.7128 - val_accuracy: 0.8164
Epoch 65/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5779 - accuracy: 0.8768 - val_loss: 0.7092 - val_accuracy: 0.8164
Epoch 66/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6126 - accuracy: 0.8719 - val_loss: 0.7418 - val_accuracy: 0.8164
Epoch 67/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5956 - accuracy: 0.8736 - val_loss: 0.7135 - val_accuracy: 0.8164
Epoch 68/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5976 - accuracy: 0.8703 - val_loss: 0.6912 - val_accuracy: 0.8131
Epoch 69/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5962 - accuracy: 0.8621 - val_loss: 0.7415 - val_accuracy: 0.8164
Epoch 70/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5971 - accuracy: 0.8686 - val_loss: 0.7171 - val_accuracy: 0.8164
Epoch 71/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5698 - accuracy: 0.8785 - val_loss: 0.6741 - val_accuracy: 0.8164
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5731 - accuracy: 0.8703 - val_loss: 0.6954 - val_accuracy: 0.8164
Epoch 73/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5807 - accuracy: 0.8670 - val_loss: 0.6912 - val_accuracy: 0.8164
Epoch 74/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5611 - accuracy: 0.8834 - val_loss: 0.6637 - val_accuracy: 0.8164
Epoch 75/100
2/2 [==============================] - 0s 52ms/step - loss: 0.5577 - accuracy: 0.8588 - val_loss: 0.6737 - val_accuracy: 0.8164
Epoch 76/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5344 - accuracy: 0.8834 - val_loss: 0.6869 - val_accuracy: 0.8164
Epoch 77/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5510 - accuracy: 0.8801 - val_loss: 0.6557 - val_accuracy: 0.8164
Epoch 78/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5190 - accuracy: 0.8752 - val_loss: 0.6445 - val_accuracy: 0.8164
Epoch 79/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5277 - accuracy: 0.8637 - val_loss: 0.6575 - val_accuracy: 0.8164
Epoch 80/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5357 - accuracy: 0.8834 - val_loss: 0.6791 - val_accuracy: 0.8164
Epoch 81/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5479 - accuracy: 0.8670 - val_loss: 0.6269 - val_accuracy: 0.8164
Epoch 82/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5373 - accuracy: 0.8785 - val_loss: 0.6233 - val_accuracy: 0.8328
Epoch 83/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5399 - accuracy: 0.8604 - val_loss: 0.6906 - val_accuracy: 0.8164
Epoch 84/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5539 - accuracy: 0.8768 - val_loss: 0.7276 - val_accuracy: 0.8164
Epoch 85/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5650 - accuracy: 0.8736 - val_loss: 0.6382 - val_accuracy: 0.8131
Epoch 86/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5223 - accuracy: 0.8752 - val_loss: 0.6122 - val_accuracy: 0.8361
Epoch 87/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5592 - accuracy: 0.8522 - val_loss: 0.6335 - val_accuracy: 0.8197
Epoch 88/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5448 - accuracy: 0.8654 - val_loss: 0.6491 - val_accuracy: 0.8164
Epoch 89/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5248 - accuracy: 0.8686 - val_loss: 0.6360 - val_accuracy: 0.8230
Epoch 90/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5382 - accuracy: 0.8686 - val_loss: 0.6325 - val_accuracy: 0.8164
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5193 - accuracy: 0.8851 - val_loss: 0.6161 - val_accuracy: 0.8164
Epoch 92/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5164 - accuracy: 0.8818 - val_loss: 0.5983 - val_accuracy: 0.8164
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5344 - accuracy: 0.8637 - val_loss: 0.6050 - val_accuracy: 0.8164
Epoch 94/100
2/2 [==============================] - 0s 53ms/step - loss: 0.5340 - accuracy: 0.8736 - val_loss: 0.6643 - val_accuracy: 0.8164
Epoch 95/100
2/2 [==============================] - 0s 69ms/step - loss: 0.5223 - accuracy: 0.8686 - val_loss: 0.6484 - val_accuracy: 0.8164
Epoch 96/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5169 - accuracy: 0.8752 - val_loss: 0.6069 - val_accuracy: 0.8295
Epoch 97/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5439 - accuracy: 0.8489 - val_loss: 0.6285 - val_accuracy: 0.8197
Epoch 98/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5129 - accuracy: 0.8604 - val_loss: 0.7240 - val_accuracy: 0.8164
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5750 - accuracy: 0.8654 - val_loss: 0.6954 - val_accuracy: 0.8164
Epoch 100/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5389 - accuracy: 0.8637 - val_loss: 0.6344 - val_accuracy: 0.8197
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 128, 'learning_rate_decay': 1e-05, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 252ms/step - loss: 3.5351 - accuracy: 0.3284 - val_loss: 2.5808 - val_accuracy: 0.6689
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2388 - accuracy: 0.6420 - val_loss: 2.6320 - val_accuracy: 0.8787
Epoch 3/100
2/2 [==============================] - 0s 31ms/step - loss: 3.0088 - accuracy: 0.8013 - val_loss: 2.8478 - val_accuracy: 0.8951
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 3.0935 - accuracy: 0.8391 - val_loss: 2.9037 - val_accuracy: 0.8852
Epoch 5/100
2/2 [==============================] - 0s 47ms/step - loss: 2.9983 - accuracy: 0.8670 - val_loss: 2.6819 - val_accuracy: 0.8852
Epoch 6/100
2/2 [==============================] - 0s 47ms/step - loss: 2.7716 - accuracy: 0.8342 - val_loss: 2.4733 - val_accuracy: 0.8754
Epoch 7/100
2/2 [==============================] - 0s 32ms/step - loss: 2.6224 - accuracy: 0.7980 - val_loss: 2.3932 - val_accuracy: 0.8721
Epoch 8/100
2/2 [==============================] - 0s 47ms/step - loss: 2.4523 - accuracy: 0.8374 - val_loss: 2.1334 - val_accuracy: 0.8721
Epoch 9/100
2/2 [==============================] - 0s 47ms/step - loss: 2.2364 - accuracy: 0.8292 - val_loss: 2.0231 - val_accuracy: 0.8721
Epoch 10/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0310 - accuracy: 0.8456 - val_loss: 1.8187 - val_accuracy: 0.8721
Epoch 11/100
2/2 [==============================] - 0s 31ms/step - loss: 1.9160 - accuracy: 0.8095 - val_loss: 1.8701 - val_accuracy: 0.8721
Epoch 12/100
2/2 [==============================] - 0s 32ms/step - loss: 1.8394 - accuracy: 0.8473 - val_loss: 1.6488 - val_accuracy: 0.8721
Epoch 13/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7001 - accuracy: 0.8309 - val_loss: 1.5612 - val_accuracy: 0.8721
Epoch 14/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5714 - accuracy: 0.8391 - val_loss: 1.4278 - val_accuracy: 0.8721
Epoch 15/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5402 - accuracy: 0.8062 - val_loss: 1.3438 - val_accuracy: 0.8721
Epoch 16/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4181 - accuracy: 0.8391 - val_loss: 1.4796 - val_accuracy: 0.8721
Epoch 17/100
2/2 [==============================] - 0s 31ms/step - loss: 1.4876 - accuracy: 0.8407 - val_loss: 1.2031 - val_accuracy: 0.8754
Epoch 18/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3544 - accuracy: 0.7980 - val_loss: 1.3414 - val_accuracy: 0.8721
Epoch 19/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3751 - accuracy: 0.8440 - val_loss: 1.3432 - val_accuracy: 0.8721
Epoch 20/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3242 - accuracy: 0.8440 - val_loss: 1.1695 - val_accuracy: 0.8590
Epoch 21/100
2/2 [==============================] - 0s 46ms/step - loss: 1.4527 - accuracy: 0.7915 - val_loss: 1.2814 - val_accuracy: 0.8721
Epoch 22/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2897 - accuracy: 0.8407 - val_loss: 1.2219 - val_accuracy: 0.8721
Epoch 23/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2104 - accuracy: 0.8391 - val_loss: 1.0029 - val_accuracy: 0.8754
Epoch 24/100
2/2 [==============================] - 0s 48ms/step - loss: 1.1661 - accuracy: 0.8243 - val_loss: 1.0836 - val_accuracy: 0.8721
Epoch 25/100
2/2 [==============================] - 0s 48ms/step - loss: 1.1236 - accuracy: 0.8489 - val_loss: 0.9731 - val_accuracy: 0.8721
Epoch 26/100
2/2 [==============================] - 0s 48ms/step - loss: 1.0108 - accuracy: 0.8473 - val_loss: 0.9132 - val_accuracy: 0.8721
Epoch 27/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0625 - accuracy: 0.8046 - val_loss: 1.0333 - val_accuracy: 0.8721
Epoch 28/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0209 - accuracy: 0.8440 - val_loss: 0.9584 - val_accuracy: 0.8721
Epoch 29/100
2/2 [==============================] - 0s 48ms/step - loss: 0.9580 - accuracy: 0.8424 - val_loss: 0.8862 - val_accuracy: 0.8721
Epoch 30/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9584 - accuracy: 0.8177 - val_loss: 0.9407 - val_accuracy: 0.8721
Epoch 31/100
2/2 [==============================] - 0s 49ms/step - loss: 0.9080 - accuracy: 0.8456 - val_loss: 0.8429 - val_accuracy: 0.8721
Epoch 32/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9310 - accuracy: 0.8391 - val_loss: 0.9087 - val_accuracy: 0.8721
Epoch 33/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9278 - accuracy: 0.8424 - val_loss: 0.9553 - val_accuracy: 0.8721
Epoch 34/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9090 - accuracy: 0.8440 - val_loss: 0.7793 - val_accuracy: 0.8721
Epoch 35/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9245 - accuracy: 0.8013 - val_loss: 0.8187 - val_accuracy: 0.8721
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8677 - accuracy: 0.8506 - val_loss: 0.8750 - val_accuracy: 0.8721
Epoch 37/100
2/2 [==============================] - 0s 78ms/step - loss: 0.8481 - accuracy: 0.8637 - val_loss: 0.7683 - val_accuracy: 0.8754
Epoch 38/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8993 - accuracy: 0.8112 - val_loss: 0.7638 - val_accuracy: 0.8721
Epoch 39/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8155 - accuracy: 0.8407 - val_loss: 0.7990 - val_accuracy: 0.8721
Epoch 40/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7786 - accuracy: 0.8539 - val_loss: 0.7161 - val_accuracy: 0.8721
Epoch 41/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7561 - accuracy: 0.8489 - val_loss: 0.7176 - val_accuracy: 0.8721
Epoch 42/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7281 - accuracy: 0.8473 - val_loss: 0.7832 - val_accuracy: 0.8721
Epoch 43/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7416 - accuracy: 0.8473 - val_loss: 0.6998 - val_accuracy: 0.8721
Epoch 44/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6967 - accuracy: 0.8604 - val_loss: 0.6952 - val_accuracy: 0.8721
Epoch 45/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7286 - accuracy: 0.8391 - val_loss: 0.7474 - val_accuracy: 0.8721
Epoch 46/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7004 - accuracy: 0.8555 - val_loss: 0.6880 - val_accuracy: 0.8721
Epoch 47/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7071 - accuracy: 0.8391 - val_loss: 0.6596 - val_accuracy: 0.8721
Epoch 48/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6963 - accuracy: 0.8555 - val_loss: 0.6963 - val_accuracy: 0.8721
Epoch 49/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7070 - accuracy: 0.8489 - val_loss: 0.6815 - val_accuracy: 0.8721
Epoch 50/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7189 - accuracy: 0.8358 - val_loss: 0.6459 - val_accuracy: 0.8721
Epoch 51/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6792 - accuracy: 0.8506 - val_loss: 0.6618 - val_accuracy: 0.8721
Epoch 52/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6888 - accuracy: 0.8571 - val_loss: 0.6723 - val_accuracy: 0.8721
Epoch 53/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7097 - accuracy: 0.8489 - val_loss: 0.6508 - val_accuracy: 0.8721
Epoch 54/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6582 - accuracy: 0.8604 - val_loss: 0.6353 - val_accuracy: 0.8721
Epoch 55/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6467 - accuracy: 0.8424 - val_loss: 0.6130 - val_accuracy: 0.8721
Epoch 56/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6530 - accuracy: 0.8440 - val_loss: 0.6064 - val_accuracy: 0.8721
Epoch 57/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6391 - accuracy: 0.8604 - val_loss: 0.6435 - val_accuracy: 0.8721
Epoch 58/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6383 - accuracy: 0.8506 - val_loss: 0.6865 - val_accuracy: 0.8721
Epoch 59/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6353 - accuracy: 0.8539 - val_loss: 0.6153 - val_accuracy: 0.8721
Epoch 60/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6327 - accuracy: 0.8489 - val_loss: 0.6272 - val_accuracy: 0.8721
Epoch 61/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6356 - accuracy: 0.8456 - val_loss: 0.6374 - val_accuracy: 0.8721
Epoch 62/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6207 - accuracy: 0.8555 - val_loss: 0.5608 - val_accuracy: 0.8721
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6562 - accuracy: 0.8374 - val_loss: 0.6120 - val_accuracy: 0.8721
Epoch 64/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6346 - accuracy: 0.8489 - val_loss: 0.6725 - val_accuracy: 0.8721
Epoch 65/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6816 - accuracy: 0.8407 - val_loss: 0.5631 - val_accuracy: 0.8721
Epoch 66/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6463 - accuracy: 0.8424 - val_loss: 0.5357 - val_accuracy: 0.8754
Epoch 67/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6379 - accuracy: 0.8391 - val_loss: 0.5600 - val_accuracy: 0.8721
Epoch 68/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6093 - accuracy: 0.8555 - val_loss: 0.5473 - val_accuracy: 0.8721
Epoch 69/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6052 - accuracy: 0.8539 - val_loss: 0.5576 - val_accuracy: 0.8721
Epoch 70/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6003 - accuracy: 0.8571 - val_loss: 0.5652 - val_accuracy: 0.8721
Epoch 71/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5957 - accuracy: 0.8489 - val_loss: 0.5372 - val_accuracy: 0.8721
Epoch 72/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6093 - accuracy: 0.8489 - val_loss: 0.5549 - val_accuracy: 0.8721
Epoch 73/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6324 - accuracy: 0.8259 - val_loss: 0.5727 - val_accuracy: 0.8721
Epoch 74/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6095 - accuracy: 0.8374 - val_loss: 0.5810 - val_accuracy: 0.8721
Epoch 75/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6279 - accuracy: 0.8473 - val_loss: 0.5615 - val_accuracy: 0.8721
Epoch 76/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6134 - accuracy: 0.8473 - val_loss: 0.5692 - val_accuracy: 0.8721
Epoch 77/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5733 - accuracy: 0.8522 - val_loss: 0.5936 - val_accuracy: 0.8721
Epoch 78/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6225 - accuracy: 0.8374 - val_loss: 0.5385 - val_accuracy: 0.8721
Epoch 79/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5955 - accuracy: 0.8571 - val_loss: 0.5212 - val_accuracy: 0.8787
Epoch 80/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6292 - accuracy: 0.8292 - val_loss: 0.5750 - val_accuracy: 0.8721
Epoch 81/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6123 - accuracy: 0.8506 - val_loss: 0.6174 - val_accuracy: 0.8721
Epoch 82/100
2/2 [==============================] - 0s 42ms/step - loss: 0.6084 - accuracy: 0.8654 - val_loss: 0.5588 - val_accuracy: 0.8721
Epoch 83/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6007 - accuracy: 0.8588 - val_loss: 0.5322 - val_accuracy: 0.8721
Epoch 84/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6108 - accuracy: 0.8440 - val_loss: 0.5699 - val_accuracy: 0.8721
Epoch 85/100
2/2 [==============================] - 0s 26ms/step - loss: 0.6342 - accuracy: 0.8473 - val_loss: 0.5861 - val_accuracy: 0.8721
Epoch 86/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6297 - accuracy: 0.8407 - val_loss: 0.5351 - val_accuracy: 0.8721
Epoch 87/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6240 - accuracy: 0.8407 - val_loss: 0.5105 - val_accuracy: 0.8951
Epoch 88/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6258 - accuracy: 0.8358 - val_loss: 0.5133 - val_accuracy: 0.8852
Epoch 89/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5884 - accuracy: 0.8473 - val_loss: 0.5367 - val_accuracy: 0.8721
Epoch 90/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5956 - accuracy: 0.8489 - val_loss: 0.5293 - val_accuracy: 0.8721
Epoch 91/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5804 - accuracy: 0.8539 - val_loss: 0.5113 - val_accuracy: 0.8754
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6027 - accuracy: 0.8391 - val_loss: 0.5408 - val_accuracy: 0.8754
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5812 - accuracy: 0.8621 - val_loss: 0.5954 - val_accuracy: 0.8721
Epoch 94/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5760 - accuracy: 0.8571 - val_loss: 0.5838 - val_accuracy: 0.8721
Epoch 95/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5648 - accuracy: 0.8555 - val_loss: 0.5463 - val_accuracy: 0.8721
Epoch 96/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5767 - accuracy: 0.8440 - val_loss: 0.5667 - val_accuracy: 0.8721
Epoch 97/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5697 - accuracy: 0.8456 - val_loss: 0.5803 - val_accuracy: 0.8721
Epoch 98/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5535 - accuracy: 0.8637 - val_loss: 0.5574 - val_accuracy: 0.8721
Epoch 99/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5485 - accuracy: 0.8539 - val_loss: 0.5230 - val_accuracy: 0.8721
Epoch 100/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5672 - accuracy: 0.8407 - val_loss: 0.5717 - val_accuracy: 0.8721
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 5, 'hidden_units': 128, 'learning_rate_decay': 1e-05, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 240ms/step - loss: 3.6063 - accuracy: 0.3574 - val_loss: 2.7792 - val_accuracy: 0.7303
Epoch 2/100
2/2 [==============================] - 0s 31ms/step - loss: 3.6341 - accuracy: 0.6934 - val_loss: 3.0634 - val_accuracy: 0.8618
Epoch 3/100
2/2 [==============================] - 0s 47ms/step - loss: 3.3537 - accuracy: 0.8164 - val_loss: 3.2863 - val_accuracy: 0.8586
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 3.2142 - accuracy: 0.8738 - val_loss: 3.2296 - val_accuracy: 0.7961
Epoch 5/100
2/2 [==============================] - 0s 47ms/step - loss: 3.1446 - accuracy: 0.8344 - val_loss: 3.3639 - val_accuracy: 0.7368
Epoch 6/100
2/2 [==============================] - 0s 32ms/step - loss: 3.1396 - accuracy: 0.8197 - val_loss: 2.9237 - val_accuracy: 0.8487
Epoch 7/100
2/2 [==============================] - 0s 31ms/step - loss: 2.7680 - accuracy: 0.8672 - val_loss: 3.0832 - val_accuracy: 0.8618
Epoch 8/100
2/2 [==============================] - 0s 32ms/step - loss: 2.7968 - accuracy: 0.8574 - val_loss: 2.4732 - val_accuracy: 0.8586
Epoch 9/100
2/2 [==============================] - 0s 47ms/step - loss: 2.2963 - accuracy: 0.8590 - val_loss: 2.2660 - val_accuracy: 0.7796
Epoch 10/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1754 - accuracy: 0.8230 - val_loss: 1.9104 - val_accuracy: 0.8553
Epoch 11/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7962 - accuracy: 0.8787 - val_loss: 2.1293 - val_accuracy: 0.8618
Epoch 12/100
2/2 [==============================] - 0s 37ms/step - loss: 1.9310 - accuracy: 0.8492 - val_loss: 1.9312 - val_accuracy: 0.8618
Epoch 13/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7359 - accuracy: 0.8590 - val_loss: 1.6218 - val_accuracy: 0.8388
Epoch 14/100
2/2 [==============================] - 0s 32ms/step - loss: 1.6895 - accuracy: 0.8295 - val_loss: 1.5457 - val_accuracy: 0.8586
Epoch 15/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4974 - accuracy: 0.8607 - val_loss: 1.6523 - val_accuracy: 0.8618
Epoch 16/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4468 - accuracy: 0.8689 - val_loss: 1.5881 - val_accuracy: 0.8618
Epoch 17/100
2/2 [==============================] - 0s 49ms/step - loss: 1.3613 - accuracy: 0.8754 - val_loss: 1.3864 - val_accuracy: 0.8618
Epoch 18/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2710 - accuracy: 0.8754 - val_loss: 1.3430 - val_accuracy: 0.8618
Epoch 19/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2127 - accuracy: 0.8836 - val_loss: 1.3447 - val_accuracy: 0.8618
Epoch 20/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1846 - accuracy: 0.8770 - val_loss: 1.2411 - val_accuracy: 0.8618
Epoch 21/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1617 - accuracy: 0.8656 - val_loss: 1.2063 - val_accuracy: 0.8618
Epoch 22/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1068 - accuracy: 0.8754 - val_loss: 1.2191 - val_accuracy: 0.8618
Epoch 23/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0880 - accuracy: 0.8770 - val_loss: 1.1560 - val_accuracy: 0.8618
Epoch 24/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0468 - accuracy: 0.8672 - val_loss: 1.0820 - val_accuracy: 0.8618
Epoch 25/100
2/2 [==============================] - 0s 48ms/step - loss: 1.0009 - accuracy: 0.8705 - val_loss: 1.0420 - val_accuracy: 0.8618
Epoch 26/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9567 - accuracy: 0.8738 - val_loss: 1.0175 - val_accuracy: 0.8618
Epoch 27/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9098 - accuracy: 0.8787 - val_loss: 1.0621 - val_accuracy: 0.8618
Epoch 28/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9087 - accuracy: 0.8754 - val_loss: 1.0814 - val_accuracy: 0.8618
Epoch 29/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9144 - accuracy: 0.8754 - val_loss: 0.9701 - val_accuracy: 0.8618
Epoch 30/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8829 - accuracy: 0.8689 - val_loss: 0.9484 - val_accuracy: 0.8618
Epoch 31/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8590 - accuracy: 0.8541 - val_loss: 0.9756 - val_accuracy: 0.8618
Epoch 32/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8255 - accuracy: 0.8689 - val_loss: 0.8827 - val_accuracy: 0.8586
Epoch 33/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8093 - accuracy: 0.8902 - val_loss: 0.8875 - val_accuracy: 0.8618
Epoch 34/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8128 - accuracy: 0.8918 - val_loss: 0.9285 - val_accuracy: 0.8618
Epoch 35/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8163 - accuracy: 0.8689 - val_loss: 0.9239 - val_accuracy: 0.8618
Epoch 36/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7887 - accuracy: 0.8787 - val_loss: 0.9263 - val_accuracy: 0.8618
Epoch 37/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7760 - accuracy: 0.8689 - val_loss: 0.8586 - val_accuracy: 0.8618
Epoch 38/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7405 - accuracy: 0.8607 - val_loss: 0.8082 - val_accuracy: 0.8553
Epoch 39/100
2/2 [==============================] - 0s 48ms/step - loss: 0.7246 - accuracy: 0.8869 - val_loss: 0.8285 - val_accuracy: 0.8618
Epoch 40/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7046 - accuracy: 0.8787 - val_loss: 0.8422 - val_accuracy: 0.8618
Epoch 41/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7002 - accuracy: 0.8672 - val_loss: 0.7457 - val_accuracy: 0.8618
Epoch 42/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6781 - accuracy: 0.8672 - val_loss: 0.7357 - val_accuracy: 0.8618
Epoch 43/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6654 - accuracy: 0.8705 - val_loss: 0.8438 - val_accuracy: 0.8618
Epoch 44/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6744 - accuracy: 0.8656 - val_loss: 0.8278 - val_accuracy: 0.8618
Epoch 45/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6381 - accuracy: 0.8803 - val_loss: 0.7164 - val_accuracy: 0.8618
Epoch 46/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6268 - accuracy: 0.8852 - val_loss: 0.7029 - val_accuracy: 0.8618
Epoch 47/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6202 - accuracy: 0.8787 - val_loss: 0.7506 - val_accuracy: 0.8618
Epoch 48/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6275 - accuracy: 0.8820 - val_loss: 0.7347 - val_accuracy: 0.8618
Epoch 49/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5907 - accuracy: 0.8820 - val_loss: 0.7150 - val_accuracy: 0.8618
Epoch 50/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6065 - accuracy: 0.8705 - val_loss: 0.7718 - val_accuracy: 0.8618
Epoch 51/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6090 - accuracy: 0.8721 - val_loss: 0.7452 - val_accuracy: 0.8618
Epoch 52/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6062 - accuracy: 0.8738 - val_loss: 0.7073 - val_accuracy: 0.8618
Epoch 53/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5951 - accuracy: 0.8902 - val_loss: 0.7337 - val_accuracy: 0.8618
Epoch 54/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6058 - accuracy: 0.8738 - val_loss: 0.7257 - val_accuracy: 0.8618
Epoch 55/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6129 - accuracy: 0.8820 - val_loss: 0.7175 - val_accuracy: 0.8618
Epoch 56/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6195 - accuracy: 0.8721 - val_loss: 0.7488 - val_accuracy: 0.8618
Epoch 57/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6148 - accuracy: 0.8787 - val_loss: 0.6969 - val_accuracy: 0.8618
Epoch 58/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5947 - accuracy: 0.8705 - val_loss: 0.6728 - val_accuracy: 0.8618
Epoch 59/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6034 - accuracy: 0.8689 - val_loss: 0.7308 - val_accuracy: 0.8618
Epoch 60/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6014 - accuracy: 0.8574 - val_loss: 0.6793 - val_accuracy: 0.8618
Epoch 61/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5736 - accuracy: 0.8787 - val_loss: 0.6666 - val_accuracy: 0.8224
Epoch 62/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6409 - accuracy: 0.8393 - val_loss: 0.6578 - val_accuracy: 0.8487
Epoch 63/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5959 - accuracy: 0.8607 - val_loss: 0.7032 - val_accuracy: 0.8618
Epoch 64/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5878 - accuracy: 0.8738 - val_loss: 0.7177 - val_accuracy: 0.8618
Epoch 65/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5874 - accuracy: 0.8721 - val_loss: 0.6580 - val_accuracy: 0.8618
Epoch 66/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5647 - accuracy: 0.8705 - val_loss: 0.6365 - val_accuracy: 0.8388
Epoch 67/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5647 - accuracy: 0.8590 - val_loss: 0.6255 - val_accuracy: 0.8618
Epoch 68/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5745 - accuracy: 0.8525 - val_loss: 0.6426 - val_accuracy: 0.8618
Epoch 69/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5420 - accuracy: 0.8820 - val_loss: 0.6144 - val_accuracy: 0.8618
Epoch 70/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5292 - accuracy: 0.8836 - val_loss: 0.6035 - val_accuracy: 0.8586
Epoch 71/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5353 - accuracy: 0.8820 - val_loss: 0.5986 - val_accuracy: 0.8520
Epoch 72/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5276 - accuracy: 0.8787 - val_loss: 0.5989 - val_accuracy: 0.8553
Epoch 73/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5302 - accuracy: 0.8738 - val_loss: 0.5888 - val_accuracy: 0.8651
Epoch 74/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4998 - accuracy: 0.8803 - val_loss: 0.5968 - val_accuracy: 0.8618
Epoch 75/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5178 - accuracy: 0.8689 - val_loss: 0.6026 - val_accuracy: 0.8586
Epoch 76/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5159 - accuracy: 0.8852 - val_loss: 0.5961 - val_accuracy: 0.8553
Epoch 77/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5091 - accuracy: 0.8754 - val_loss: 0.5907 - val_accuracy: 0.8586
Epoch 78/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4957 - accuracy: 0.8902 - val_loss: 0.5922 - val_accuracy: 0.8553
Epoch 79/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4948 - accuracy: 0.8918 - val_loss: 0.5925 - val_accuracy: 0.8618
Epoch 80/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4952 - accuracy: 0.8951 - val_loss: 0.5896 - val_accuracy: 0.8553
Epoch 81/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5145 - accuracy: 0.8820 - val_loss: 0.5853 - val_accuracy: 0.8553
Epoch 82/100
2/2 [==============================] - 0s 50ms/step - loss: 0.4955 - accuracy: 0.8787 - val_loss: 0.5929 - val_accuracy: 0.8618
Epoch 83/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5078 - accuracy: 0.8787 - val_loss: 0.5977 - val_accuracy: 0.8586
Epoch 84/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4961 - accuracy: 0.8787 - val_loss: 0.5805 - val_accuracy: 0.8586
Epoch 85/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4749 - accuracy: 0.9000 - val_loss: 0.5787 - val_accuracy: 0.8586
Epoch 86/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4990 - accuracy: 0.8754 - val_loss: 0.5844 - val_accuracy: 0.8586
Epoch 87/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5139 - accuracy: 0.8721 - val_loss: 0.5733 - val_accuracy: 0.8651
Epoch 88/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5118 - accuracy: 0.8607 - val_loss: 0.5681 - val_accuracy: 0.8684
Epoch 89/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4838 - accuracy: 0.8803 - val_loss: 0.5777 - val_accuracy: 0.8586
Epoch 90/100
2/2 [==============================] - 0s 49ms/step - loss: 0.4887 - accuracy: 0.8836 - val_loss: 0.5866 - val_accuracy: 0.8651
Epoch 91/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4863 - accuracy: 0.8803 - val_loss: 0.5743 - val_accuracy: 0.8618
Epoch 92/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4909 - accuracy: 0.8689 - val_loss: 0.5722 - val_accuracy: 0.8651
Epoch 93/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4735 - accuracy: 0.8770 - val_loss: 0.5691 - val_accuracy: 0.8651
Epoch 94/100
2/2 [==============================] - 0s 48ms/step - loss: 0.4718 - accuracy: 0.8836 - val_loss: 0.5713 - val_accuracy: 0.8553
Epoch 95/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4915 - accuracy: 0.8803 - val_loss: 0.5709 - val_accuracy: 0.8684
Epoch 96/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4747 - accuracy: 0.8803 - val_loss: 0.5851 - val_accuracy: 0.8421
Epoch 97/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5032 - accuracy: 0.8672 - val_loss: 0.5864 - val_accuracy: 0.8487
Epoch 98/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4933 - accuracy: 0.8689 - val_loss: 0.6048 - val_accuracy: 0.8618
Epoch 99/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5174 - accuracy: 0.8672 - val_loss: 0.5866 - val_accuracy: 0.8553
Epoch 100/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5019 - accuracy: 0.8705 - val_loss: 0.5715 - val_accuracy: 0.8388
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 6
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 3, 'hidden_units': 128, 'learning_rate_decay': 1e-05, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 236ms/step - loss: 2.7391 - accuracy: 0.4269 - val_loss: 2.6780 - val_accuracy: 0.6098
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 2.6642 - accuracy: 0.5993 - val_loss: 2.6122 - val_accuracy: 0.7672
Epoch 3/100
2/2 [==============================] - 0s 31ms/step - loss: 2.5926 - accuracy: 0.7438 - val_loss: 2.5493 - val_accuracy: 0.7967
Epoch 4/100
2/2 [==============================] - 0s 31ms/step - loss: 2.5255 - accuracy: 0.8259 - val_loss: 2.4891 - val_accuracy: 0.8164
Epoch 5/100
2/2 [==============================] - 0s 33ms/step - loss: 2.4667 - accuracy: 0.8555 - val_loss: 2.4315 - val_accuracy: 0.8164
Epoch 6/100
2/2 [==============================] - 0s 32ms/step - loss: 2.4059 - accuracy: 0.8654 - val_loss: 2.3762 - val_accuracy: 0.8164
Epoch 7/100
2/2 [==============================] - 0s 32ms/step - loss: 2.3521 - accuracy: 0.8670 - val_loss: 2.3230 - val_accuracy: 0.8164
Epoch 8/100
2/2 [==============================] - 0s 31ms/step - loss: 2.2959 - accuracy: 0.8670 - val_loss: 2.2720 - val_accuracy: 0.8164
Epoch 9/100
2/2 [==============================] - 0s 31ms/step - loss: 2.2411 - accuracy: 0.8670 - val_loss: 2.2231 - val_accuracy: 0.8164
Epoch 10/100
2/2 [==============================] - 0s 32ms/step - loss: 2.1888 - accuracy: 0.8670 - val_loss: 2.1761 - val_accuracy: 0.8164
Epoch 11/100
2/2 [==============================] - 0s 32ms/step - loss: 2.1439 - accuracy: 0.8670 - val_loss: 2.1308 - val_accuracy: 0.8164
Epoch 12/100
2/2 [==============================] - 0s 32ms/step - loss: 2.0923 - accuracy: 0.8670 - val_loss: 2.0872 - val_accuracy: 0.8164
Epoch 13/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0476 - accuracy: 0.8670 - val_loss: 2.0451 - val_accuracy: 0.8164
Epoch 14/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0001 - accuracy: 0.8670 - val_loss: 2.0042 - val_accuracy: 0.8164
Epoch 15/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9643 - accuracy: 0.8670 - val_loss: 1.9646 - val_accuracy: 0.8164
Epoch 16/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9185 - accuracy: 0.8670 - val_loss: 1.9264 - val_accuracy: 0.8164
Epoch 17/100
2/2 [==============================] - 0s 47ms/step - loss: 1.8795 - accuracy: 0.8670 - val_loss: 1.8894 - val_accuracy: 0.8164
Epoch 18/100
2/2 [==============================] - 0s 47ms/step - loss: 1.8446 - accuracy: 0.8670 - val_loss: 1.8534 - val_accuracy: 0.8164
Epoch 19/100
2/2 [==============================] - 0s 48ms/step - loss: 1.8026 - accuracy: 0.8670 - val_loss: 1.8183 - val_accuracy: 0.8164
Epoch 20/100
2/2 [==============================] - 0s 46ms/step - loss: 1.7658 - accuracy: 0.8670 - val_loss: 1.7838 - val_accuracy: 0.8164
Epoch 21/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7296 - accuracy: 0.8670 - val_loss: 1.7500 - val_accuracy: 0.8164
Epoch 22/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6932 - accuracy: 0.8670 - val_loss: 1.7173 - val_accuracy: 0.8164
Epoch 23/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6633 - accuracy: 0.8670 - val_loss: 1.6853 - val_accuracy: 0.8164
Epoch 24/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6330 - accuracy: 0.8670 - val_loss: 1.6543 - val_accuracy: 0.8164
Epoch 25/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5936 - accuracy: 0.8670 - val_loss: 1.6238 - val_accuracy: 0.8164
Epoch 26/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5680 - accuracy: 0.8670 - val_loss: 1.5939 - val_accuracy: 0.8164
Epoch 27/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5347 - accuracy: 0.8670 - val_loss: 1.5644 - val_accuracy: 0.8164
Epoch 28/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5073 - accuracy: 0.8670 - val_loss: 1.5356 - val_accuracy: 0.8164
Epoch 29/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4735 - accuracy: 0.8670 - val_loss: 1.5075 - val_accuracy: 0.8164
Epoch 30/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4470 - accuracy: 0.8670 - val_loss: 1.4799 - val_accuracy: 0.8164
Epoch 31/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4247 - accuracy: 0.8670 - val_loss: 1.4529 - val_accuracy: 0.8164
Epoch 32/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3891 - accuracy: 0.8670 - val_loss: 1.4262 - val_accuracy: 0.8164
Epoch 33/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3643 - accuracy: 0.8670 - val_loss: 1.3998 - val_accuracy: 0.8164
Epoch 34/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3412 - accuracy: 0.8670 - val_loss: 1.3739 - val_accuracy: 0.8164
Epoch 35/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3170 - accuracy: 0.8670 - val_loss: 1.3484 - val_accuracy: 0.8164
Epoch 36/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2896 - accuracy: 0.8670 - val_loss: 1.3233 - val_accuracy: 0.8164
Epoch 37/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2615 - accuracy: 0.8670 - val_loss: 1.2989 - val_accuracy: 0.8164
Epoch 38/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2347 - accuracy: 0.8670 - val_loss: 1.2751 - val_accuracy: 0.8164
Epoch 39/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2070 - accuracy: 0.8670 - val_loss: 1.2518 - val_accuracy: 0.8164
Epoch 40/100
2/2 [==============================] - 0s 52ms/step - loss: 1.1896 - accuracy: 0.8670 - val_loss: 1.2287 - val_accuracy: 0.8164
Epoch 41/100
2/2 [==============================] - 0s 45ms/step - loss: 1.1696 - accuracy: 0.8670 - val_loss: 1.2059 - val_accuracy: 0.8164
Epoch 42/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1411 - accuracy: 0.8670 - val_loss: 1.1835 - val_accuracy: 0.8164
Epoch 43/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1234 - accuracy: 0.8670 - val_loss: 1.1615 - val_accuracy: 0.8164
Epoch 44/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1010 - accuracy: 0.8670 - val_loss: 1.1398 - val_accuracy: 0.8164
Epoch 45/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0746 - accuracy: 0.8670 - val_loss: 1.1183 - val_accuracy: 0.8164
Epoch 46/100
2/2 [==============================] - 0s 33ms/step - loss: 1.0559 - accuracy: 0.8670 - val_loss: 1.0970 - val_accuracy: 0.8164
Epoch 47/100
2/2 [==============================] - 0s 33ms/step - loss: 1.0351 - accuracy: 0.8670 - val_loss: 1.0761 - val_accuracy: 0.8164
Epoch 48/100
2/2 [==============================] - 0s 35ms/step - loss: 1.0132 - accuracy: 0.8670 - val_loss: 1.0557 - val_accuracy: 0.8164
Epoch 49/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9969 - accuracy: 0.8670 - val_loss: 1.0359 - val_accuracy: 0.8164
Epoch 50/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9764 - accuracy: 0.8670 - val_loss: 1.0166 - val_accuracy: 0.8164
Epoch 51/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9555 - accuracy: 0.8670 - val_loss: 0.9975 - val_accuracy: 0.8164
Epoch 52/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9354 - accuracy: 0.8670 - val_loss: 0.9787 - val_accuracy: 0.8164
Epoch 53/100
2/2 [==============================] - 0s 33ms/step - loss: 0.9158 - accuracy: 0.8670 - val_loss: 0.9606 - val_accuracy: 0.8164
Epoch 54/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8967 - accuracy: 0.8670 - val_loss: 0.9432 - val_accuracy: 0.8164
Epoch 55/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8782 - accuracy: 0.8670 - val_loss: 0.9263 - val_accuracy: 0.8164
Epoch 56/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8621 - accuracy: 0.8670 - val_loss: 0.9097 - val_accuracy: 0.8164
Epoch 57/100
2/2 [==============================] - 0s 46ms/step - loss: 0.8470 - accuracy: 0.8670 - val_loss: 0.8935 - val_accuracy: 0.8164
Epoch 58/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8249 - accuracy: 0.8670 - val_loss: 0.8775 - val_accuracy: 0.8164
Epoch 59/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8117 - accuracy: 0.8670 - val_loss: 0.8617 - val_accuracy: 0.8164
Epoch 60/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7982 - accuracy: 0.8670 - val_loss: 0.8463 - val_accuracy: 0.8164
Epoch 61/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7772 - accuracy: 0.8670 - val_loss: 0.8311 - val_accuracy: 0.8164
Epoch 62/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7634 - accuracy: 0.8670 - val_loss: 0.8162 - val_accuracy: 0.8164
Epoch 63/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7436 - accuracy: 0.8670 - val_loss: 0.8018 - val_accuracy: 0.8164
Epoch 64/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7329 - accuracy: 0.8670 - val_loss: 0.7879 - val_accuracy: 0.8164
Epoch 65/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7186 - accuracy: 0.8670 - val_loss: 0.7743 - val_accuracy: 0.8164
Epoch 66/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7071 - accuracy: 0.8670 - val_loss: 0.7612 - val_accuracy: 0.8164
Epoch 67/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6882 - accuracy: 0.8670 - val_loss: 0.7485 - val_accuracy: 0.8164
Epoch 68/100
2/2 [==============================] - 0s 43ms/step - loss: 0.6800 - accuracy: 0.8670 - val_loss: 0.7361 - val_accuracy: 0.8164
Epoch 69/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6650 - accuracy: 0.8670 - val_loss: 0.7239 - val_accuracy: 0.8164
Epoch 70/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6544 - accuracy: 0.8670 - val_loss: 0.7121 - val_accuracy: 0.8164
Epoch 71/100
2/2 [==============================] - 0s 42ms/step - loss: 0.6418 - accuracy: 0.8670 - val_loss: 0.7005 - val_accuracy: 0.8164
Epoch 72/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6292 - accuracy: 0.8670 - val_loss: 0.6891 - val_accuracy: 0.8164
Epoch 73/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6185 - accuracy: 0.8670 - val_loss: 0.6783 - val_accuracy: 0.8164
Epoch 74/100
2/2 [==============================] - 0s 87ms/step - loss: 0.6061 - accuracy: 0.8670 - val_loss: 0.6681 - val_accuracy: 0.8164
Epoch 75/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5981 - accuracy: 0.8670 - val_loss: 0.6583 - val_accuracy: 0.8164
Epoch 76/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5828 - accuracy: 0.8670 - val_loss: 0.6489 - val_accuracy: 0.8164
Epoch 77/100
2/2 [==============================] - 0s 28ms/step - loss: 0.5772 - accuracy: 0.8670 - val_loss: 0.6399 - val_accuracy: 0.8164
Epoch 78/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5658 - accuracy: 0.8670 - val_loss: 0.6310 - val_accuracy: 0.8164
Epoch 79/100
2/2 [==============================] - 0s 55ms/step - loss: 0.5527 - accuracy: 0.8670 - val_loss: 0.6225 - val_accuracy: 0.8164
Epoch 80/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5498 - accuracy: 0.8670 - val_loss: 0.6140 - val_accuracy: 0.8164
Epoch 81/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5374 - accuracy: 0.8670 - val_loss: 0.6056 - val_accuracy: 0.8164
Epoch 82/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5274 - accuracy: 0.8670 - val_loss: 0.5975 - val_accuracy: 0.8164
Epoch 83/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5226 - accuracy: 0.8670 - val_loss: 0.5900 - val_accuracy: 0.8164
Epoch 84/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5136 - accuracy: 0.8670 - val_loss: 0.5825 - val_accuracy: 0.8164
Epoch 85/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5068 - accuracy: 0.8670 - val_loss: 0.5754 - val_accuracy: 0.8164
Epoch 86/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4997 - accuracy: 0.8670 - val_loss: 0.5684 - val_accuracy: 0.8164
Epoch 87/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4894 - accuracy: 0.8670 - val_loss: 0.5620 - val_accuracy: 0.8164
Epoch 88/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4865 - accuracy: 0.8670 - val_loss: 0.5558 - val_accuracy: 0.8164
Epoch 89/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4810 - accuracy: 0.8670 - val_loss: 0.5497 - val_accuracy: 0.8164
Epoch 90/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4748 - accuracy: 0.8670 - val_loss: 0.5436 - val_accuracy: 0.8164
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4664 - accuracy: 0.8670 - val_loss: 0.5377 - val_accuracy: 0.8164
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4624 - accuracy: 0.8670 - val_loss: 0.5322 - val_accuracy: 0.8164
Epoch 93/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4614 - accuracy: 0.8670 - val_loss: 0.5269 - val_accuracy: 0.8164
Epoch 94/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4519 - accuracy: 0.8670 - val_loss: 0.5215 - val_accuracy: 0.8164
Epoch 95/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4471 - accuracy: 0.8670 - val_loss: 0.5166 - val_accuracy: 0.8164
Epoch 96/100
2/2 [==============================] - 0s 46ms/step - loss: 0.4430 - accuracy: 0.8670 - val_loss: 0.5120 - val_accuracy: 0.8164
Epoch 97/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4399 - accuracy: 0.8670 - val_loss: 0.5079 - val_accuracy: 0.8164
Epoch 98/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4376 - accuracy: 0.8670 - val_loss: 0.5041 - val_accuracy: 0.8164
Epoch 99/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4344 - accuracy: 0.8670 - val_loss: 0.5006 - val_accuracy: 0.8164
Epoch 100/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4325 - accuracy: 0.8670 - val_loss: 0.4976 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 3, 'hidden_units': 128, 'learning_rate_decay': 1e-05, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 220ms/step - loss: 2.6577 - accuracy: 0.6486 - val_loss: 2.5803 - val_accuracy: 0.8656
Epoch 2/100
2/2 [==============================] - 0s 47ms/step - loss: 2.5858 - accuracy: 0.7619 - val_loss: 2.5140 - val_accuracy: 0.8721
Epoch 3/100
2/2 [==============================] - 0s 47ms/step - loss: 2.5218 - accuracy: 0.8112 - val_loss: 2.4502 - val_accuracy: 0.8721
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 2.4603 - accuracy: 0.8309 - val_loss: 2.3892 - val_accuracy: 0.8721
Epoch 5/100
2/2 [==============================] - 0s 47ms/step - loss: 2.4007 - accuracy: 0.8374 - val_loss: 2.3307 - val_accuracy: 0.8721
Epoch 6/100
2/2 [==============================] - 0s 47ms/step - loss: 2.3434 - accuracy: 0.8391 - val_loss: 2.2747 - val_accuracy: 0.8721
Epoch 7/100
2/2 [==============================] - 0s 32ms/step - loss: 2.2888 - accuracy: 0.8391 - val_loss: 2.2211 - val_accuracy: 0.8721
Epoch 8/100
2/2 [==============================] - 0s 31ms/step - loss: 2.2315 - accuracy: 0.8391 - val_loss: 2.1696 - val_accuracy: 0.8721
Epoch 9/100
2/2 [==============================] - 0s 31ms/step - loss: 2.1907 - accuracy: 0.8391 - val_loss: 2.1198 - val_accuracy: 0.8721
Epoch 10/100
2/2 [==============================] - 0s 32ms/step - loss: 2.1396 - accuracy: 0.8391 - val_loss: 2.0717 - val_accuracy: 0.8721
Epoch 11/100
2/2 [==============================] - 0s 32ms/step - loss: 2.0906 - accuracy: 0.8391 - val_loss: 2.0251 - val_accuracy: 0.8721
Epoch 12/100
2/2 [==============================] - 0s 31ms/step - loss: 2.0477 - accuracy: 0.8391 - val_loss: 1.9802 - val_accuracy: 0.8721
Epoch 13/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0027 - accuracy: 0.8391 - val_loss: 1.9367 - val_accuracy: 0.8721
Epoch 14/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9636 - accuracy: 0.8391 - val_loss: 1.8946 - val_accuracy: 0.8721
Epoch 15/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9221 - accuracy: 0.8391 - val_loss: 1.8536 - val_accuracy: 0.8721
Epoch 16/100
2/2 [==============================] - 0s 48ms/step - loss: 1.8839 - accuracy: 0.8391 - val_loss: 1.8139 - val_accuracy: 0.8721
Epoch 17/100
2/2 [==============================] - 0s 47ms/step - loss: 1.8436 - accuracy: 0.8391 - val_loss: 1.7754 - val_accuracy: 0.8721
Epoch 18/100
2/2 [==============================] - 0s 31ms/step - loss: 1.8088 - accuracy: 0.8391 - val_loss: 1.7381 - val_accuracy: 0.8721
Epoch 19/100
2/2 [==============================] - 0s 31ms/step - loss: 1.7640 - accuracy: 0.8391 - val_loss: 1.7016 - val_accuracy: 0.8721
Epoch 20/100
2/2 [==============================] - 0s 32ms/step - loss: 1.7335 - accuracy: 0.8391 - val_loss: 1.6661 - val_accuracy: 0.8721
Epoch 21/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6964 - accuracy: 0.8391 - val_loss: 1.6316 - val_accuracy: 0.8721
Epoch 22/100
2/2 [==============================] - 0s 32ms/step - loss: 1.6617 - accuracy: 0.8391 - val_loss: 1.5982 - val_accuracy: 0.8721
Epoch 23/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6381 - accuracy: 0.8391 - val_loss: 1.5658 - val_accuracy: 0.8721
Epoch 24/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5999 - accuracy: 0.8391 - val_loss: 1.5345 - val_accuracy: 0.8721
Epoch 25/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5673 - accuracy: 0.8391 - val_loss: 1.5040 - val_accuracy: 0.8721
Epoch 26/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5385 - accuracy: 0.8391 - val_loss: 1.4741 - val_accuracy: 0.8721
Epoch 27/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5088 - accuracy: 0.8391 - val_loss: 1.4446 - val_accuracy: 0.8721
Epoch 28/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4809 - accuracy: 0.8391 - val_loss: 1.4159 - val_accuracy: 0.8721
Epoch 29/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4542 - accuracy: 0.8391 - val_loss: 1.3879 - val_accuracy: 0.8721
Epoch 30/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4228 - accuracy: 0.8391 - val_loss: 1.3607 - val_accuracy: 0.8721
Epoch 31/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4013 - accuracy: 0.8391 - val_loss: 1.3341 - val_accuracy: 0.8721
Epoch 32/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3768 - accuracy: 0.8391 - val_loss: 1.3079 - val_accuracy: 0.8721
Epoch 33/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3468 - accuracy: 0.8391 - val_loss: 1.2821 - val_accuracy: 0.8721
Epoch 34/100
2/2 [==============================] - 0s 31ms/step - loss: 1.3188 - accuracy: 0.8391 - val_loss: 1.2567 - val_accuracy: 0.8721
Epoch 35/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2989 - accuracy: 0.8391 - val_loss: 1.2316 - val_accuracy: 0.8721
Epoch 36/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2741 - accuracy: 0.8391 - val_loss: 1.2070 - val_accuracy: 0.8721
Epoch 37/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2467 - accuracy: 0.8391 - val_loss: 1.1826 - val_accuracy: 0.8721
Epoch 38/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2321 - accuracy: 0.8391 - val_loss: 1.1587 - val_accuracy: 0.8721
Epoch 39/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2040 - accuracy: 0.8391 - val_loss: 1.1350 - val_accuracy: 0.8721
Epoch 40/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1761 - accuracy: 0.8391 - val_loss: 1.1117 - val_accuracy: 0.8721
Epoch 41/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1520 - accuracy: 0.8391 - val_loss: 1.0888 - val_accuracy: 0.8721
Epoch 42/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1336 - accuracy: 0.8391 - val_loss: 1.0663 - val_accuracy: 0.8721
Epoch 43/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1182 - accuracy: 0.8391 - val_loss: 1.0441 - val_accuracy: 0.8721
Epoch 44/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0907 - accuracy: 0.8391 - val_loss: 1.0226 - val_accuracy: 0.8721
Epoch 45/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0666 - accuracy: 0.8391 - val_loss: 1.0016 - val_accuracy: 0.8721
Epoch 46/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0491 - accuracy: 0.8391 - val_loss: 0.9810 - val_accuracy: 0.8721
Epoch 47/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0303 - accuracy: 0.8391 - val_loss: 0.9609 - val_accuracy: 0.8721
Epoch 48/100
2/2 [==============================] - 0s 31ms/step - loss: 1.0087 - accuracy: 0.8391 - val_loss: 0.9411 - val_accuracy: 0.8721
Epoch 49/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9913 - accuracy: 0.8391 - val_loss: 0.9218 - val_accuracy: 0.8721
Epoch 50/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9758 - accuracy: 0.8391 - val_loss: 0.9027 - val_accuracy: 0.8721
Epoch 51/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9524 - accuracy: 0.8391 - val_loss: 0.8839 - val_accuracy: 0.8721
Epoch 52/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9335 - accuracy: 0.8391 - val_loss: 0.8651 - val_accuracy: 0.8721
Epoch 53/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9198 - accuracy: 0.8391 - val_loss: 0.8465 - val_accuracy: 0.8721
Epoch 54/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8944 - accuracy: 0.8391 - val_loss: 0.8284 - val_accuracy: 0.8721
Epoch 55/100
2/2 [==============================] - 0s 61ms/step - loss: 0.8806 - accuracy: 0.8391 - val_loss: 0.8108 - val_accuracy: 0.8721
Epoch 56/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8644 - accuracy: 0.8391 - val_loss: 0.7938 - val_accuracy: 0.8721
Epoch 57/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8446 - accuracy: 0.8391 - val_loss: 0.7774 - val_accuracy: 0.8721
Epoch 58/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8334 - accuracy: 0.8391 - val_loss: 0.7613 - val_accuracy: 0.8721
Epoch 59/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8185 - accuracy: 0.8391 - val_loss: 0.7456 - val_accuracy: 0.8721
Epoch 60/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8031 - accuracy: 0.8391 - val_loss: 0.7301 - val_accuracy: 0.8721
Epoch 61/100
2/2 [==============================] - 0s 53ms/step - loss: 0.7865 - accuracy: 0.8391 - val_loss: 0.7147 - val_accuracy: 0.8721
Epoch 62/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7725 - accuracy: 0.8391 - val_loss: 0.6996 - val_accuracy: 0.8721
Epoch 63/100
2/2 [==============================] - 0s 44ms/step - loss: 0.7571 - accuracy: 0.8391 - val_loss: 0.6848 - val_accuracy: 0.8721
Epoch 64/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7398 - accuracy: 0.8391 - val_loss: 0.6704 - val_accuracy: 0.8721
Epoch 65/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7313 - accuracy: 0.8391 - val_loss: 0.6565 - val_accuracy: 0.8721
Epoch 66/100
2/2 [==============================] - 0s 48ms/step - loss: 0.7198 - accuracy: 0.8391 - val_loss: 0.6431 - val_accuracy: 0.8721
Epoch 67/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7108 - accuracy: 0.8391 - val_loss: 0.6302 - val_accuracy: 0.8721
Epoch 68/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6915 - accuracy: 0.8391 - val_loss: 0.6175 - val_accuracy: 0.8721
Epoch 69/100
2/2 [==============================] - 0s 29ms/step - loss: 0.6829 - accuracy: 0.8391 - val_loss: 0.6055 - val_accuracy: 0.8721
Epoch 70/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6707 - accuracy: 0.8391 - val_loss: 0.5940 - val_accuracy: 0.8721
Epoch 71/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6572 - accuracy: 0.8391 - val_loss: 0.5825 - val_accuracy: 0.8721
Epoch 72/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6516 - accuracy: 0.8391 - val_loss: 0.5714 - val_accuracy: 0.8721
Epoch 73/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6325 - accuracy: 0.8391 - val_loss: 0.5605 - val_accuracy: 0.8721
Epoch 74/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6267 - accuracy: 0.8391 - val_loss: 0.5502 - val_accuracy: 0.8721
Epoch 75/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6122 - accuracy: 0.8391 - val_loss: 0.5400 - val_accuracy: 0.8721
Epoch 76/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6077 - accuracy: 0.8391 - val_loss: 0.5301 - val_accuracy: 0.8721
Epoch 77/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5990 - accuracy: 0.8391 - val_loss: 0.5206 - val_accuracy: 0.8721
Epoch 78/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5920 - accuracy: 0.8391 - val_loss: 0.5116 - val_accuracy: 0.8721
Epoch 79/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5812 - accuracy: 0.8391 - val_loss: 0.5030 - val_accuracy: 0.8721
Epoch 80/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5733 - accuracy: 0.8391 - val_loss: 0.4946 - val_accuracy: 0.8721
Epoch 81/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5632 - accuracy: 0.8391 - val_loss: 0.4866 - val_accuracy: 0.8721
Epoch 82/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5588 - accuracy: 0.8391 - val_loss: 0.4791 - val_accuracy: 0.8721
Epoch 83/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5463 - accuracy: 0.8391 - val_loss: 0.4716 - val_accuracy: 0.8721
Epoch 84/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5417 - accuracy: 0.8391 - val_loss: 0.4643 - val_accuracy: 0.8721
Epoch 85/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5376 - accuracy: 0.8391 - val_loss: 0.4573 - val_accuracy: 0.8721
Epoch 86/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5317 - accuracy: 0.8391 - val_loss: 0.4508 - val_accuracy: 0.8721
Epoch 87/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5249 - accuracy: 0.8391 - val_loss: 0.4448 - val_accuracy: 0.8721
Epoch 88/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5151 - accuracy: 0.8391 - val_loss: 0.4390 - val_accuracy: 0.8721
Epoch 89/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5119 - accuracy: 0.8391 - val_loss: 0.4335 - val_accuracy: 0.8721
Epoch 90/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5112 - accuracy: 0.8391 - val_loss: 0.4280 - val_accuracy: 0.8721
Epoch 91/100
2/2 [==============================] - 0s 27ms/step - loss: 0.5015 - accuracy: 0.8391 - val_loss: 0.4230 - val_accuracy: 0.8721
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4982 - accuracy: 0.8391 - val_loss: 0.4180 - val_accuracy: 0.8721
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4936 - accuracy: 0.8391 - val_loss: 0.4134 - val_accuracy: 0.8721
Epoch 94/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4848 - accuracy: 0.8391 - val_loss: 0.4091 - val_accuracy: 0.8721
Epoch 95/100
2/2 [==============================] - 0s 44ms/step - loss: 0.4821 - accuracy: 0.8391 - val_loss: 0.4053 - val_accuracy: 0.8721
Epoch 96/100
2/2 [==============================] - 0s 54ms/step - loss: 0.4787 - accuracy: 0.8391 - val_loss: 0.4018 - val_accuracy: 0.8721
Epoch 97/100
2/2 [==============================] - 0s 48ms/step - loss: 0.4757 - accuracy: 0.8391 - val_loss: 0.3989 - val_accuracy: 0.8721
Epoch 98/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4732 - accuracy: 0.8374 - val_loss: 0.3963 - val_accuracy: 0.8721
Epoch 99/100
2/2 [==============================] - 0s 64ms/step - loss: 0.4700 - accuracy: 0.8391 - val_loss: 0.3938 - val_accuracy: 0.8721
Epoch 100/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4698 - accuracy: 0.8391 - val_loss: 0.3913 - val_accuracy: 0.8721
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 3, 'hidden_units': 128, 'learning_rate_decay': 1e-05, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': 0.95, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': False, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 233ms/step - loss: 2.7298 - accuracy: 0.3852 - val_loss: 2.6548 - val_accuracy: 0.6579
Epoch 2/100
2/2 [==============================] - 0s 31ms/step - loss: 2.6637 - accuracy: 0.5344 - val_loss: 2.5836 - val_accuracy: 0.8289
Epoch 3/100
2/2 [==============================] - 0s 31ms/step - loss: 2.5888 - accuracy: 0.7049 - val_loss: 2.5154 - val_accuracy: 0.8553
Epoch 4/100
2/2 [==============================] - 0s 47ms/step - loss: 2.5334 - accuracy: 0.7525 - val_loss: 2.4500 - val_accuracy: 0.8553
Epoch 5/100
2/2 [==============================] - 0s 47ms/step - loss: 2.4587 - accuracy: 0.8197 - val_loss: 2.3872 - val_accuracy: 0.8586
Epoch 6/100
2/2 [==============================] - 0s 32ms/step - loss: 2.4014 - accuracy: 0.8344 - val_loss: 2.3274 - val_accuracy: 0.8618
Epoch 7/100
2/2 [==============================] - 0s 32ms/step - loss: 2.3445 - accuracy: 0.8393 - val_loss: 2.2704 - val_accuracy: 0.8618
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 2.2825 - accuracy: 0.8393 - val_loss: 2.2160 - val_accuracy: 0.8618
Epoch 9/100
2/2 [==============================] - 0s 48ms/step - loss: 2.2328 - accuracy: 0.8426 - val_loss: 2.1638 - val_accuracy: 0.8618
Epoch 10/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1771 - accuracy: 0.8443 - val_loss: 2.1134 - val_accuracy: 0.8618
Epoch 11/100
2/2 [==============================] - 0s 31ms/step - loss: 2.1249 - accuracy: 0.8443 - val_loss: 2.0648 - val_accuracy: 0.8618
Epoch 12/100
2/2 [==============================] - 0s 31ms/step - loss: 2.0807 - accuracy: 0.8443 - val_loss: 2.0182 - val_accuracy: 0.8618
Epoch 13/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0357 - accuracy: 0.8443 - val_loss: 1.9736 - val_accuracy: 0.8618
Epoch 14/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9852 - accuracy: 0.8443 - val_loss: 1.9307 - val_accuracy: 0.8618
Epoch 15/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9449 - accuracy: 0.8443 - val_loss: 1.8894 - val_accuracy: 0.8618
Epoch 16/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9023 - accuracy: 0.8443 - val_loss: 1.8498 - val_accuracy: 0.8618
Epoch 17/100
2/2 [==============================] - 0s 47ms/step - loss: 1.8671 - accuracy: 0.8443 - val_loss: 1.8117 - val_accuracy: 0.8618
Epoch 18/100
2/2 [==============================] - 0s 47ms/step - loss: 1.8254 - accuracy: 0.8443 - val_loss: 1.7750 - val_accuracy: 0.8618
Epoch 19/100
2/2 [==============================] - 0s 53ms/step - loss: 1.7916 - accuracy: 0.8443 - val_loss: 1.7395 - val_accuracy: 0.8618
Epoch 20/100
2/2 [==============================] - 0s 47ms/step - loss: 1.7618 - accuracy: 0.8443 - val_loss: 1.7052 - val_accuracy: 0.8618
Epoch 21/100
2/2 [==============================] - 0s 48ms/step - loss: 1.7201 - accuracy: 0.8443 - val_loss: 1.6721 - val_accuracy: 0.8618
Epoch 22/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6889 - accuracy: 0.8443 - val_loss: 1.6400 - val_accuracy: 0.8618
Epoch 23/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6513 - accuracy: 0.8443 - val_loss: 1.6089 - val_accuracy: 0.8618
Epoch 24/100
2/2 [==============================] - 0s 31ms/step - loss: 1.6239 - accuracy: 0.8443 - val_loss: 1.5785 - val_accuracy: 0.8618
Epoch 25/100
2/2 [==============================] - 0s 31ms/step - loss: 1.5909 - accuracy: 0.8443 - val_loss: 1.5488 - val_accuracy: 0.8618
Epoch 26/100
2/2 [==============================] - 0s 47ms/step - loss: 1.5593 - accuracy: 0.8443 - val_loss: 1.5197 - val_accuracy: 0.8618
Epoch 27/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5336 - accuracy: 0.8443 - val_loss: 1.4910 - val_accuracy: 0.8618
Epoch 28/100
2/2 [==============================] - 0s 32ms/step - loss: 1.5050 - accuracy: 0.8443 - val_loss: 1.4631 - val_accuracy: 0.8618
Epoch 29/100
2/2 [==============================] - 0s 48ms/step - loss: 1.4719 - accuracy: 0.8443 - val_loss: 1.4361 - val_accuracy: 0.8618
Epoch 30/100
2/2 [==============================] - 0s 31ms/step - loss: 1.4474 - accuracy: 0.8443 - val_loss: 1.4097 - val_accuracy: 0.8618
Epoch 31/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4206 - accuracy: 0.8443 - val_loss: 1.3839 - val_accuracy: 0.8618
Epoch 32/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3959 - accuracy: 0.8443 - val_loss: 1.3587 - val_accuracy: 0.8618
Epoch 33/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3642 - accuracy: 0.8443 - val_loss: 1.3340 - val_accuracy: 0.8618
Epoch 34/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3410 - accuracy: 0.8443 - val_loss: 1.3095 - val_accuracy: 0.8618
Epoch 35/100
2/2 [==============================] - 0s 47ms/step - loss: 1.3155 - accuracy: 0.8443 - val_loss: 1.2856 - val_accuracy: 0.8618
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 1.2898 - accuracy: 0.8443 - val_loss: 1.2623 - val_accuracy: 0.8618
Epoch 37/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2628 - accuracy: 0.8443 - val_loss: 1.2394 - val_accuracy: 0.8618
Epoch 38/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2435 - accuracy: 0.8443 - val_loss: 1.2169 - val_accuracy: 0.8618
Epoch 39/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2215 - accuracy: 0.8443 - val_loss: 1.1948 - val_accuracy: 0.8618
Epoch 40/100
2/2 [==============================] - 0s 32ms/step - loss: 1.1962 - accuracy: 0.8443 - val_loss: 1.1732 - val_accuracy: 0.8618
Epoch 41/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1678 - accuracy: 0.8443 - val_loss: 1.1521 - val_accuracy: 0.8618
Epoch 42/100
2/2 [==============================] - 0s 32ms/step - loss: 1.1568 - accuracy: 0.8443 - val_loss: 1.1313 - val_accuracy: 0.8618
Epoch 43/100
2/2 [==============================] - 0s 31ms/step - loss: 1.1330 - accuracy: 0.8443 - val_loss: 1.1107 - val_accuracy: 0.8618
Epoch 44/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1065 - accuracy: 0.8443 - val_loss: 1.0906 - val_accuracy: 0.8618
Epoch 45/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0852 - accuracy: 0.8443 - val_loss: 1.0712 - val_accuracy: 0.8618
Epoch 46/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0625 - accuracy: 0.8443 - val_loss: 1.0520 - val_accuracy: 0.8618
Epoch 47/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0440 - accuracy: 0.8443 - val_loss: 1.0330 - val_accuracy: 0.8618
Epoch 48/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0250 - accuracy: 0.8443 - val_loss: 1.0142 - val_accuracy: 0.8618
Epoch 49/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0039 - accuracy: 0.8443 - val_loss: 0.9957 - val_accuracy: 0.8618
Epoch 50/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9874 - accuracy: 0.8443 - val_loss: 0.9775 - val_accuracy: 0.8618
Epoch 51/100
2/2 [==============================] - 0s 46ms/step - loss: 0.9677 - accuracy: 0.8443 - val_loss: 0.9597 - val_accuracy: 0.8618
Epoch 52/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9514 - accuracy: 0.8443 - val_loss: 0.9423 - val_accuracy: 0.8618
Epoch 53/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9294 - accuracy: 0.8443 - val_loss: 0.9250 - val_accuracy: 0.8618
Epoch 54/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9169 - accuracy: 0.8443 - val_loss: 0.9082 - val_accuracy: 0.8618
Epoch 55/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8921 - accuracy: 0.8426 - val_loss: 0.8918 - val_accuracy: 0.8618
Epoch 56/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8765 - accuracy: 0.8443 - val_loss: 0.8759 - val_accuracy: 0.8618
Epoch 57/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8621 - accuracy: 0.8443 - val_loss: 0.8600 - val_accuracy: 0.8618
Epoch 58/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8487 - accuracy: 0.8443 - val_loss: 0.8442 - val_accuracy: 0.8618
Epoch 59/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8271 - accuracy: 0.8443 - val_loss: 0.8286 - val_accuracy: 0.8618
Epoch 60/100
2/2 [==============================] - 0s 47ms/step - loss: 0.8095 - accuracy: 0.8443 - val_loss: 0.8134 - val_accuracy: 0.8618
Epoch 61/100
2/2 [==============================] - 0s 46ms/step - loss: 0.7958 - accuracy: 0.8443 - val_loss: 0.7987 - val_accuracy: 0.8618
Epoch 62/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7834 - accuracy: 0.8443 - val_loss: 0.7842 - val_accuracy: 0.8618
Epoch 63/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7681 - accuracy: 0.8443 - val_loss: 0.7700 - val_accuracy: 0.8618
Epoch 64/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7519 - accuracy: 0.8443 - val_loss: 0.7562 - val_accuracy: 0.8618
Epoch 65/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7376 - accuracy: 0.8443 - val_loss: 0.7427 - val_accuracy: 0.8618
Epoch 66/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7183 - accuracy: 0.8443 - val_loss: 0.7297 - val_accuracy: 0.8618
Epoch 67/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7122 - accuracy: 0.8443 - val_loss: 0.7174 - val_accuracy: 0.8618
Epoch 68/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6990 - accuracy: 0.8443 - val_loss: 0.7052 - val_accuracy: 0.8618
Epoch 69/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6815 - accuracy: 0.8443 - val_loss: 0.6933 - val_accuracy: 0.8618
Epoch 70/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6729 - accuracy: 0.8443 - val_loss: 0.6818 - val_accuracy: 0.8618
Epoch 71/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6584 - accuracy: 0.8443 - val_loss: 0.6708 - val_accuracy: 0.8618
Epoch 72/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6527 - accuracy: 0.8443 - val_loss: 0.6602 - val_accuracy: 0.8618
Epoch 73/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6361 - accuracy: 0.8443 - val_loss: 0.6497 - val_accuracy: 0.8618
Epoch 74/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6261 - accuracy: 0.8443 - val_loss: 0.6394 - val_accuracy: 0.8618
Epoch 75/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6120 - accuracy: 0.8443 - val_loss: 0.6295 - val_accuracy: 0.8618
Epoch 76/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6074 - accuracy: 0.8443 - val_loss: 0.6200 - val_accuracy: 0.8618
Epoch 77/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5934 - accuracy: 0.8443 - val_loss: 0.6105 - val_accuracy: 0.8618
Epoch 78/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5850 - accuracy: 0.8443 - val_loss: 0.6012 - val_accuracy: 0.8618
Epoch 79/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5784 - accuracy: 0.8443 - val_loss: 0.5923 - val_accuracy: 0.8618
Epoch 80/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5673 - accuracy: 0.8443 - val_loss: 0.5836 - val_accuracy: 0.8618
Epoch 81/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5575 - accuracy: 0.8443 - val_loss: 0.5753 - val_accuracy: 0.8618
Epoch 82/100
2/2 [==============================] - 0s 45ms/step - loss: 0.5475 - accuracy: 0.8443 - val_loss: 0.5672 - val_accuracy: 0.8618
Epoch 83/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5412 - accuracy: 0.8459 - val_loss: 0.5597 - val_accuracy: 0.8618
Epoch 84/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5354 - accuracy: 0.8443 - val_loss: 0.5527 - val_accuracy: 0.8618
Epoch 85/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5237 - accuracy: 0.8443 - val_loss: 0.5459 - val_accuracy: 0.8618
Epoch 86/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5206 - accuracy: 0.8426 - val_loss: 0.5394 - val_accuracy: 0.8618
Epoch 87/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5083 - accuracy: 0.8426 - val_loss: 0.5333 - val_accuracy: 0.8618
Epoch 88/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5010 - accuracy: 0.8459 - val_loss: 0.5274 - val_accuracy: 0.8618
Epoch 89/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4886 - accuracy: 0.8475 - val_loss: 0.5216 - val_accuracy: 0.8618
Epoch 90/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4905 - accuracy: 0.8443 - val_loss: 0.5159 - val_accuracy: 0.8618
Epoch 91/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4830 - accuracy: 0.8443 - val_loss: 0.5103 - val_accuracy: 0.8618
Epoch 92/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4766 - accuracy: 0.8443 - val_loss: 0.5048 - val_accuracy: 0.8618
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4710 - accuracy: 0.8443 - val_loss: 0.4997 - val_accuracy: 0.8618
Epoch 94/100
2/2 [==============================] - 0s 47ms/step - loss: 0.4661 - accuracy: 0.8459 - val_loss: 0.4950 - val_accuracy: 0.8618
Epoch 95/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4621 - accuracy: 0.8475 - val_loss: 0.4905 - val_accuracy: 0.8618
Epoch 96/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4599 - accuracy: 0.8475 - val_loss: 0.4864 - val_accuracy: 0.8586
Epoch 97/100
2/2 [==============================] - 0s 32ms/step - loss: 0.4548 - accuracy: 0.8492 - val_loss: 0.4824 - val_accuracy: 0.8618
Epoch 98/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4460 - accuracy: 0.8492 - val_loss: 0.4787 - val_accuracy: 0.8618
Epoch 99/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4477 - accuracy: 0.8426 - val_loss: 0.4753 - val_accuracy: 0.8618
Epoch 100/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4438 - accuracy: 0.8426 - val_loss: 0.4721 - val_accuracy: 0.8618
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 7
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': False, 'initializers': 'glorot_normal'}
Batch size: 256
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
3/3 [==============================] - 1s 118ms/step - loss: 2.5746 - accuracy: 0.4401 - val_loss: 2.4969 - val_accuracy: 0.5049
Epoch 2/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5367 - accuracy: 0.4598 - val_loss: 2.4963 - val_accuracy: 0.5049
Epoch 3/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5346 - accuracy: 0.4647 - val_loss: 2.4958 - val_accuracy: 0.5049
Epoch 4/100
3/3 [==============================] - 0s 24ms/step - loss: 2.5263 - accuracy: 0.4499 - val_loss: 2.4953 - val_accuracy: 0.5049
Epoch 5/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5490 - accuracy: 0.4319 - val_loss: 2.4947 - val_accuracy: 0.5049
Epoch 6/100
3/3 [==============================] - 0s 15ms/step - loss: 2.5044 - accuracy: 0.4631 - val_loss: 2.4942 - val_accuracy: 0.5049
Epoch 7/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5620 - accuracy: 0.4647 - val_loss: 2.4937 - val_accuracy: 0.5049
Epoch 8/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5424 - accuracy: 0.4565 - val_loss: 2.4932 - val_accuracy: 0.5049
Epoch 9/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5246 - accuracy: 0.4516 - val_loss: 2.4927 - val_accuracy: 0.5049
Epoch 10/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4833 - accuracy: 0.4729 - val_loss: 2.4922 - val_accuracy: 0.5049
Epoch 11/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5114 - accuracy: 0.4565 - val_loss: 2.4917 - val_accuracy: 0.5049
Epoch 12/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5508 - accuracy: 0.4286 - val_loss: 2.4912 - val_accuracy: 0.5049
Epoch 13/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5352 - accuracy: 0.4581 - val_loss: 2.4907 - val_accuracy: 0.5049
Epoch 14/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5265 - accuracy: 0.4877 - val_loss: 2.4902 - val_accuracy: 0.5082
Epoch 15/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5153 - accuracy: 0.4926 - val_loss: 2.4898 - val_accuracy: 0.5082
Epoch 16/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5421 - accuracy: 0.4663 - val_loss: 2.4892 - val_accuracy: 0.5082
Epoch 17/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5116 - accuracy: 0.4532 - val_loss: 2.4888 - val_accuracy: 0.5082
Epoch 18/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5259 - accuracy: 0.4516 - val_loss: 2.4883 - val_accuracy: 0.5082
Epoch 19/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4982 - accuracy: 0.4729 - val_loss: 2.4878 - val_accuracy: 0.5082
Epoch 20/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5293 - accuracy: 0.4729 - val_loss: 2.4873 - val_accuracy: 0.5082
Epoch 21/100
3/3 [==============================] - 0s 15ms/step - loss: 2.4994 - accuracy: 0.4926 - val_loss: 2.4868 - val_accuracy: 0.5082
Epoch 22/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5271 - accuracy: 0.4614 - val_loss: 2.4863 - val_accuracy: 0.5082
Epoch 23/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4995 - accuracy: 0.4713 - val_loss: 2.4858 - val_accuracy: 0.5115
Epoch 24/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5652 - accuracy: 0.4319 - val_loss: 2.4853 - val_accuracy: 0.5115
Epoch 25/100
3/3 [==============================] - 0s 15ms/step - loss: 2.5282 - accuracy: 0.4647 - val_loss: 2.4848 - val_accuracy: 0.5115
Epoch 26/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5597 - accuracy: 0.4713 - val_loss: 2.4843 - val_accuracy: 0.5115
Epoch 27/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5352 - accuracy: 0.4483 - val_loss: 2.4838 - val_accuracy: 0.5115
Epoch 28/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5146 - accuracy: 0.4499 - val_loss: 2.4833 - val_accuracy: 0.5115
Epoch 29/100
3/3 [==============================] - 0s 24ms/step - loss: 2.5118 - accuracy: 0.4729 - val_loss: 2.4828 - val_accuracy: 0.5115
Epoch 30/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4926 - accuracy: 0.4598 - val_loss: 2.4823 - val_accuracy: 0.5115
Epoch 31/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5309 - accuracy: 0.4401 - val_loss: 2.4818 - val_accuracy: 0.5115
Epoch 32/100
3/3 [==============================] - 0s 28ms/step - loss: 2.4996 - accuracy: 0.4598 - val_loss: 2.4813 - val_accuracy: 0.5115
Epoch 33/100
3/3 [==============================] - 0s 15ms/step - loss: 2.5057 - accuracy: 0.4795 - val_loss: 2.4808 - val_accuracy: 0.5115
Epoch 34/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5104 - accuracy: 0.4598 - val_loss: 2.4803 - val_accuracy: 0.5115
Epoch 35/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5587 - accuracy: 0.4236 - val_loss: 2.4798 - val_accuracy: 0.5115
Epoch 36/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5352 - accuracy: 0.4499 - val_loss: 2.4793 - val_accuracy: 0.5115
Epoch 37/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5222 - accuracy: 0.4926 - val_loss: 2.4788 - val_accuracy: 0.5115
Epoch 38/100
3/3 [==============================] - 0s 26ms/step - loss: 2.5217 - accuracy: 0.4532 - val_loss: 2.4784 - val_accuracy: 0.5115
Epoch 39/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5116 - accuracy: 0.4499 - val_loss: 2.4779 - val_accuracy: 0.5115
Epoch 40/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5070 - accuracy: 0.4663 - val_loss: 2.4774 - val_accuracy: 0.5148
Epoch 41/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5014 - accuracy: 0.4762 - val_loss: 2.4769 - val_accuracy: 0.5148
Epoch 42/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4952 - accuracy: 0.4729 - val_loss: 2.4764 - val_accuracy: 0.5148
Epoch 43/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5192 - accuracy: 0.4647 - val_loss: 2.4759 - val_accuracy: 0.5148
Epoch 44/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5122 - accuracy: 0.4631 - val_loss: 2.4754 - val_accuracy: 0.5148
Epoch 45/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5219 - accuracy: 0.4663 - val_loss: 2.4749 - val_accuracy: 0.5148
Epoch 46/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5146 - accuracy: 0.4565 - val_loss: 2.4744 - val_accuracy: 0.5148
Epoch 47/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4819 - accuracy: 0.4795 - val_loss: 2.4739 - val_accuracy: 0.5148
Epoch 48/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5288 - accuracy: 0.4532 - val_loss: 2.4734 - val_accuracy: 0.5115
Epoch 49/100
3/3 [==============================] - 0s 14ms/step - loss: 2.5050 - accuracy: 0.4631 - val_loss: 2.4729 - val_accuracy: 0.5115
Epoch 50/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5062 - accuracy: 0.4877 - val_loss: 2.4724 - val_accuracy: 0.5115
Epoch 51/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4862 - accuracy: 0.4565 - val_loss: 2.4719 - val_accuracy: 0.5115
Epoch 52/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5285 - accuracy: 0.4499 - val_loss: 2.4714 - val_accuracy: 0.5115
Epoch 53/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4999 - accuracy: 0.4433 - val_loss: 2.4709 - val_accuracy: 0.5148
Epoch 54/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5261 - accuracy: 0.4778 - val_loss: 2.4704 - val_accuracy: 0.5148
Epoch 55/100
3/3 [==============================] - 0s 24ms/step - loss: 2.5081 - accuracy: 0.4516 - val_loss: 2.4700 - val_accuracy: 0.5213
Epoch 56/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4830 - accuracy: 0.4532 - val_loss: 2.4695 - val_accuracy: 0.5213
Epoch 57/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5212 - accuracy: 0.4614 - val_loss: 2.4690 - val_accuracy: 0.5213
Epoch 58/100
3/3 [==============================] - 0s 24ms/step - loss: 2.5306 - accuracy: 0.4516 - val_loss: 2.4685 - val_accuracy: 0.5213
Epoch 59/100
3/3 [==============================] - 0s 14ms/step - loss: 2.5049 - accuracy: 0.4532 - val_loss: 2.4680 - val_accuracy: 0.5213
Epoch 60/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5205 - accuracy: 0.4680 - val_loss: 2.4675 - val_accuracy: 0.5213
Epoch 61/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5234 - accuracy: 0.4351 - val_loss: 2.4670 - val_accuracy: 0.5213
Epoch 62/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5530 - accuracy: 0.4499 - val_loss: 2.4665 - val_accuracy: 0.5213
Epoch 63/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4625 - accuracy: 0.4860 - val_loss: 2.4660 - val_accuracy: 0.5213
Epoch 64/100
3/3 [==============================] - 0s 24ms/step - loss: 2.4844 - accuracy: 0.4778 - val_loss: 2.4655 - val_accuracy: 0.5213
Epoch 65/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5038 - accuracy: 0.4844 - val_loss: 2.4650 - val_accuracy: 0.5213
Epoch 66/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4601 - accuracy: 0.5090 - val_loss: 2.4646 - val_accuracy: 0.5213
Epoch 67/100
3/3 [==============================] - 0s 15ms/step - loss: 2.5129 - accuracy: 0.4795 - val_loss: 2.4641 - val_accuracy: 0.5213
Epoch 68/100
3/3 [==============================] - 0s 17ms/step - loss: 2.5438 - accuracy: 0.4647 - val_loss: 2.4636 - val_accuracy: 0.5213
Epoch 69/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5319 - accuracy: 0.4614 - val_loss: 2.4631 - val_accuracy: 0.5213
Epoch 70/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4845 - accuracy: 0.4663 - val_loss: 2.4626 - val_accuracy: 0.5213
Epoch 71/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5370 - accuracy: 0.4598 - val_loss: 2.4621 - val_accuracy: 0.5213
Epoch 72/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4870 - accuracy: 0.4877 - val_loss: 2.4616 - val_accuracy: 0.5213
Epoch 73/100
3/3 [==============================] - 0s 24ms/step - loss: 2.5408 - accuracy: 0.4565 - val_loss: 2.4611 - val_accuracy: 0.5213
Epoch 74/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4945 - accuracy: 0.4877 - val_loss: 2.4606 - val_accuracy: 0.5213
Epoch 75/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5024 - accuracy: 0.4745 - val_loss: 2.4602 - val_accuracy: 0.5213
Epoch 76/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4989 - accuracy: 0.4713 - val_loss: 2.4597 - val_accuracy: 0.5213
Epoch 77/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4845 - accuracy: 0.4696 - val_loss: 2.4592 - val_accuracy: 0.5213
Epoch 78/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4940 - accuracy: 0.4565 - val_loss: 2.4587 - val_accuracy: 0.5213
Epoch 79/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4753 - accuracy: 0.4713 - val_loss: 2.4582 - val_accuracy: 0.5213
Epoch 80/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5160 - accuracy: 0.4532 - val_loss: 2.4577 - val_accuracy: 0.5213
Epoch 81/100
3/3 [==============================] - 0s 18ms/step - loss: 2.4971 - accuracy: 0.4598 - val_loss: 2.4572 - val_accuracy: 0.5213
Epoch 82/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4794 - accuracy: 0.4828 - val_loss: 2.4567 - val_accuracy: 0.5213
Epoch 83/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4571 - accuracy: 0.4762 - val_loss: 2.4562 - val_accuracy: 0.5213
Epoch 84/100
3/3 [==============================] - 0s 18ms/step - loss: 2.5223 - accuracy: 0.4548 - val_loss: 2.4557 - val_accuracy: 0.5213
Epoch 85/100
3/3 [==============================] - 0s 24ms/step - loss: 2.5233 - accuracy: 0.4598 - val_loss: 2.4553 - val_accuracy: 0.5213
Epoch 86/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4780 - accuracy: 0.4483 - val_loss: 2.4548 - val_accuracy: 0.5213
Epoch 87/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5201 - accuracy: 0.4598 - val_loss: 2.4543 - val_accuracy: 0.5213
Epoch 88/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4866 - accuracy: 0.4778 - val_loss: 2.4538 - val_accuracy: 0.5213
Epoch 89/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4905 - accuracy: 0.4729 - val_loss: 2.4533 - val_accuracy: 0.5213
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4786 - accuracy: 0.4943 - val_loss: 2.4528 - val_accuracy: 0.5213
Epoch 91/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5002 - accuracy: 0.4844 - val_loss: 2.4523 - val_accuracy: 0.5213
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4822 - accuracy: 0.4548 - val_loss: 2.4518 - val_accuracy: 0.5213
Epoch 93/100
3/3 [==============================] - 0s 31ms/step - loss: 2.5131 - accuracy: 0.4631 - val_loss: 2.4513 - val_accuracy: 0.5213
Epoch 94/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4566 - accuracy: 0.4663 - val_loss: 2.4508 - val_accuracy: 0.5213
Epoch 95/100
3/3 [==============================] - 0s 25ms/step - loss: 2.4805 - accuracy: 0.4614 - val_loss: 2.4504 - val_accuracy: 0.5213
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5061 - accuracy: 0.4631 - val_loss: 2.4499 - val_accuracy: 0.5213
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4925 - accuracy: 0.4729 - val_loss: 2.4494 - val_accuracy: 0.5213
Epoch 98/100
3/3 [==============================] - 0s 14ms/step - loss: 2.4850 - accuracy: 0.4647 - val_loss: 2.4489 - val_accuracy: 0.5213
Epoch 99/100
3/3 [==============================] - 0s 22ms/step - loss: 2.4876 - accuracy: 0.4713 - val_loss: 2.4484 - val_accuracy: 0.5213
Epoch 100/100
3/3 [==============================] - 0s 21ms/step - loss: 2.5231 - accuracy: 0.4433 - val_loss: 2.4479 - val_accuracy: 0.5213
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 193us/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': False, 'initializers': 'glorot_normal'}
Batch size: 256
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
3/3 [==============================] - 1s 117ms/step - loss: 2.8824 - accuracy: 0.1527 - val_loss: 2.8262 - val_accuracy: 0.1016
Epoch 2/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8994 - accuracy: 0.1478 - val_loss: 2.8255 - val_accuracy: 0.1016
Epoch 3/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8990 - accuracy: 0.1445 - val_loss: 2.8249 - val_accuracy: 0.1016
Epoch 4/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8676 - accuracy: 0.1609 - val_loss: 2.8243 - val_accuracy: 0.1016
Epoch 5/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8844 - accuracy: 0.1560 - val_loss: 2.8237 - val_accuracy: 0.1016
Epoch 6/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8626 - accuracy: 0.1856 - val_loss: 2.8231 - val_accuracy: 0.1016
Epoch 7/100
3/3 [==============================] - 0s 15ms/step - loss: 2.8756 - accuracy: 0.1773 - val_loss: 2.8225 - val_accuracy: 0.1016
Epoch 8/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8711 - accuracy: 0.1724 - val_loss: 2.8220 - val_accuracy: 0.1016
Epoch 9/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8828 - accuracy: 0.1741 - val_loss: 2.8214 - val_accuracy: 0.1016
Epoch 10/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8544 - accuracy: 0.1823 - val_loss: 2.8208 - val_accuracy: 0.1016
Epoch 11/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8731 - accuracy: 0.1691 - val_loss: 2.8203 - val_accuracy: 0.1016
Epoch 12/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8740 - accuracy: 0.1724 - val_loss: 2.8197 - val_accuracy: 0.1016
Epoch 13/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8701 - accuracy: 0.1511 - val_loss: 2.8191 - val_accuracy: 0.1016
Epoch 14/100
3/3 [==============================] - 0s 26ms/step - loss: 2.8863 - accuracy: 0.1346 - val_loss: 2.8185 - val_accuracy: 0.1016
Epoch 15/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8514 - accuracy: 0.1609 - val_loss: 2.8180 - val_accuracy: 0.1016
Epoch 16/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8980 - accuracy: 0.1445 - val_loss: 2.8174 - val_accuracy: 0.1016
Epoch 17/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8706 - accuracy: 0.1429 - val_loss: 2.8168 - val_accuracy: 0.1016
Epoch 18/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8802 - accuracy: 0.1790 - val_loss: 2.8163 - val_accuracy: 0.1016
Epoch 19/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8714 - accuracy: 0.1658 - val_loss: 2.8157 - val_accuracy: 0.1016
Epoch 20/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8856 - accuracy: 0.1691 - val_loss: 2.8151 - val_accuracy: 0.1016
Epoch 21/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8627 - accuracy: 0.1330 - val_loss: 2.8146 - val_accuracy: 0.1016
Epoch 22/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8849 - accuracy: 0.1839 - val_loss: 2.8140 - val_accuracy: 0.1016
Epoch 23/100
3/3 [==============================] - 0s 13ms/step - loss: 2.8734 - accuracy: 0.1593 - val_loss: 2.8134 - val_accuracy: 0.1016
Epoch 24/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8505 - accuracy: 0.1576 - val_loss: 2.8128 - val_accuracy: 0.1016
Epoch 25/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8837 - accuracy: 0.1527 - val_loss: 2.8123 - val_accuracy: 0.1016
Epoch 26/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8680 - accuracy: 0.1658 - val_loss: 2.8117 - val_accuracy: 0.1016
Epoch 27/100
3/3 [==============================] - 0s 26ms/step - loss: 2.8560 - accuracy: 0.1856 - val_loss: 2.8111 - val_accuracy: 0.1016
Epoch 28/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8876 - accuracy: 0.1363 - val_loss: 2.8106 - val_accuracy: 0.1016
Epoch 29/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8689 - accuracy: 0.1773 - val_loss: 2.8100 - val_accuracy: 0.1016
Epoch 30/100
3/3 [==============================] - 0s 23ms/step - loss: 2.8620 - accuracy: 0.1658 - val_loss: 2.8094 - val_accuracy: 0.1016
Epoch 31/100
3/3 [==============================] - 0s 15ms/step - loss: 2.8539 - accuracy: 0.1839 - val_loss: 2.8089 - val_accuracy: 0.1016
Epoch 32/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8511 - accuracy: 0.1461 - val_loss: 2.8083 - val_accuracy: 0.1016
Epoch 33/100
3/3 [==============================] - 0s 22ms/step - loss: 2.8925 - accuracy: 0.1461 - val_loss: 2.8077 - val_accuracy: 0.1016
Epoch 34/100
3/3 [==============================] - 0s 19ms/step - loss: 2.8818 - accuracy: 0.1494 - val_loss: 2.8072 - val_accuracy: 0.1016
Epoch 35/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8853 - accuracy: 0.1658 - val_loss: 2.8066 - val_accuracy: 0.1016
Epoch 36/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8880 - accuracy: 0.1544 - val_loss: 2.8060 - val_accuracy: 0.1016
Epoch 37/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8651 - accuracy: 0.1593 - val_loss: 2.8055 - val_accuracy: 0.1016
Epoch 38/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8671 - accuracy: 0.1576 - val_loss: 2.8049 - val_accuracy: 0.1016
Epoch 39/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8292 - accuracy: 0.1921 - val_loss: 2.8043 - val_accuracy: 0.1016
Epoch 40/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8598 - accuracy: 0.1560 - val_loss: 2.8038 - val_accuracy: 0.1016
Epoch 41/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8603 - accuracy: 0.1741 - val_loss: 2.8032 - val_accuracy: 0.1016
Epoch 42/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8544 - accuracy: 0.1609 - val_loss: 2.8026 - val_accuracy: 0.1016
Epoch 43/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8426 - accuracy: 0.1741 - val_loss: 2.8021 - val_accuracy: 0.1016
Epoch 44/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8610 - accuracy: 0.1642 - val_loss: 2.8015 - val_accuracy: 0.1016
Epoch 45/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8585 - accuracy: 0.1560 - val_loss: 2.8009 - val_accuracy: 0.1016
Epoch 46/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8482 - accuracy: 0.1642 - val_loss: 2.8004 - val_accuracy: 0.1016
Epoch 47/100
3/3 [==============================] - 0s 19ms/step - loss: 2.8600 - accuracy: 0.1691 - val_loss: 2.7998 - val_accuracy: 0.1016
Epoch 48/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8433 - accuracy: 0.1658 - val_loss: 2.7992 - val_accuracy: 0.1016
Epoch 49/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8506 - accuracy: 0.1790 - val_loss: 2.7987 - val_accuracy: 0.1016
Epoch 50/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8590 - accuracy: 0.1626 - val_loss: 2.7981 - val_accuracy: 0.1016
Epoch 51/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8598 - accuracy: 0.1626 - val_loss: 2.7975 - val_accuracy: 0.1016
Epoch 52/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8647 - accuracy: 0.1626 - val_loss: 2.7970 - val_accuracy: 0.1016
Epoch 53/100
3/3 [==============================] - 0s 27ms/step - loss: 2.8374 - accuracy: 0.1724 - val_loss: 2.7964 - val_accuracy: 0.1016
Epoch 54/100
3/3 [==============================] - 0s 23ms/step - loss: 2.8273 - accuracy: 0.1823 - val_loss: 2.7958 - val_accuracy: 0.1016
Epoch 55/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8513 - accuracy: 0.1691 - val_loss: 2.7953 - val_accuracy: 0.1016
Epoch 56/100
3/3 [==============================] - 0s 26ms/step - loss: 2.8487 - accuracy: 0.1560 - val_loss: 2.7947 - val_accuracy: 0.1016
Epoch 57/100
3/3 [==============================] - 0s 20ms/step - loss: 2.8422 - accuracy: 0.1773 - val_loss: 2.7942 - val_accuracy: 0.1016
Epoch 58/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8475 - accuracy: 0.1675 - val_loss: 2.7936 - val_accuracy: 0.1016
Epoch 59/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8462 - accuracy: 0.1675 - val_loss: 2.7930 - val_accuracy: 0.1016
Epoch 60/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8296 - accuracy: 0.1708 - val_loss: 2.7925 - val_accuracy: 0.1016
Epoch 61/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8389 - accuracy: 0.1872 - val_loss: 2.7919 - val_accuracy: 0.1016
Epoch 62/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8344 - accuracy: 0.1675 - val_loss: 2.7913 - val_accuracy: 0.1016
Epoch 63/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8466 - accuracy: 0.1675 - val_loss: 2.7908 - val_accuracy: 0.1016
Epoch 64/100
3/3 [==============================] - 0s 15ms/step - loss: 2.8393 - accuracy: 0.1609 - val_loss: 2.7902 - val_accuracy: 0.1016
Epoch 65/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8488 - accuracy: 0.1642 - val_loss: 2.7896 - val_accuracy: 0.1016
Epoch 66/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8258 - accuracy: 0.1560 - val_loss: 2.7891 - val_accuracy: 0.1016
Epoch 67/100
3/3 [==============================] - 0s 27ms/step - loss: 2.8192 - accuracy: 0.1773 - val_loss: 2.7885 - val_accuracy: 0.1016
Epoch 68/100
3/3 [==============================] - 0s 20ms/step - loss: 2.8043 - accuracy: 0.1675 - val_loss: 2.7880 - val_accuracy: 0.1016
Epoch 69/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8640 - accuracy: 0.1363 - val_loss: 2.7874 - val_accuracy: 0.1016
Epoch 70/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8430 - accuracy: 0.1658 - val_loss: 2.7868 - val_accuracy: 0.1016
Epoch 71/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8542 - accuracy: 0.1494 - val_loss: 2.7863 - val_accuracy: 0.1016
Epoch 72/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8569 - accuracy: 0.1609 - val_loss: 2.7857 - val_accuracy: 0.1016
Epoch 73/100
3/3 [==============================] - 0s 14ms/step - loss: 2.8179 - accuracy: 0.1856 - val_loss: 2.7851 - val_accuracy: 0.1016
Epoch 74/100
3/3 [==============================] - 0s 15ms/step - loss: 2.8536 - accuracy: 0.1560 - val_loss: 2.7846 - val_accuracy: 0.1016
Epoch 75/100
3/3 [==============================] - 0s 15ms/step - loss: 2.8573 - accuracy: 0.1593 - val_loss: 2.7840 - val_accuracy: 0.1016
Epoch 76/100
3/3 [==============================] - 0s 19ms/step - loss: 2.8366 - accuracy: 0.1724 - val_loss: 2.7834 - val_accuracy: 0.1016
Epoch 77/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8406 - accuracy: 0.1790 - val_loss: 2.7829 - val_accuracy: 0.1016
Epoch 78/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8566 - accuracy: 0.1658 - val_loss: 2.7823 - val_accuracy: 0.1016
Epoch 79/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8631 - accuracy: 0.1461 - val_loss: 2.7818 - val_accuracy: 0.1016
Epoch 80/100
3/3 [==============================] - 0s 19ms/step - loss: 2.8467 - accuracy: 0.1724 - val_loss: 2.7812 - val_accuracy: 0.1016
Epoch 81/100
3/3 [==============================] - 0s 13ms/step - loss: 2.8429 - accuracy: 0.1658 - val_loss: 2.7806 - val_accuracy: 0.1016
Epoch 82/100
3/3 [==============================] - 0s 14ms/step - loss: 2.8197 - accuracy: 0.1691 - val_loss: 2.7801 - val_accuracy: 0.1016
Epoch 83/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8248 - accuracy: 0.1691 - val_loss: 2.7795 - val_accuracy: 0.1016
Epoch 84/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8281 - accuracy: 0.1757 - val_loss: 2.7790 - val_accuracy: 0.1016
Epoch 85/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8168 - accuracy: 0.1675 - val_loss: 2.7784 - val_accuracy: 0.1049
Epoch 86/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8274 - accuracy: 0.1905 - val_loss: 2.7778 - val_accuracy: 0.1049
Epoch 87/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8239 - accuracy: 0.1823 - val_loss: 2.7773 - val_accuracy: 0.1049
Epoch 88/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8517 - accuracy: 0.1642 - val_loss: 2.7767 - val_accuracy: 0.1049
Epoch 89/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8317 - accuracy: 0.1642 - val_loss: 2.7762 - val_accuracy: 0.1049
Epoch 90/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8191 - accuracy: 0.1823 - val_loss: 2.7756 - val_accuracy: 0.1049
Epoch 91/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8398 - accuracy: 0.1642 - val_loss: 2.7750 - val_accuracy: 0.1049
Epoch 92/100
3/3 [==============================] - 0s 19ms/step - loss: 2.8407 - accuracy: 0.1626 - val_loss: 2.7745 - val_accuracy: 0.1049
Epoch 93/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8382 - accuracy: 0.1724 - val_loss: 2.7739 - val_accuracy: 0.1049
Epoch 94/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8406 - accuracy: 0.1724 - val_loss: 2.7734 - val_accuracy: 0.1049
Epoch 95/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8547 - accuracy: 0.1708 - val_loss: 2.7728 - val_accuracy: 0.1049
Epoch 96/100
3/3 [==============================] - 0s 27ms/step - loss: 2.8302 - accuracy: 0.1773 - val_loss: 2.7722 - val_accuracy: 0.1049
Epoch 97/100
3/3 [==============================] - 0s 22ms/step - loss: 2.8327 - accuracy: 0.1544 - val_loss: 2.7717 - val_accuracy: 0.1049
Epoch 98/100
3/3 [==============================] - 0s 20ms/step - loss: 2.8228 - accuracy: 0.1724 - val_loss: 2.7711 - val_accuracy: 0.1049
Epoch 99/100
3/3 [==============================] - 0s 13ms/step - loss: 2.8541 - accuracy: 0.1593 - val_loss: 2.7706 - val_accuracy: 0.1049
Epoch 100/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8201 - accuracy: 0.1773 - val_loss: 2.7700 - val_accuracy: 0.1049
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 1e-05, 'optimizer': 'RMSprop', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': False, 'initializers': 'glorot_normal'}
Batch size: 256
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
3/3 [==============================] - 1s 114ms/step - loss: 2.3553 - accuracy: 0.5738 - val_loss: 2.3477 - val_accuracy: 0.5526
Epoch 2/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3725 - accuracy: 0.5721 - val_loss: 2.3472 - val_accuracy: 0.5526
Epoch 3/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3553 - accuracy: 0.6098 - val_loss: 2.3467 - val_accuracy: 0.5526
Epoch 4/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3510 - accuracy: 0.5689 - val_loss: 2.3463 - val_accuracy: 0.5526
Epoch 5/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3472 - accuracy: 0.5984 - val_loss: 2.3459 - val_accuracy: 0.5526
Epoch 6/100
3/3 [==============================] - 0s 15ms/step - loss: 2.3703 - accuracy: 0.5459 - val_loss: 2.3454 - val_accuracy: 0.5526
Epoch 7/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3635 - accuracy: 0.5836 - val_loss: 2.3450 - val_accuracy: 0.5526
Epoch 8/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3660 - accuracy: 0.5852 - val_loss: 2.3446 - val_accuracy: 0.5526
Epoch 9/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3934 - accuracy: 0.5705 - val_loss: 2.3442 - val_accuracy: 0.5526
Epoch 10/100
3/3 [==============================] - 0s 40ms/step - loss: 2.3557 - accuracy: 0.5623 - val_loss: 2.3438 - val_accuracy: 0.5526
Epoch 11/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3583 - accuracy: 0.5951 - val_loss: 2.3434 - val_accuracy: 0.5526
Epoch 12/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3192 - accuracy: 0.5934 - val_loss: 2.3430 - val_accuracy: 0.5526
Epoch 13/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3474 - accuracy: 0.5885 - val_loss: 2.3425 - val_accuracy: 0.5526
Epoch 14/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3678 - accuracy: 0.5984 - val_loss: 2.3421 - val_accuracy: 0.5526
Epoch 15/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3789 - accuracy: 0.5836 - val_loss: 2.3417 - val_accuracy: 0.5526
Epoch 16/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3447 - accuracy: 0.5852 - val_loss: 2.3413 - val_accuracy: 0.5526
Epoch 17/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3595 - accuracy: 0.5803 - val_loss: 2.3409 - val_accuracy: 0.5526
Epoch 18/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3392 - accuracy: 0.5852 - val_loss: 2.3404 - val_accuracy: 0.5526
Epoch 19/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3726 - accuracy: 0.5623 - val_loss: 2.3400 - val_accuracy: 0.5559
Epoch 20/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3739 - accuracy: 0.5770 - val_loss: 2.3396 - val_accuracy: 0.5559
Epoch 21/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3538 - accuracy: 0.5951 - val_loss: 2.3392 - val_accuracy: 0.5559
Epoch 22/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3819 - accuracy: 0.5738 - val_loss: 2.3388 - val_accuracy: 0.5559
Epoch 23/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3567 - accuracy: 0.5820 - val_loss: 2.3383 - val_accuracy: 0.5592
Epoch 24/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3938 - accuracy: 0.5787 - val_loss: 2.3379 - val_accuracy: 0.5592
Epoch 25/100
3/3 [==============================] - 0s 29ms/step - loss: 2.3632 - accuracy: 0.5803 - val_loss: 2.3375 - val_accuracy: 0.5592
Epoch 26/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3176 - accuracy: 0.6082 - val_loss: 2.3371 - val_accuracy: 0.5592
Epoch 27/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3346 - accuracy: 0.5885 - val_loss: 2.3367 - val_accuracy: 0.5592
Epoch 28/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3633 - accuracy: 0.5623 - val_loss: 2.3363 - val_accuracy: 0.5592
Epoch 29/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3432 - accuracy: 0.5721 - val_loss: 2.3359 - val_accuracy: 0.5592
Epoch 30/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3381 - accuracy: 0.6016 - val_loss: 2.3354 - val_accuracy: 0.5592
Epoch 31/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3457 - accuracy: 0.6016 - val_loss: 2.3350 - val_accuracy: 0.5592
Epoch 32/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3462 - accuracy: 0.5820 - val_loss: 2.3346 - val_accuracy: 0.5592
Epoch 33/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3725 - accuracy: 0.5869 - val_loss: 2.3342 - val_accuracy: 0.5592
Epoch 34/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3772 - accuracy: 0.5770 - val_loss: 2.3338 - val_accuracy: 0.5592
Epoch 35/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3835 - accuracy: 0.5557 - val_loss: 2.3334 - val_accuracy: 0.5592
Epoch 36/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3521 - accuracy: 0.5836 - val_loss: 2.3329 - val_accuracy: 0.5592
Epoch 37/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3177 - accuracy: 0.5836 - val_loss: 2.3325 - val_accuracy: 0.5592
Epoch 38/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3290 - accuracy: 0.5836 - val_loss: 2.3321 - val_accuracy: 0.5592
Epoch 39/100
3/3 [==============================] - 0s 20ms/step - loss: 2.3228 - accuracy: 0.5934 - val_loss: 2.3317 - val_accuracy: 0.5592
Epoch 40/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3455 - accuracy: 0.5967 - val_loss: 2.3313 - val_accuracy: 0.5592
Epoch 41/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3358 - accuracy: 0.5803 - val_loss: 2.3309 - val_accuracy: 0.5592
Epoch 42/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3382 - accuracy: 0.5934 - val_loss: 2.3304 - val_accuracy: 0.5592
Epoch 43/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3351 - accuracy: 0.5869 - val_loss: 2.3300 - val_accuracy: 0.5592
Epoch 44/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3414 - accuracy: 0.5787 - val_loss: 2.3296 - val_accuracy: 0.5592
Epoch 45/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3458 - accuracy: 0.5721 - val_loss: 2.3292 - val_accuracy: 0.5592
Epoch 46/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3419 - accuracy: 0.5918 - val_loss: 2.3288 - val_accuracy: 0.5592
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3434 - accuracy: 0.6016 - val_loss: 2.3284 - val_accuracy: 0.5625
Epoch 48/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3136 - accuracy: 0.6000 - val_loss: 2.3280 - val_accuracy: 0.5625
Epoch 49/100
3/3 [==============================] - 0s 21ms/step - loss: 2.3083 - accuracy: 0.6033 - val_loss: 2.3276 - val_accuracy: 0.5625
Epoch 50/100
3/3 [==============================] - 0s 15ms/step - loss: 2.3282 - accuracy: 0.6230 - val_loss: 2.3271 - val_accuracy: 0.5625
Epoch 51/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3386 - accuracy: 0.5836 - val_loss: 2.3267 - val_accuracy: 0.5625
Epoch 52/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3057 - accuracy: 0.6066 - val_loss: 2.3263 - val_accuracy: 0.5625
Epoch 53/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3666 - accuracy: 0.5803 - val_loss: 2.3259 - val_accuracy: 0.5625
Epoch 54/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3498 - accuracy: 0.6066 - val_loss: 2.3255 - val_accuracy: 0.5625
Epoch 55/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3480 - accuracy: 0.6000 - val_loss: 2.3251 - val_accuracy: 0.5625
Epoch 56/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3198 - accuracy: 0.5934 - val_loss: 2.3246 - val_accuracy: 0.5625
Epoch 57/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3261 - accuracy: 0.6131 - val_loss: 2.3242 - val_accuracy: 0.5625
Epoch 58/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3307 - accuracy: 0.5820 - val_loss: 2.3238 - val_accuracy: 0.5625
Epoch 59/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3378 - accuracy: 0.5852 - val_loss: 2.3234 - val_accuracy: 0.5625
Epoch 60/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3305 - accuracy: 0.5902 - val_loss: 2.3230 - val_accuracy: 0.5625
Epoch 61/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3373 - accuracy: 0.5885 - val_loss: 2.3226 - val_accuracy: 0.5625
Epoch 62/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3209 - accuracy: 0.6033 - val_loss: 2.3222 - val_accuracy: 0.5625
Epoch 63/100
3/3 [==============================] - 0s 15ms/step - loss: 2.3467 - accuracy: 0.5754 - val_loss: 2.3217 - val_accuracy: 0.5625
Epoch 64/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3301 - accuracy: 0.6082 - val_loss: 2.3213 - val_accuracy: 0.5625
Epoch 65/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3234 - accuracy: 0.5738 - val_loss: 2.3209 - val_accuracy: 0.5625
Epoch 66/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3467 - accuracy: 0.5852 - val_loss: 2.3205 - val_accuracy: 0.5625
Epoch 67/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3104 - accuracy: 0.6033 - val_loss: 2.3201 - val_accuracy: 0.5625
Epoch 68/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3403 - accuracy: 0.5934 - val_loss: 2.3197 - val_accuracy: 0.5625
Epoch 69/100
3/3 [==============================] - 0s 27ms/step - loss: 2.3364 - accuracy: 0.5623 - val_loss: 2.3193 - val_accuracy: 0.5625
Epoch 70/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3178 - accuracy: 0.5656 - val_loss: 2.3188 - val_accuracy: 0.5625
Epoch 71/100
3/3 [==============================] - 0s 27ms/step - loss: 2.3372 - accuracy: 0.6033 - val_loss: 2.3184 - val_accuracy: 0.5625
Epoch 72/100
3/3 [==============================] - 0s 23ms/step - loss: 2.3379 - accuracy: 0.5885 - val_loss: 2.3180 - val_accuracy: 0.5625
Epoch 73/100
3/3 [==============================] - 0s 29ms/step - loss: 2.3301 - accuracy: 0.6115 - val_loss: 2.3176 - val_accuracy: 0.5625
Epoch 74/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3485 - accuracy: 0.5803 - val_loss: 2.3172 - val_accuracy: 0.5625
Epoch 75/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3218 - accuracy: 0.5902 - val_loss: 2.3168 - val_accuracy: 0.5625
Epoch 76/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3368 - accuracy: 0.5852 - val_loss: 2.3164 - val_accuracy: 0.5625
Epoch 77/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3364 - accuracy: 0.5852 - val_loss: 2.3160 - val_accuracy: 0.5625
Epoch 78/100
3/3 [==============================] - 0s 12ms/step - loss: 2.3512 - accuracy: 0.6066 - val_loss: 2.3156 - val_accuracy: 0.5625
Epoch 79/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3525 - accuracy: 0.5803 - val_loss: 2.3151 - val_accuracy: 0.5625
Epoch 80/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3433 - accuracy: 0.5902 - val_loss: 2.3147 - val_accuracy: 0.5625
Epoch 81/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3240 - accuracy: 0.6082 - val_loss: 2.3143 - val_accuracy: 0.5625
Epoch 82/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3484 - accuracy: 0.5770 - val_loss: 2.3139 - val_accuracy: 0.5625
Epoch 83/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3313 - accuracy: 0.5820 - val_loss: 2.3135 - val_accuracy: 0.5625
Epoch 84/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3412 - accuracy: 0.5754 - val_loss: 2.3131 - val_accuracy: 0.5625
Epoch 85/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3215 - accuracy: 0.5852 - val_loss: 2.3127 - val_accuracy: 0.5625
Epoch 86/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3416 - accuracy: 0.5574 - val_loss: 2.3123 - val_accuracy: 0.5625
Epoch 87/100
3/3 [==============================] - 0s 16ms/step - loss: 2.2901 - accuracy: 0.5918 - val_loss: 2.3119 - val_accuracy: 0.5625
Epoch 88/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3661 - accuracy: 0.5672 - val_loss: 2.3115 - val_accuracy: 0.5625
Epoch 89/100
3/3 [==============================] - 0s 27ms/step - loss: 2.3340 - accuracy: 0.5902 - val_loss: 2.3110 - val_accuracy: 0.5625
Epoch 90/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3518 - accuracy: 0.5869 - val_loss: 2.3106 - val_accuracy: 0.5625
Epoch 91/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3046 - accuracy: 0.6033 - val_loss: 2.3102 - val_accuracy: 0.5625
Epoch 92/100
3/3 [==============================] - 0s 24ms/step - loss: 2.3520 - accuracy: 0.5689 - val_loss: 2.3098 - val_accuracy: 0.5625
Epoch 93/100
3/3 [==============================] - 0s 13ms/step - loss: 2.3172 - accuracy: 0.6164 - val_loss: 2.3094 - val_accuracy: 0.5625
Epoch 94/100
3/3 [==============================] - 0s 14ms/step - loss: 2.3158 - accuracy: 0.6049 - val_loss: 2.3090 - val_accuracy: 0.5625
Epoch 95/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3341 - accuracy: 0.5984 - val_loss: 2.3086 - val_accuracy: 0.5625
Epoch 96/100
3/3 [==============================] - 0s 16ms/step - loss: 2.3457 - accuracy: 0.5803 - val_loss: 2.3082 - val_accuracy: 0.5625
Epoch 97/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3320 - accuracy: 0.5836 - val_loss: 2.3078 - val_accuracy: 0.5625
Epoch 98/100
3/3 [==============================] - 0s 24ms/step - loss: 2.2928 - accuracy: 0.6180 - val_loss: 2.3074 - val_accuracy: 0.5625
Epoch 99/100
3/3 [==============================] - 0s 29ms/step - loss: 2.2994 - accuracy: 0.5869 - val_loss: 2.3070 - val_accuracy: 0.5625
Epoch 100/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3134 - accuracy: 0.5951 - val_loss: 2.3065 - val_accuracy: 0.5625
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 0s/step
Experiment number: 8
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 230ms/step - loss: 1.5516 - accuracy: 0.4926 - val_loss: 1.2101 - val_accuracy: 0.7639
Epoch 2/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1765 - accuracy: 0.7570 - val_loss: 0.9689 - val_accuracy: 0.8164
Epoch 3/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9149 - accuracy: 0.8604 - val_loss: 1.0085 - val_accuracy: 0.8164
Epoch 4/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9031 - accuracy: 0.8670 - val_loss: 1.0777 - val_accuracy: 0.8164
Epoch 5/100
2/2 [==============================] - 0s 30ms/step - loss: 0.9164 - accuracy: 0.8670 - val_loss: 1.0872 - val_accuracy: 0.8164
Epoch 6/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8989 - accuracy: 0.8670 - val_loss: 1.0438 - val_accuracy: 0.8164
Epoch 7/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8768 - accuracy: 0.8670 - val_loss: 0.9847 - val_accuracy: 0.8164
Epoch 8/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7877 - accuracy: 0.8670 - val_loss: 0.9354 - val_accuracy: 0.8164
Epoch 9/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7149 - accuracy: 0.8670 - val_loss: 0.9056 - val_accuracy: 0.8164
Epoch 10/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6905 - accuracy: 0.8670 - val_loss: 0.8857 - val_accuracy: 0.8164
Epoch 11/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6728 - accuracy: 0.8670 - val_loss: 0.8718 - val_accuracy: 0.8164
Epoch 12/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6769 - accuracy: 0.8670 - val_loss: 0.8577 - val_accuracy: 0.8164
Epoch 13/100
2/2 [==============================] - 0s 46ms/step - loss: 0.6678 - accuracy: 0.8654 - val_loss: 0.8460 - val_accuracy: 0.8164
Epoch 14/100
2/2 [==============================] - 0s 30ms/step - loss: 0.6861 - accuracy: 0.8637 - val_loss: 0.8469 - val_accuracy: 0.8164
Epoch 15/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7015 - accuracy: 0.8506 - val_loss: 0.8666 - val_accuracy: 0.8230
Epoch 16/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7682 - accuracy: 0.8325 - val_loss: 0.8967 - val_accuracy: 0.8230
Epoch 17/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8064 - accuracy: 0.8161 - val_loss: 0.9250 - val_accuracy: 0.8197
Epoch 18/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8036 - accuracy: 0.8292 - val_loss: 0.9393 - val_accuracy: 0.8492
Epoch 19/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8008 - accuracy: 0.8473 - val_loss: 0.9737 - val_accuracy: 0.8361
Epoch 20/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8106 - accuracy: 0.8686 - val_loss: 1.0208 - val_accuracy: 0.8164
Epoch 21/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8233 - accuracy: 0.8654 - val_loss: 1.0576 - val_accuracy: 0.8197
Epoch 22/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8405 - accuracy: 0.8686 - val_loss: 1.0715 - val_accuracy: 0.8164
Epoch 23/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8152 - accuracy: 0.8637 - val_loss: 1.0763 - val_accuracy: 0.8131
Epoch 24/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8423 - accuracy: 0.8621 - val_loss: 1.0840 - val_accuracy: 0.8131
Epoch 25/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8319 - accuracy: 0.8571 - val_loss: 1.0839 - val_accuracy: 0.8098
Epoch 26/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8460 - accuracy: 0.8506 - val_loss: 1.0779 - val_accuracy: 0.8098
Epoch 27/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8515 - accuracy: 0.8522 - val_loss: 1.0637 - val_accuracy: 0.8197
Epoch 28/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8561 - accuracy: 0.8571 - val_loss: 1.0341 - val_accuracy: 0.8197
Epoch 29/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8239 - accuracy: 0.8654 - val_loss: 1.0055 - val_accuracy: 0.8361
Epoch 30/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8087 - accuracy: 0.8588 - val_loss: 0.9954 - val_accuracy: 0.8197
Epoch 31/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7750 - accuracy: 0.8555 - val_loss: 0.9981 - val_accuracy: 0.8164
Epoch 32/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8007 - accuracy: 0.8637 - val_loss: 1.0081 - val_accuracy: 0.8098
Epoch 33/100
2/2 [==============================] - 0s 28ms/step - loss: 0.7556 - accuracy: 0.8654 - val_loss: 1.0133 - val_accuracy: 0.8131
Epoch 34/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7542 - accuracy: 0.8719 - val_loss: 0.9810 - val_accuracy: 0.8164
Epoch 35/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7425 - accuracy: 0.8604 - val_loss: 0.9138 - val_accuracy: 0.8164
Epoch 36/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7154 - accuracy: 0.8604 - val_loss: 0.8827 - val_accuracy: 0.8164
Epoch 37/100
2/2 [==============================] - 0s 49ms/step - loss: 0.7080 - accuracy: 0.8670 - val_loss: 0.8640 - val_accuracy: 0.8164
Epoch 38/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6958 - accuracy: 0.8686 - val_loss: 0.8536 - val_accuracy: 0.8164
Epoch 39/100
2/2 [==============================] - 0s 28ms/step - loss: 0.6962 - accuracy: 0.8670 - val_loss: 0.8443 - val_accuracy: 0.8164
Epoch 40/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7105 - accuracy: 0.8670 - val_loss: 0.8468 - val_accuracy: 0.8164
Epoch 41/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7205 - accuracy: 0.8670 - val_loss: 0.8455 - val_accuracy: 0.8164
Epoch 42/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7241 - accuracy: 0.8670 - val_loss: 0.8394 - val_accuracy: 0.8164
Epoch 43/100
2/2 [==============================] - 0s 49ms/step - loss: 0.7206 - accuracy: 0.8670 - val_loss: 0.8330 - val_accuracy: 0.8164
Epoch 44/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7199 - accuracy: 0.8670 - val_loss: 0.8281 - val_accuracy: 0.8164
Epoch 45/100
2/2 [==============================] - 0s 27ms/step - loss: 0.7217 - accuracy: 0.8670 - val_loss: 0.8206 - val_accuracy: 0.8164
Epoch 46/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7068 - accuracy: 0.8670 - val_loss: 0.8202 - val_accuracy: 0.8164
Epoch 47/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7113 - accuracy: 0.8670 - val_loss: 0.8257 - val_accuracy: 0.8164
Epoch 48/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7155 - accuracy: 0.8670 - val_loss: 0.8286 - val_accuracy: 0.8164
Epoch 49/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7182 - accuracy: 0.8670 - val_loss: 0.8252 - val_accuracy: 0.8164
Epoch 50/100
2/2 [==============================] - 0s 49ms/step - loss: 0.7061 - accuracy: 0.8670 - val_loss: 0.8180 - val_accuracy: 0.8164
Epoch 51/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7094 - accuracy: 0.8670 - val_loss: 0.8121 - val_accuracy: 0.8164
Epoch 52/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6975 - accuracy: 0.8670 - val_loss: 0.8040 - val_accuracy: 0.8164
Epoch 53/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6882 - accuracy: 0.8670 - val_loss: 0.7928 - val_accuracy: 0.8164
Epoch 54/100
2/2 [==============================] - 0s 51ms/step - loss: 0.6750 - accuracy: 0.8670 - val_loss: 0.7797 - val_accuracy: 0.8164
Epoch 55/100
2/2 [==============================] - 0s 52ms/step - loss: 0.6860 - accuracy: 0.8670 - val_loss: 0.7643 - val_accuracy: 0.8164
Epoch 56/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6748 - accuracy: 0.8670 - val_loss: 0.7464 - val_accuracy: 0.8164
Epoch 57/100
2/2 [==============================] - 0s 45ms/step - loss: 0.6653 - accuracy: 0.8670 - val_loss: 0.7375 - val_accuracy: 0.8164
Epoch 58/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6569 - accuracy: 0.8670 - val_loss: 0.7369 - val_accuracy: 0.8164
Epoch 59/100
2/2 [==============================] - 0s 52ms/step - loss: 0.6443 - accuracy: 0.8670 - val_loss: 0.7386 - val_accuracy: 0.8164
Epoch 60/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6480 - accuracy: 0.8670 - val_loss: 0.7420 - val_accuracy: 0.8164
Epoch 61/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6380 - accuracy: 0.8670 - val_loss: 0.7471 - val_accuracy: 0.8164
Epoch 62/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6325 - accuracy: 0.8670 - val_loss: 0.7561 - val_accuracy: 0.8164
Epoch 63/100
2/2 [==============================] - 0s 27ms/step - loss: 0.6277 - accuracy: 0.8670 - val_loss: 0.7643 - val_accuracy: 0.8164
Epoch 64/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6134 - accuracy: 0.8670 - val_loss: 0.7734 - val_accuracy: 0.8164
Epoch 65/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6116 - accuracy: 0.8670 - val_loss: 0.7866 - val_accuracy: 0.8164
Epoch 66/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6249 - accuracy: 0.8670 - val_loss: 0.7970 - val_accuracy: 0.8164
Epoch 67/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6169 - accuracy: 0.8686 - val_loss: 0.8034 - val_accuracy: 0.8164
Epoch 68/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6162 - accuracy: 0.8686 - val_loss: 0.7968 - val_accuracy: 0.8164
Epoch 69/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6239 - accuracy: 0.8670 - val_loss: 0.7819 - val_accuracy: 0.8164
Epoch 70/100
2/2 [==============================] - 0s 51ms/step - loss: 0.5979 - accuracy: 0.8670 - val_loss: 0.7608 - val_accuracy: 0.8164
Epoch 71/100
2/2 [==============================] - 0s 24ms/step - loss: 0.6064 - accuracy: 0.8670 - val_loss: 0.7334 - val_accuracy: 0.8164
Epoch 72/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5851 - accuracy: 0.8654 - val_loss: 0.7081 - val_accuracy: 0.8164
Epoch 73/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5974 - accuracy: 0.8670 - val_loss: 0.6972 - val_accuracy: 0.8164
Epoch 74/100
2/2 [==============================] - 0s 48ms/step - loss: 0.5710 - accuracy: 0.8686 - val_loss: 0.7008 - val_accuracy: 0.8164
Epoch 75/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5733 - accuracy: 0.8686 - val_loss: 0.7051 - val_accuracy: 0.8164
Epoch 76/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5790 - accuracy: 0.8670 - val_loss: 0.7084 - val_accuracy: 0.8164
Epoch 77/100
2/2 [==============================] - 0s 52ms/step - loss: 0.6034 - accuracy: 0.8654 - val_loss: 0.7082 - val_accuracy: 0.8164
Epoch 78/100
2/2 [==============================] - 0s 25ms/step - loss: 0.5706 - accuracy: 0.8670 - val_loss: 0.7105 - val_accuracy: 0.8164
Epoch 79/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5980 - accuracy: 0.8670 - val_loss: 0.7116 - val_accuracy: 0.8164
Epoch 80/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5928 - accuracy: 0.8670 - val_loss: 0.7149 - val_accuracy: 0.8164
Epoch 81/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5879 - accuracy: 0.8670 - val_loss: 0.7182 - val_accuracy: 0.8164
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5963 - accuracy: 0.8670 - val_loss: 0.7071 - val_accuracy: 0.8164
Epoch 83/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5893 - accuracy: 0.8670 - val_loss: 0.6927 - val_accuracy: 0.8164
Epoch 84/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5892 - accuracy: 0.8670 - val_loss: 0.6871 - val_accuracy: 0.8164
Epoch 85/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5997 - accuracy: 0.8670 - val_loss: 0.6830 - val_accuracy: 0.8164
Epoch 86/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5778 - accuracy: 0.8670 - val_loss: 0.6863 - val_accuracy: 0.8164
Epoch 87/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5640 - accuracy: 0.8670 - val_loss: 0.6975 - val_accuracy: 0.8164
Epoch 88/100
2/2 [==============================] - 0s 53ms/step - loss: 0.5588 - accuracy: 0.8670 - val_loss: 0.7056 - val_accuracy: 0.8164
Epoch 89/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5703 - accuracy: 0.8686 - val_loss: 0.7018 - val_accuracy: 0.8164
Epoch 90/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6006 - accuracy: 0.8686 - val_loss: 0.6889 - val_accuracy: 0.8164
Epoch 91/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5779 - accuracy: 0.8670 - val_loss: 0.6738 - val_accuracy: 0.8164
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5902 - accuracy: 0.8670 - val_loss: 0.6650 - val_accuracy: 0.8164
Epoch 93/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5926 - accuracy: 0.8670 - val_loss: 0.6582 - val_accuracy: 0.8164
Epoch 94/100
2/2 [==============================] - 0s 51ms/step - loss: 0.5443 - accuracy: 0.8686 - val_loss: 0.6556 - val_accuracy: 0.8164
Epoch 95/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5735 - accuracy: 0.8686 - val_loss: 0.6529 - val_accuracy: 0.8164
Epoch 96/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5708 - accuracy: 0.8670 - val_loss: 0.6505 - val_accuracy: 0.8164
Epoch 97/100
2/2 [==============================] - 0s 69ms/step - loss: 0.5669 - accuracy: 0.8670 - val_loss: 0.6510 - val_accuracy: 0.8164
Epoch 98/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5939 - accuracy: 0.8670 - val_loss: 0.6505 - val_accuracy: 0.8164
Epoch 99/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5555 - accuracy: 0.8670 - val_loss: 0.6437 - val_accuracy: 0.8164
Epoch 100/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5790 - accuracy: 0.8670 - val_loss: 0.6341 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 227ms/step - loss: 1.4326 - accuracy: 0.5402 - val_loss: 1.1556 - val_accuracy: 0.7902
Epoch 2/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2075 - accuracy: 0.7619 - val_loss: 0.9306 - val_accuracy: 0.8689
Epoch 3/100
2/2 [==============================] - 0s 52ms/step - loss: 0.9798 - accuracy: 0.8342 - val_loss: 0.8095 - val_accuracy: 0.8754
Epoch 4/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8605 - accuracy: 0.8407 - val_loss: 0.7397 - val_accuracy: 0.8721
Epoch 5/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8149 - accuracy: 0.8407 - val_loss: 0.6908 - val_accuracy: 0.8721
Epoch 6/100
2/2 [==============================] - 0s 31ms/step - loss: 0.7855 - accuracy: 0.8391 - val_loss: 0.6525 - val_accuracy: 0.8721
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7478 - accuracy: 0.8391 - val_loss: 0.6211 - val_accuracy: 0.8754
Epoch 8/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7323 - accuracy: 0.8407 - val_loss: 0.5944 - val_accuracy: 0.8984
Epoch 9/100
2/2 [==============================] - 0s 49ms/step - loss: 0.7115 - accuracy: 0.8604 - val_loss: 0.5810 - val_accuracy: 0.8852
Epoch 10/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7077 - accuracy: 0.8456 - val_loss: 0.5844 - val_accuracy: 0.8656
Epoch 11/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7640 - accuracy: 0.8292 - val_loss: 0.5892 - val_accuracy: 0.8590
Epoch 12/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7483 - accuracy: 0.8128 - val_loss: 0.5843 - val_accuracy: 0.8885
Epoch 13/100
2/2 [==============================] - 0s 51ms/step - loss: 0.7298 - accuracy: 0.8259 - val_loss: 0.5892 - val_accuracy: 0.8754
Epoch 14/100
2/2 [==============================] - 0s 25ms/step - loss: 0.7302 - accuracy: 0.8654 - val_loss: 0.6132 - val_accuracy: 0.8721
Epoch 15/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7572 - accuracy: 0.8424 - val_loss: 0.6359 - val_accuracy: 0.8721
Epoch 16/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7919 - accuracy: 0.8358 - val_loss: 0.6520 - val_accuracy: 0.8721
Epoch 17/100
2/2 [==============================] - 0s 36ms/step - loss: 0.8288 - accuracy: 0.8259 - val_loss: 0.6407 - val_accuracy: 0.8852
Epoch 18/100
2/2 [==============================] - 0s 48ms/step - loss: 0.7840 - accuracy: 0.8391 - val_loss: 0.6232 - val_accuracy: 0.8951
Epoch 19/100
2/2 [==============================] - 0s 23ms/step - loss: 0.7634 - accuracy: 0.8555 - val_loss: 0.6258 - val_accuracy: 0.8984
Epoch 20/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8206 - accuracy: 0.8374 - val_loss: 0.6433 - val_accuracy: 0.8951
Epoch 21/100
2/2 [==============================] - 0s 31ms/step - loss: 0.8213 - accuracy: 0.8391 - val_loss: 0.6569 - val_accuracy: 0.8721
Epoch 22/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8068 - accuracy: 0.8407 - val_loss: 0.6725 - val_accuracy: 0.8689
Epoch 23/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8130 - accuracy: 0.8473 - val_loss: 0.6777 - val_accuracy: 0.8918
Epoch 24/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8156 - accuracy: 0.8292 - val_loss: 0.6979 - val_accuracy: 0.8787
Epoch 25/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8504 - accuracy: 0.8144 - val_loss: 0.7089 - val_accuracy: 0.8820
Epoch 26/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8195 - accuracy: 0.8243 - val_loss: 0.6926 - val_accuracy: 0.8951
Epoch 27/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7701 - accuracy: 0.8555 - val_loss: 0.6949 - val_accuracy: 0.8787
Epoch 28/100
2/2 [==============================] - 0s 48ms/step - loss: 0.7552 - accuracy: 0.8539 - val_loss: 0.7169 - val_accuracy: 0.8754
Epoch 29/100
2/2 [==============================] - 0s 28ms/step - loss: 0.7787 - accuracy: 0.8440 - val_loss: 0.7295 - val_accuracy: 0.8721
Epoch 30/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7853 - accuracy: 0.8374 - val_loss: 0.7291 - val_accuracy: 0.8721
Epoch 31/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7597 - accuracy: 0.8424 - val_loss: 0.7224 - val_accuracy: 0.8590
Epoch 32/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7683 - accuracy: 0.8407 - val_loss: 0.7173 - val_accuracy: 0.8656
Epoch 33/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7928 - accuracy: 0.8456 - val_loss: 0.7009 - val_accuracy: 0.8689
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8073 - accuracy: 0.8424 - val_loss: 0.6829 - val_accuracy: 0.8754
Epoch 35/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7949 - accuracy: 0.8391 - val_loss: 0.6707 - val_accuracy: 0.8820
Epoch 36/100
2/2 [==============================] - 0s 51ms/step - loss: 0.8011 - accuracy: 0.8391 - val_loss: 0.6673 - val_accuracy: 0.8754
Epoch 37/100
2/2 [==============================] - 0s 30ms/step - loss: 0.8066 - accuracy: 0.8473 - val_loss: 0.6620 - val_accuracy: 0.8787
Epoch 38/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7942 - accuracy: 0.8440 - val_loss: 0.6495 - val_accuracy: 0.8852
Epoch 39/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7701 - accuracy: 0.8506 - val_loss: 0.6324 - val_accuracy: 0.8852
Epoch 40/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7441 - accuracy: 0.8522 - val_loss: 0.6219 - val_accuracy: 0.8885
Epoch 41/100
2/2 [==============================] - 0s 52ms/step - loss: 0.7515 - accuracy: 0.8407 - val_loss: 0.6140 - val_accuracy: 0.8852
Epoch 42/100
2/2 [==============================] - 0s 26ms/step - loss: 0.7205 - accuracy: 0.8522 - val_loss: 0.6130 - val_accuracy: 0.8852
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7261 - accuracy: 0.8604 - val_loss: 0.6117 - val_accuracy: 0.8852
Epoch 44/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7292 - accuracy: 0.8456 - val_loss: 0.6086 - val_accuracy: 0.8951
Epoch 45/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7228 - accuracy: 0.8456 - val_loss: 0.6062 - val_accuracy: 0.8885
Epoch 46/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7014 - accuracy: 0.8555 - val_loss: 0.6060 - val_accuracy: 0.8820
Epoch 47/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6889 - accuracy: 0.8522 - val_loss: 0.6065 - val_accuracy: 0.8754
Epoch 48/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7119 - accuracy: 0.8276 - val_loss: 0.6001 - val_accuracy: 0.8754
Epoch 49/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6727 - accuracy: 0.8391 - val_loss: 0.5920 - val_accuracy: 0.8754
Epoch 50/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6861 - accuracy: 0.8358 - val_loss: 0.5795 - val_accuracy: 0.8754
Epoch 51/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6937 - accuracy: 0.8374 - val_loss: 0.5665 - val_accuracy: 0.8754
Epoch 52/100
2/2 [==============================] - 0s 29ms/step - loss: 0.6508 - accuracy: 0.8391 - val_loss: 0.5574 - val_accuracy: 0.8787
Epoch 53/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6897 - accuracy: 0.8374 - val_loss: 0.5482 - val_accuracy: 0.8689
Epoch 54/100
2/2 [==============================] - 0s 53ms/step - loss: 0.6364 - accuracy: 0.8407 - val_loss: 0.5471 - val_accuracy: 0.8689
Epoch 55/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6637 - accuracy: 0.8456 - val_loss: 0.5502 - val_accuracy: 0.8656
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6536 - accuracy: 0.8456 - val_loss: 0.5556 - val_accuracy: 0.8656
Epoch 57/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6757 - accuracy: 0.8440 - val_loss: 0.5635 - val_accuracy: 0.8656
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6666 - accuracy: 0.8456 - val_loss: 0.5690 - val_accuracy: 0.8787
Epoch 59/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6665 - accuracy: 0.8539 - val_loss: 0.5733 - val_accuracy: 0.8820
Epoch 60/100
2/2 [==============================] - 0s 44ms/step - loss: 0.6734 - accuracy: 0.8506 - val_loss: 0.5737 - val_accuracy: 0.8852
Epoch 61/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6782 - accuracy: 0.8424 - val_loss: 0.5718 - val_accuracy: 0.8689
Epoch 62/100
2/2 [==============================] - 0s 53ms/step - loss: 0.7120 - accuracy: 0.8489 - val_loss: 0.5648 - val_accuracy: 0.8721
Epoch 63/100
2/2 [==============================] - 0s 45ms/step - loss: 0.6909 - accuracy: 0.8391 - val_loss: 0.5558 - val_accuracy: 0.8852
Epoch 64/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6731 - accuracy: 0.8456 - val_loss: 0.5459 - val_accuracy: 0.8721
Epoch 65/100
2/2 [==============================] - 0s 40ms/step - loss: 0.6581 - accuracy: 0.8440 - val_loss: 0.5348 - val_accuracy: 0.8754
Epoch 66/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6596 - accuracy: 0.8489 - val_loss: 0.5185 - val_accuracy: 0.8820
Epoch 67/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6417 - accuracy: 0.8424 - val_loss: 0.5079 - val_accuracy: 0.8885
Epoch 68/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6231 - accuracy: 0.8424 - val_loss: 0.5008 - val_accuracy: 0.8885
Epoch 69/100
2/2 [==============================] - 0s 51ms/step - loss: 0.6165 - accuracy: 0.8440 - val_loss: 0.5005 - val_accuracy: 0.8852
Epoch 70/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6163 - accuracy: 0.8440 - val_loss: 0.4988 - val_accuracy: 0.8787
Epoch 71/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6217 - accuracy: 0.8374 - val_loss: 0.4936 - val_accuracy: 0.8689
Epoch 72/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5907 - accuracy: 0.8325 - val_loss: 0.4860 - val_accuracy: 0.8721
Epoch 73/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5973 - accuracy: 0.8391 - val_loss: 0.4834 - val_accuracy: 0.8754
Epoch 74/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6077 - accuracy: 0.8374 - val_loss: 0.4922 - val_accuracy: 0.8754
Epoch 75/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5937 - accuracy: 0.8342 - val_loss: 0.5090 - val_accuracy: 0.8754
Epoch 76/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6064 - accuracy: 0.8407 - val_loss: 0.5162 - val_accuracy: 0.8754
Epoch 77/100
2/2 [==============================] - 0s 45ms/step - loss: 0.6178 - accuracy: 0.8374 - val_loss: 0.5165 - val_accuracy: 0.8721
Epoch 78/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6065 - accuracy: 0.8391 - val_loss: 0.5229 - val_accuracy: 0.8689
Epoch 79/100
2/2 [==============================] - 0s 28ms/step - loss: 0.6362 - accuracy: 0.8374 - val_loss: 0.5342 - val_accuracy: 0.8689
Epoch 80/100
2/2 [==============================] - 0s 42ms/step - loss: 0.6320 - accuracy: 0.8374 - val_loss: 0.5403 - val_accuracy: 0.8689
Epoch 81/100
2/2 [==============================] - 0s 30ms/step - loss: 0.6591 - accuracy: 0.8391 - val_loss: 0.5411 - val_accuracy: 0.8689
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6376 - accuracy: 0.8391 - val_loss: 0.5382 - val_accuracy: 0.8689
Epoch 83/100
2/2 [==============================] - 0s 22ms/step - loss: 0.6287 - accuracy: 0.8440 - val_loss: 0.5343 - val_accuracy: 0.8689
Epoch 84/100
2/2 [==============================] - 0s 29ms/step - loss: 0.6243 - accuracy: 0.8391 - val_loss: 0.5287 - val_accuracy: 0.8721
Epoch 85/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6250 - accuracy: 0.8407 - val_loss: 0.5229 - val_accuracy: 0.8721
Epoch 86/100
2/2 [==============================] - 0s 51ms/step - loss: 0.6147 - accuracy: 0.8374 - val_loss: 0.5169 - val_accuracy: 0.8721
Epoch 87/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6157 - accuracy: 0.8391 - val_loss: 0.5122 - val_accuracy: 0.8721
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6294 - accuracy: 0.8342 - val_loss: 0.5096 - val_accuracy: 0.8721
Epoch 89/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6054 - accuracy: 0.8358 - val_loss: 0.5084 - val_accuracy: 0.8721
Epoch 90/100
2/2 [==============================] - 0s 47ms/step - loss: 0.6173 - accuracy: 0.8424 - val_loss: 0.5083 - val_accuracy: 0.8721
Epoch 91/100
2/2 [==============================] - 0s 29ms/step - loss: 0.5957 - accuracy: 0.8424 - val_loss: 0.5066 - val_accuracy: 0.8787
Epoch 92/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5908 - accuracy: 0.8489 - val_loss: 0.5035 - val_accuracy: 0.8820
Epoch 93/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6115 - accuracy: 0.8407 - val_loss: 0.5008 - val_accuracy: 0.8852
Epoch 94/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6025 - accuracy: 0.8456 - val_loss: 0.4991 - val_accuracy: 0.8918
Epoch 95/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6120 - accuracy: 0.8473 - val_loss: 0.4965 - val_accuracy: 0.8885
Epoch 96/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5935 - accuracy: 0.8440 - val_loss: 0.4954 - val_accuracy: 0.8918
Epoch 97/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6205 - accuracy: 0.8456 - val_loss: 0.4911 - val_accuracy: 0.8852
Epoch 98/100
2/2 [==============================] - 0s 50ms/step - loss: 0.5896 - accuracy: 0.8522 - val_loss: 0.4832 - val_accuracy: 0.8885
Epoch 99/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5920 - accuracy: 0.8424 - val_loss: 0.4717 - val_accuracy: 0.8918
Epoch 100/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5958 - accuracy: 0.8424 - val_loss: 0.4591 - val_accuracy: 0.8852
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 219ms/step - loss: 1.2364 - accuracy: 0.6639 - val_loss: 1.0876 - val_accuracy: 0.7664
Epoch 2/100
2/2 [==============================] - 0s 50ms/step - loss: 1.0695 - accuracy: 0.7918 - val_loss: 0.9088 - val_accuracy: 0.8520
Epoch 3/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8983 - accuracy: 0.8508 - val_loss: 0.8310 - val_accuracy: 0.8750
Epoch 4/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8020 - accuracy: 0.8574 - val_loss: 0.8082 - val_accuracy: 0.8684
Epoch 5/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7565 - accuracy: 0.8525 - val_loss: 0.8015 - val_accuracy: 0.8717
Epoch 6/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7205 - accuracy: 0.8705 - val_loss: 0.8014 - val_accuracy: 0.8454
Epoch 7/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7147 - accuracy: 0.8492 - val_loss: 0.8011 - val_accuracy: 0.8257
Epoch 8/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6751 - accuracy: 0.8525 - val_loss: 0.8020 - val_accuracy: 0.8355
Epoch 9/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6593 - accuracy: 0.8607 - val_loss: 0.7935 - val_accuracy: 0.8322
Epoch 10/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6535 - accuracy: 0.8623 - val_loss: 0.7814 - val_accuracy: 0.8355
Epoch 11/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6395 - accuracy: 0.8705 - val_loss: 0.7777 - val_accuracy: 0.8289
Epoch 12/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6424 - accuracy: 0.8689 - val_loss: 0.7709 - val_accuracy: 0.8322
Epoch 13/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6294 - accuracy: 0.8672 - val_loss: 0.7698 - val_accuracy: 0.8487
Epoch 14/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6684 - accuracy: 0.8639 - val_loss: 0.7708 - val_accuracy: 0.8421
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6667 - accuracy: 0.8689 - val_loss: 0.7746 - val_accuracy: 0.8388
Epoch 16/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6740 - accuracy: 0.8607 - val_loss: 0.7889 - val_accuracy: 0.8289
Epoch 17/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7012 - accuracy: 0.8426 - val_loss: 0.8013 - val_accuracy: 0.8125
Epoch 18/100
2/2 [==============================] - 0s 37ms/step - loss: 0.6852 - accuracy: 0.8574 - val_loss: 0.7901 - val_accuracy: 0.8158
Epoch 19/100
2/2 [==============================] - 0s 39ms/step - loss: 0.6988 - accuracy: 0.8639 - val_loss: 0.7838 - val_accuracy: 0.8289
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6971 - accuracy: 0.8623 - val_loss: 0.7929 - val_accuracy: 0.8421
Epoch 21/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7060 - accuracy: 0.8639 - val_loss: 0.7988 - val_accuracy: 0.8355
Epoch 22/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7162 - accuracy: 0.8541 - val_loss: 0.7953 - val_accuracy: 0.8388
Epoch 23/100
2/2 [==============================] - 0s 47ms/step - loss: 0.7170 - accuracy: 0.8705 - val_loss: 0.7770 - val_accuracy: 0.8454
Epoch 24/100
2/2 [==============================] - 0s 25ms/step - loss: 0.7035 - accuracy: 0.8623 - val_loss: 0.7584 - val_accuracy: 0.8553
Epoch 25/100
2/2 [==============================] - 0s 30ms/step - loss: 0.6845 - accuracy: 0.8787 - val_loss: 0.7567 - val_accuracy: 0.8388
Epoch 26/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6833 - accuracy: 0.8787 - val_loss: 0.7615 - val_accuracy: 0.8421
Epoch 27/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6795 - accuracy: 0.8607 - val_loss: 0.7498 - val_accuracy: 0.8454
Epoch 28/100
2/2 [==============================] - 0s 27ms/step - loss: 0.6460 - accuracy: 0.8836 - val_loss: 0.7531 - val_accuracy: 0.8388
Epoch 29/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6745 - accuracy: 0.8689 - val_loss: 0.7691 - val_accuracy: 0.8487
Epoch 30/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6548 - accuracy: 0.8836 - val_loss: 0.7813 - val_accuracy: 0.8454
Epoch 31/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6746 - accuracy: 0.8705 - val_loss: 0.7920 - val_accuracy: 0.8487
Epoch 32/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6814 - accuracy: 0.8689 - val_loss: 0.7990 - val_accuracy: 0.8454
Epoch 33/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7016 - accuracy: 0.8656 - val_loss: 0.7901 - val_accuracy: 0.8487
Epoch 34/100
2/2 [==============================] - 0s 48ms/step - loss: 0.6742 - accuracy: 0.8656 - val_loss: 0.7659 - val_accuracy: 0.8421
Epoch 35/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6561 - accuracy: 0.8754 - val_loss: 0.7512 - val_accuracy: 0.8520
Epoch 36/100
2/2 [==============================] - 0s 32ms/step - loss: 0.6592 - accuracy: 0.8721 - val_loss: 0.7508 - val_accuracy: 0.8520
Epoch 37/100
2/2 [==============================] - 0s 33ms/step - loss: 0.6704 - accuracy: 0.8607 - val_loss: 0.7460 - val_accuracy: 0.8586
Epoch 38/100
2/2 [==============================] - 0s 38ms/step - loss: 0.6623 - accuracy: 0.8738 - val_loss: 0.7427 - val_accuracy: 0.8520
Epoch 39/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6603 - accuracy: 0.8639 - val_loss: 0.7548 - val_accuracy: 0.8388
Epoch 40/100
2/2 [==============================] - 0s 51ms/step - loss: 0.6760 - accuracy: 0.8639 - val_loss: 0.7639 - val_accuracy: 0.8289
Epoch 41/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6655 - accuracy: 0.8705 - val_loss: 0.7474 - val_accuracy: 0.8454
Epoch 42/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6511 - accuracy: 0.8689 - val_loss: 0.7202 - val_accuracy: 0.8651
Epoch 43/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6544 - accuracy: 0.8656 - val_loss: 0.7109 - val_accuracy: 0.8586
Epoch 44/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6510 - accuracy: 0.8623 - val_loss: 0.7113 - val_accuracy: 0.8586
Epoch 45/100
2/2 [==============================] - 0s 35ms/step - loss: 0.6566 - accuracy: 0.8574 - val_loss: 0.7005 - val_accuracy: 0.8586
Epoch 46/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6511 - accuracy: 0.8590 - val_loss: 0.6937 - val_accuracy: 0.8520
Epoch 47/100
2/2 [==============================] - 0s 51ms/step - loss: 0.6402 - accuracy: 0.8639 - val_loss: 0.7075 - val_accuracy: 0.8388
Epoch 48/100
2/2 [==============================] - 0s 51ms/step - loss: 0.6429 - accuracy: 0.8607 - val_loss: 0.7204 - val_accuracy: 0.8388
Epoch 49/100
2/2 [==============================] - 0s 46ms/step - loss: 0.6363 - accuracy: 0.8672 - val_loss: 0.7108 - val_accuracy: 0.8191
Epoch 50/100
2/2 [==============================] - 0s 50ms/step - loss: 0.6038 - accuracy: 0.8787 - val_loss: 0.6905 - val_accuracy: 0.8388
Epoch 51/100
2/2 [==============================] - 0s 49ms/step - loss: 0.6186 - accuracy: 0.8705 - val_loss: 0.6670 - val_accuracy: 0.8454
Epoch 52/100
2/2 [==============================] - 0s 50ms/step - loss: 0.5822 - accuracy: 0.8803 - val_loss: 0.6591 - val_accuracy: 0.8421
Epoch 53/100
2/2 [==============================] - 0s 43ms/step - loss: 0.5748 - accuracy: 0.8754 - val_loss: 0.6629 - val_accuracy: 0.8520
Epoch 54/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5891 - accuracy: 0.8639 - val_loss: 0.6713 - val_accuracy: 0.8520
Epoch 55/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5912 - accuracy: 0.8721 - val_loss: 0.6817 - val_accuracy: 0.8388
Epoch 56/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5816 - accuracy: 0.8738 - val_loss: 0.6972 - val_accuracy: 0.8257
Epoch 57/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5895 - accuracy: 0.8721 - val_loss: 0.7179 - val_accuracy: 0.8322
Epoch 58/100
2/2 [==============================] - 0s 47ms/step - loss: 0.5990 - accuracy: 0.8787 - val_loss: 0.7286 - val_accuracy: 0.8289
Epoch 59/100
2/2 [==============================] - 0s 31ms/step - loss: 0.6082 - accuracy: 0.8820 - val_loss: 0.7250 - val_accuracy: 0.8191
Epoch 60/100
2/2 [==============================] - 0s 30ms/step - loss: 0.5931 - accuracy: 0.8770 - val_loss: 0.7207 - val_accuracy: 0.8224
Epoch 61/100
2/2 [==============================] - 0s 36ms/step - loss: 0.6020 - accuracy: 0.8705 - val_loss: 0.7216 - val_accuracy: 0.8257
Epoch 62/100
2/2 [==============================] - 0s 56ms/step - loss: 0.5988 - accuracy: 0.8787 - val_loss: 0.7260 - val_accuracy: 0.8289
Epoch 63/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5961 - accuracy: 0.8607 - val_loss: 0.7221 - val_accuracy: 0.8224
Epoch 64/100
2/2 [==============================] - 0s 26ms/step - loss: 0.5979 - accuracy: 0.8623 - val_loss: 0.7132 - val_accuracy: 0.8224
Epoch 65/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5864 - accuracy: 0.8787 - val_loss: 0.7000 - val_accuracy: 0.8257
Epoch 66/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5711 - accuracy: 0.8705 - val_loss: 0.6855 - val_accuracy: 0.8257
Epoch 67/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5789 - accuracy: 0.8689 - val_loss: 0.6710 - val_accuracy: 0.8289
Epoch 68/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5795 - accuracy: 0.8623 - val_loss: 0.6546 - val_accuracy: 0.8388
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5966 - accuracy: 0.8574 - val_loss: 0.6378 - val_accuracy: 0.8421
Epoch 70/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5644 - accuracy: 0.8672 - val_loss: 0.6242 - val_accuracy: 0.8388
Epoch 71/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5404 - accuracy: 0.8639 - val_loss: 0.6245 - val_accuracy: 0.8322
Epoch 72/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5231 - accuracy: 0.8852 - val_loss: 0.6321 - val_accuracy: 0.8257
Epoch 73/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5362 - accuracy: 0.8754 - val_loss: 0.6357 - val_accuracy: 0.8289
Epoch 74/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5259 - accuracy: 0.8869 - val_loss: 0.6408 - val_accuracy: 0.8322
Epoch 75/100
2/2 [==============================] - 0s 40ms/step - loss: 0.5588 - accuracy: 0.8721 - val_loss: 0.6344 - val_accuracy: 0.8322
Epoch 76/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5463 - accuracy: 0.8705 - val_loss: 0.6177 - val_accuracy: 0.8421
Epoch 77/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5576 - accuracy: 0.8541 - val_loss: 0.6113 - val_accuracy: 0.8553
Epoch 78/100
2/2 [==============================] - 0s 50ms/step - loss: 0.5545 - accuracy: 0.8689 - val_loss: 0.6149 - val_accuracy: 0.8553
Epoch 79/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5686 - accuracy: 0.8623 - val_loss: 0.6175 - val_accuracy: 0.8651
Epoch 80/100
2/2 [==============================] - 0s 30ms/step - loss: 0.5828 - accuracy: 0.8607 - val_loss: 0.6190 - val_accuracy: 0.8618
Epoch 81/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5635 - accuracy: 0.8639 - val_loss: 0.6197 - val_accuracy: 0.8618
Epoch 82/100
2/2 [==============================] - 0s 49ms/step - loss: 0.5557 - accuracy: 0.8639 - val_loss: 0.6252 - val_accuracy: 0.8553
Epoch 83/100
2/2 [==============================] - 0s 29ms/step - loss: 0.5611 - accuracy: 0.8803 - val_loss: 0.6338 - val_accuracy: 0.8355
Epoch 84/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5576 - accuracy: 0.8705 - val_loss: 0.6424 - val_accuracy: 0.8322
Epoch 85/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5497 - accuracy: 0.8721 - val_loss: 0.6399 - val_accuracy: 0.8224
Epoch 86/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5438 - accuracy: 0.8738 - val_loss: 0.6191 - val_accuracy: 0.8355
Epoch 87/100
2/2 [==============================] - 0s 36ms/step - loss: 0.5349 - accuracy: 0.8738 - val_loss: 0.5977 - val_accuracy: 0.8487
Epoch 88/100
2/2 [==============================] - 0s 46ms/step - loss: 0.5191 - accuracy: 0.8754 - val_loss: 0.5845 - val_accuracy: 0.8487
Epoch 89/100
2/2 [==============================] - 0s 56ms/step - loss: 0.5032 - accuracy: 0.8705 - val_loss: 0.5794 - val_accuracy: 0.8520
Epoch 90/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5245 - accuracy: 0.8574 - val_loss: 0.5824 - val_accuracy: 0.8520
Epoch 91/100
2/2 [==============================] - 0s 23ms/step - loss: 0.5240 - accuracy: 0.8492 - val_loss: 0.5911 - val_accuracy: 0.8454
Epoch 92/100
2/2 [==============================] - 0s 31ms/step - loss: 0.5175 - accuracy: 0.8607 - val_loss: 0.6055 - val_accuracy: 0.8454
Epoch 93/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5207 - accuracy: 0.8639 - val_loss: 0.6219 - val_accuracy: 0.8355
Epoch 94/100
2/2 [==============================] - 0s 51ms/step - loss: 0.5293 - accuracy: 0.8738 - val_loss: 0.6366 - val_accuracy: 0.8355
Epoch 95/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5373 - accuracy: 0.8770 - val_loss: 0.6381 - val_accuracy: 0.8355
Epoch 96/100
2/2 [==============================] - 0s 41ms/step - loss: 0.5838 - accuracy: 0.8541 - val_loss: 0.6188 - val_accuracy: 0.8388
Epoch 97/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5112 - accuracy: 0.8869 - val_loss: 0.5986 - val_accuracy: 0.8322
Epoch 98/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5273 - accuracy: 0.8836 - val_loss: 0.5924 - val_accuracy: 0.8388
Epoch 99/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5064 - accuracy: 0.8852 - val_loss: 0.5964 - val_accuracy: 0.8322
Epoch 100/100
2/2 [==============================] - 0s 38ms/step - loss: 0.5001 - accuracy: 0.8869 - val_loss: 0.6138 - val_accuracy: 0.8421
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 9
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 32, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.9, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 64ms/step - loss: 3.4325 - accuracy: 0.3366 - val_loss: 3.3877 - val_accuracy: 0.3770
Epoch 2/100
5/5 [==============================] - 0s 12ms/step - loss: 3.4175 - accuracy: 0.3202 - val_loss: 3.3762 - val_accuracy: 0.3902
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3971 - accuracy: 0.3235 - val_loss: 3.3665 - val_accuracy: 0.4000
Epoch 4/100
5/5 [==============================] - 0s 11ms/step - loss: 3.3856 - accuracy: 0.3235 - val_loss: 3.3570 - val_accuracy: 0.4033
Epoch 5/100
5/5 [==============================] - 0s 11ms/step - loss: 3.3700 - accuracy: 0.3711 - val_loss: 3.3480 - val_accuracy: 0.4230
Epoch 6/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3652 - accuracy: 0.3448 - val_loss: 3.3392 - val_accuracy: 0.4328
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3523 - accuracy: 0.3695 - val_loss: 3.3305 - val_accuracy: 0.4459
Epoch 8/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3455 - accuracy: 0.3744 - val_loss: 3.3216 - val_accuracy: 0.4525
Epoch 9/100
5/5 [==============================] - 0s 10ms/step - loss: 3.3362 - accuracy: 0.3727 - val_loss: 3.3126 - val_accuracy: 0.4623
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3216 - accuracy: 0.4023 - val_loss: 3.3039 - val_accuracy: 0.4623
Epoch 11/100
5/5 [==============================] - 0s 11ms/step - loss: 3.3136 - accuracy: 0.3908 - val_loss: 3.2951 - val_accuracy: 0.4721
Epoch 12/100
5/5 [==============================] - 0s 9ms/step - loss: 3.3127 - accuracy: 0.3711 - val_loss: 3.2863 - val_accuracy: 0.4754
Epoch 13/100
5/5 [==============================] - 0s 8ms/step - loss: 3.2988 - accuracy: 0.3859 - val_loss: 3.2776 - val_accuracy: 0.4820
Epoch 14/100
5/5 [==============================] - 0s 11ms/step - loss: 3.2903 - accuracy: 0.3941 - val_loss: 3.2690 - val_accuracy: 0.4918
Epoch 15/100
5/5 [==============================] - 0s 11ms/step - loss: 3.2666 - accuracy: 0.4433 - val_loss: 3.2602 - val_accuracy: 0.5049
Epoch 16/100
5/5 [==============================] - 0s 8ms/step - loss: 3.2669 - accuracy: 0.3957 - val_loss: 3.2513 - val_accuracy: 0.5148
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2482 - accuracy: 0.4171 - val_loss: 3.2423 - val_accuracy: 0.5311
Epoch 18/100
5/5 [==============================] - 0s 10ms/step - loss: 3.2359 - accuracy: 0.4433 - val_loss: 3.2334 - val_accuracy: 0.5344
Epoch 19/100
5/5 [==============================] - 0s 11ms/step - loss: 3.2303 - accuracy: 0.4122 - val_loss: 3.2243 - val_accuracy: 0.5410
Epoch 20/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2203 - accuracy: 0.4105 - val_loss: 3.2153 - val_accuracy: 0.5410
Epoch 21/100
5/5 [==============================] - 0s 13ms/step - loss: 3.2176 - accuracy: 0.4450 - val_loss: 3.2062 - val_accuracy: 0.5410
Epoch 22/100
5/5 [==============================] - 0s 23ms/step - loss: 3.2037 - accuracy: 0.4368 - val_loss: 3.1972 - val_accuracy: 0.5377
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 3.2027 - accuracy: 0.4187 - val_loss: 3.1881 - val_accuracy: 0.5377
Epoch 24/100
5/5 [==============================] - 0s 13ms/step - loss: 3.1888 - accuracy: 0.4236 - val_loss: 3.1791 - val_accuracy: 0.5377
Epoch 25/100
5/5 [==============================] - 0s 11ms/step - loss: 3.1761 - accuracy: 0.4499 - val_loss: 3.1698 - val_accuracy: 0.5475
Epoch 26/100
5/5 [==============================] - 0s 12ms/step - loss: 3.1744 - accuracy: 0.4581 - val_loss: 3.1605 - val_accuracy: 0.5541
Epoch 27/100
5/5 [==============================] - 0s 9ms/step - loss: 3.1466 - accuracy: 0.5074 - val_loss: 3.1515 - val_accuracy: 0.5639
Epoch 28/100
5/5 [==============================] - 0s 12ms/step - loss: 3.1431 - accuracy: 0.4745 - val_loss: 3.1425 - val_accuracy: 0.5672
Epoch 29/100
5/5 [==============================] - 0s 14ms/step - loss: 3.1379 - accuracy: 0.4696 - val_loss: 3.1332 - val_accuracy: 0.5705
Epoch 30/100
5/5 [==============================] - 0s 9ms/step - loss: 3.1227 - accuracy: 0.4943 - val_loss: 3.1240 - val_accuracy: 0.5738
Epoch 31/100
5/5 [==============================] - 0s 11ms/step - loss: 3.1224 - accuracy: 0.5041 - val_loss: 3.1147 - val_accuracy: 0.5738
Epoch 32/100
5/5 [==============================] - 0s 9ms/step - loss: 3.1057 - accuracy: 0.5041 - val_loss: 3.1054 - val_accuracy: 0.5803
Epoch 33/100
5/5 [==============================] - 0s 9ms/step - loss: 3.0992 - accuracy: 0.4828 - val_loss: 3.0962 - val_accuracy: 0.5869
Epoch 34/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0945 - accuracy: 0.4943 - val_loss: 3.0869 - val_accuracy: 0.5934
Epoch 35/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0830 - accuracy: 0.4877 - val_loss: 3.0777 - val_accuracy: 0.5967
Epoch 36/100
5/5 [==============================] - 0s 8ms/step - loss: 3.0764 - accuracy: 0.5057 - val_loss: 3.0685 - val_accuracy: 0.6066
Epoch 37/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0585 - accuracy: 0.5435 - val_loss: 3.0592 - val_accuracy: 0.6164
Epoch 38/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0498 - accuracy: 0.5287 - val_loss: 3.0499 - val_accuracy: 0.6262
Epoch 39/100
5/5 [==============================] - 0s 14ms/step - loss: 3.0440 - accuracy: 0.5222 - val_loss: 3.0405 - val_accuracy: 0.6262
Epoch 40/100
5/5 [==============================] - 0s 11ms/step - loss: 3.0330 - accuracy: 0.5468 - val_loss: 3.0312 - val_accuracy: 0.6393
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0241 - accuracy: 0.5287 - val_loss: 3.0220 - val_accuracy: 0.6426
Epoch 42/100
5/5 [==============================] - 0s 14ms/step - loss: 3.0202 - accuracy: 0.5172 - val_loss: 3.0128 - val_accuracy: 0.6525
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0131 - accuracy: 0.5320 - val_loss: 3.0035 - val_accuracy: 0.6525
Epoch 44/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9958 - accuracy: 0.5484 - val_loss: 2.9941 - val_accuracy: 0.6525
Epoch 45/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9849 - accuracy: 0.5764 - val_loss: 2.9848 - val_accuracy: 0.6525
Epoch 46/100
5/5 [==============================] - 0s 8ms/step - loss: 2.9820 - accuracy: 0.5567 - val_loss: 2.9756 - val_accuracy: 0.6492
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9673 - accuracy: 0.5681 - val_loss: 2.9663 - val_accuracy: 0.6590
Epoch 48/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9656 - accuracy: 0.5550 - val_loss: 2.9571 - val_accuracy: 0.6590
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9579 - accuracy: 0.5649 - val_loss: 2.9478 - val_accuracy: 0.6623
Epoch 50/100
5/5 [==============================] - 0s 8ms/step - loss: 2.9436 - accuracy: 0.5714 - val_loss: 2.9387 - val_accuracy: 0.6656
Epoch 51/100
5/5 [==============================] - 0s 11ms/step - loss: 2.9373 - accuracy: 0.5665 - val_loss: 2.9295 - val_accuracy: 0.6754
Epoch 52/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9256 - accuracy: 0.5895 - val_loss: 2.9203 - val_accuracy: 0.6754
Epoch 53/100
5/5 [==============================] - 0s 9ms/step - loss: 2.9167 - accuracy: 0.5911 - val_loss: 2.9110 - val_accuracy: 0.6787
Epoch 54/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9211 - accuracy: 0.5780 - val_loss: 2.9021 - val_accuracy: 0.6820
Epoch 55/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8926 - accuracy: 0.5796 - val_loss: 2.8929 - val_accuracy: 0.6820
Epoch 56/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8860 - accuracy: 0.5961 - val_loss: 2.8837 - val_accuracy: 0.6820
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8886 - accuracy: 0.6043 - val_loss: 2.8745 - val_accuracy: 0.6820
Epoch 58/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8707 - accuracy: 0.6223 - val_loss: 2.8655 - val_accuracy: 0.6820
Epoch 59/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8557 - accuracy: 0.6240 - val_loss: 2.8563 - val_accuracy: 0.6852
Epoch 60/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8586 - accuracy: 0.6141 - val_loss: 2.8473 - val_accuracy: 0.6885
Epoch 61/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8475 - accuracy: 0.6158 - val_loss: 2.8382 - val_accuracy: 0.6852
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8345 - accuracy: 0.6076 - val_loss: 2.8293 - val_accuracy: 0.6852
Epoch 63/100
5/5 [==============================] - 0s 9ms/step - loss: 2.8296 - accuracy: 0.6076 - val_loss: 2.8203 - val_accuracy: 0.6885
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8211 - accuracy: 0.6158 - val_loss: 2.8114 - val_accuracy: 0.6885
Epoch 65/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8133 - accuracy: 0.6338 - val_loss: 2.8025 - val_accuracy: 0.6951
Epoch 66/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8037 - accuracy: 0.6158 - val_loss: 2.7938 - val_accuracy: 0.6951
Epoch 67/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7925 - accuracy: 0.6338 - val_loss: 2.7850 - val_accuracy: 0.6984
Epoch 68/100
5/5 [==============================] - 0s 14ms/step - loss: 2.7847 - accuracy: 0.6388 - val_loss: 2.7761 - val_accuracy: 0.7049
Epoch 69/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7803 - accuracy: 0.6437 - val_loss: 2.7673 - val_accuracy: 0.7049
Epoch 70/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7715 - accuracy: 0.6453 - val_loss: 2.7585 - val_accuracy: 0.7049
Epoch 71/100
5/5 [==============================] - 0s 15ms/step - loss: 2.7652 - accuracy: 0.6355 - val_loss: 2.7497 - val_accuracy: 0.7049
Epoch 72/100
5/5 [==============================] - 0s 11ms/step - loss: 2.7579 - accuracy: 0.6437 - val_loss: 2.7410 - val_accuracy: 0.7049
Epoch 73/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7395 - accuracy: 0.6371 - val_loss: 2.7322 - val_accuracy: 0.7049
Epoch 74/100
5/5 [==============================] - 0s 14ms/step - loss: 2.7373 - accuracy: 0.6601 - val_loss: 2.7235 - val_accuracy: 0.7082
Epoch 75/100
5/5 [==============================] - 0s 9ms/step - loss: 2.7286 - accuracy: 0.6322 - val_loss: 2.7149 - val_accuracy: 0.7148
Epoch 76/100
5/5 [==============================] - 0s 8ms/step - loss: 2.7202 - accuracy: 0.6601 - val_loss: 2.7063 - val_accuracy: 0.7148
Epoch 77/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7165 - accuracy: 0.6502 - val_loss: 2.6977 - val_accuracy: 0.7148
Epoch 78/100
5/5 [==============================] - 0s 11ms/step - loss: 2.7015 - accuracy: 0.6585 - val_loss: 2.6892 - val_accuracy: 0.7148
Epoch 79/100
5/5 [==============================] - 0s 14ms/step - loss: 2.6956 - accuracy: 0.6634 - val_loss: 2.6806 - val_accuracy: 0.7213
Epoch 80/100
5/5 [==============================] - 0s 11ms/step - loss: 2.6891 - accuracy: 0.6667 - val_loss: 2.6720 - val_accuracy: 0.7246
Epoch 81/100
5/5 [==============================] - 0s 9ms/step - loss: 2.6818 - accuracy: 0.6683 - val_loss: 2.6634 - val_accuracy: 0.7246
Epoch 82/100
5/5 [==============================] - 0s 12ms/step - loss: 2.6591 - accuracy: 0.6502 - val_loss: 2.6548 - val_accuracy: 0.7246
Epoch 83/100
5/5 [==============================] - 0s 14ms/step - loss: 2.6666 - accuracy: 0.6831 - val_loss: 2.6464 - val_accuracy: 0.7246
Epoch 84/100
5/5 [==============================] - 0s 8ms/step - loss: 2.6602 - accuracy: 0.6535 - val_loss: 2.6381 - val_accuracy: 0.7246
Epoch 85/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6490 - accuracy: 0.6732 - val_loss: 2.6297 - val_accuracy: 0.7246
Epoch 86/100
5/5 [==============================] - 0s 11ms/step - loss: 2.6349 - accuracy: 0.6814 - val_loss: 2.6213 - val_accuracy: 0.7246
Epoch 87/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6352 - accuracy: 0.6601 - val_loss: 2.6128 - val_accuracy: 0.7213
Epoch 88/100
5/5 [==============================] - 0s 8ms/step - loss: 2.6227 - accuracy: 0.6667 - val_loss: 2.6045 - val_accuracy: 0.7279
Epoch 89/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6198 - accuracy: 0.6650 - val_loss: 2.5962 - val_accuracy: 0.7279
Epoch 90/100
5/5 [==============================] - 0s 14ms/step - loss: 2.6103 - accuracy: 0.6700 - val_loss: 2.5879 - val_accuracy: 0.7279
Epoch 91/100
5/5 [==============================] - 0s 9ms/step - loss: 2.5950 - accuracy: 0.6732 - val_loss: 2.5796 - val_accuracy: 0.7279
Epoch 92/100
5/5 [==============================] - 0s 8ms/step - loss: 2.5890 - accuracy: 0.6732 - val_loss: 2.5714 - val_accuracy: 0.7311
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5896 - accuracy: 0.6814 - val_loss: 2.5631 - val_accuracy: 0.7344
Epoch 94/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5786 - accuracy: 0.6880 - val_loss: 2.5550 - val_accuracy: 0.7344
Epoch 95/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5696 - accuracy: 0.6716 - val_loss: 2.5467 - val_accuracy: 0.7311
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5661 - accuracy: 0.6700 - val_loss: 2.5386 - val_accuracy: 0.7311
Epoch 97/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5516 - accuracy: 0.6782 - val_loss: 2.5304 - val_accuracy: 0.7311
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5555 - accuracy: 0.6765 - val_loss: 2.5224 - val_accuracy: 0.7311
Epoch 99/100
5/5 [==============================] - 0s 9ms/step - loss: 2.5342 - accuracy: 0.6617 - val_loss: 2.5142 - val_accuracy: 0.7344
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5268 - accuracy: 0.6798 - val_loss: 2.5061 - val_accuracy: 0.7344
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 32, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.9, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 67ms/step - loss: 3.4493 - accuracy: 0.2512 - val_loss: 3.2983 - val_accuracy: 0.3803
Epoch 2/100
5/5 [==============================] - 0s 12ms/step - loss: 3.4392 - accuracy: 0.2562 - val_loss: 3.2879 - val_accuracy: 0.3869
Epoch 3/100
5/5 [==============================] - 0s 13ms/step - loss: 3.4168 - accuracy: 0.2726 - val_loss: 3.2789 - val_accuracy: 0.3967
Epoch 4/100
5/5 [==============================] - 0s 12ms/step - loss: 3.4063 - accuracy: 0.2578 - val_loss: 3.2706 - val_accuracy: 0.3967
Epoch 5/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3812 - accuracy: 0.2627 - val_loss: 3.2627 - val_accuracy: 0.4066
Epoch 6/100
5/5 [==============================] - 0s 9ms/step - loss: 3.3782 - accuracy: 0.2644 - val_loss: 3.2549 - val_accuracy: 0.4098
Epoch 7/100
5/5 [==============================] - 0s 26ms/step - loss: 3.3675 - accuracy: 0.2709 - val_loss: 3.2473 - val_accuracy: 0.4098
Epoch 8/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3524 - accuracy: 0.2693 - val_loss: 3.2396 - val_accuracy: 0.4098
Epoch 9/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3466 - accuracy: 0.2529 - val_loss: 3.2320 - val_accuracy: 0.4131
Epoch 10/100
5/5 [==============================] - 0s 14ms/step - loss: 3.3416 - accuracy: 0.2660 - val_loss: 3.2242 - val_accuracy: 0.4033
Epoch 11/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3177 - accuracy: 0.2759 - val_loss: 3.2165 - val_accuracy: 0.4033
Epoch 12/100
5/5 [==============================] - 0s 10ms/step - loss: 3.3075 - accuracy: 0.2906 - val_loss: 3.2089 - val_accuracy: 0.4066
Epoch 13/100
5/5 [==============================] - 0s 9ms/step - loss: 3.2988 - accuracy: 0.2923 - val_loss: 3.2011 - val_accuracy: 0.4131
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2787 - accuracy: 0.2775 - val_loss: 3.1932 - val_accuracy: 0.4230
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 3.2746 - accuracy: 0.2923 - val_loss: 3.1855 - val_accuracy: 0.4262
Epoch 16/100
5/5 [==============================] - 0s 9ms/step - loss: 3.2652 - accuracy: 0.2890 - val_loss: 3.1776 - val_accuracy: 0.4230
Epoch 17/100
5/5 [==============================] - 0s 9ms/step - loss: 3.2565 - accuracy: 0.2841 - val_loss: 3.1697 - val_accuracy: 0.4197
Epoch 18/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2422 - accuracy: 0.3103 - val_loss: 3.1617 - val_accuracy: 0.4230
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2405 - accuracy: 0.3054 - val_loss: 3.1536 - val_accuracy: 0.4230
Epoch 20/100
5/5 [==============================] - 0s 13ms/step - loss: 3.2149 - accuracy: 0.3169 - val_loss: 3.1455 - val_accuracy: 0.4295
Epoch 21/100
5/5 [==============================] - 0s 11ms/step - loss: 3.2090 - accuracy: 0.3038 - val_loss: 3.1373 - val_accuracy: 0.4295
Epoch 22/100
5/5 [==============================] - 0s 14ms/step - loss: 3.1988 - accuracy: 0.2923 - val_loss: 3.1291 - val_accuracy: 0.4361
Epoch 23/100
5/5 [==============================] - 0s 10ms/step - loss: 3.1847 - accuracy: 0.3186 - val_loss: 3.1209 - val_accuracy: 0.4459
Epoch 24/100
5/5 [==============================] - 0s 11ms/step - loss: 3.1745 - accuracy: 0.3317 - val_loss: 3.1126 - val_accuracy: 0.4525
Epoch 25/100
5/5 [==============================] - 0s 13ms/step - loss: 3.1745 - accuracy: 0.3235 - val_loss: 3.1043 - val_accuracy: 0.4525
Epoch 26/100
5/5 [==============================] - 0s 13ms/step - loss: 3.1589 - accuracy: 0.3202 - val_loss: 3.0961 - val_accuracy: 0.4492
Epoch 27/100
5/5 [==============================] - 0s 9ms/step - loss: 3.1513 - accuracy: 0.3366 - val_loss: 3.0877 - val_accuracy: 0.4492
Epoch 28/100
5/5 [==============================] - 0s 13ms/step - loss: 3.1314 - accuracy: 0.3415 - val_loss: 3.0794 - val_accuracy: 0.4557
Epoch 29/100
5/5 [==============================] - 0s 14ms/step - loss: 3.1228 - accuracy: 0.3300 - val_loss: 3.0709 - val_accuracy: 0.4557
Epoch 30/100
5/5 [==============================] - 0s 9ms/step - loss: 3.1134 - accuracy: 0.3727 - val_loss: 3.0626 - val_accuracy: 0.4623
Epoch 31/100
5/5 [==============================] - 0s 13ms/step - loss: 3.1012 - accuracy: 0.3530 - val_loss: 3.0542 - val_accuracy: 0.4656
Epoch 32/100
5/5 [==============================] - 0s 11ms/step - loss: 3.0964 - accuracy: 0.3629 - val_loss: 3.0458 - val_accuracy: 0.4721
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 3.1018 - accuracy: 0.3432 - val_loss: 3.0374 - val_accuracy: 0.4885
Epoch 34/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0688 - accuracy: 0.3645 - val_loss: 3.0290 - val_accuracy: 0.4951
Epoch 35/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0657 - accuracy: 0.3695 - val_loss: 3.0205 - val_accuracy: 0.5049
Epoch 36/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0505 - accuracy: 0.3810 - val_loss: 3.0119 - val_accuracy: 0.5148
Epoch 37/100
5/5 [==============================] - 0s 9ms/step - loss: 3.0516 - accuracy: 0.3711 - val_loss: 3.0033 - val_accuracy: 0.5311
Epoch 38/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0355 - accuracy: 0.3941 - val_loss: 2.9947 - val_accuracy: 0.5377
Epoch 39/100
5/5 [==============================] - 0s 10ms/step - loss: 3.0282 - accuracy: 0.4286 - val_loss: 2.9861 - val_accuracy: 0.5410
Epoch 40/100
5/5 [==============================] - 0s 9ms/step - loss: 3.0164 - accuracy: 0.4072 - val_loss: 2.9774 - val_accuracy: 0.5443
Epoch 41/100
5/5 [==============================] - 0s 14ms/step - loss: 3.0078 - accuracy: 0.4138 - val_loss: 2.9688 - val_accuracy: 0.5508
Epoch 42/100
5/5 [==============================] - 0s 15ms/step - loss: 2.9935 - accuracy: 0.4401 - val_loss: 2.9600 - val_accuracy: 0.5639
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9915 - accuracy: 0.4236 - val_loss: 2.9513 - val_accuracy: 0.5705
Epoch 44/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9815 - accuracy: 0.4581 - val_loss: 2.9427 - val_accuracy: 0.5770
Epoch 45/100
5/5 [==============================] - 0s 11ms/step - loss: 2.9657 - accuracy: 0.4351 - val_loss: 2.9340 - val_accuracy: 0.5738
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9573 - accuracy: 0.4384 - val_loss: 2.9252 - val_accuracy: 0.5738
Epoch 47/100
5/5 [==============================] - 0s 11ms/step - loss: 2.9474 - accuracy: 0.4581 - val_loss: 2.9165 - val_accuracy: 0.5803
Epoch 48/100
5/5 [==============================] - 0s 10ms/step - loss: 2.9482 - accuracy: 0.4384 - val_loss: 2.9077 - val_accuracy: 0.5803
Epoch 49/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9337 - accuracy: 0.4433 - val_loss: 2.8990 - val_accuracy: 0.5803
Epoch 50/100
5/5 [==============================] - 0s 11ms/step - loss: 2.9181 - accuracy: 0.4811 - val_loss: 2.8902 - val_accuracy: 0.5770
Epoch 51/100
5/5 [==============================] - 0s 14ms/step - loss: 2.9079 - accuracy: 0.4844 - val_loss: 2.8815 - val_accuracy: 0.5869
Epoch 52/100
5/5 [==============================] - 0s 14ms/step - loss: 2.9003 - accuracy: 0.4926 - val_loss: 2.8727 - val_accuracy: 0.5902
Epoch 53/100
5/5 [==============================] - 0s 11ms/step - loss: 2.8943 - accuracy: 0.4877 - val_loss: 2.8639 - val_accuracy: 0.5934
Epoch 54/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8795 - accuracy: 0.5107 - val_loss: 2.8552 - val_accuracy: 0.5934
Epoch 55/100
5/5 [==============================] - 0s 9ms/step - loss: 2.8782 - accuracy: 0.4795 - val_loss: 2.8464 - val_accuracy: 0.6000
Epoch 56/100
5/5 [==============================] - 0s 8ms/step - loss: 2.8600 - accuracy: 0.5140 - val_loss: 2.8377 - val_accuracy: 0.6066
Epoch 57/100
5/5 [==============================] - 0s 8ms/step - loss: 2.8574 - accuracy: 0.5189 - val_loss: 2.8289 - val_accuracy: 0.6098
Epoch 58/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8463 - accuracy: 0.5255 - val_loss: 2.8202 - val_accuracy: 0.6164
Epoch 59/100
5/5 [==============================] - 0s 11ms/step - loss: 2.8343 - accuracy: 0.5222 - val_loss: 2.8112 - val_accuracy: 0.6164
Epoch 60/100
5/5 [==============================] - 0s 9ms/step - loss: 2.8248 - accuracy: 0.5222 - val_loss: 2.8024 - val_accuracy: 0.6230
Epoch 61/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8173 - accuracy: 0.5074 - val_loss: 2.7937 - val_accuracy: 0.6262
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8099 - accuracy: 0.5090 - val_loss: 2.7849 - val_accuracy: 0.6361
Epoch 63/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7988 - accuracy: 0.5353 - val_loss: 2.7762 - val_accuracy: 0.6393
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7867 - accuracy: 0.5468 - val_loss: 2.7673 - val_accuracy: 0.6459
Epoch 65/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7821 - accuracy: 0.5501 - val_loss: 2.7585 - val_accuracy: 0.6492
Epoch 66/100
5/5 [==============================] - 0s 15ms/step - loss: 2.7757 - accuracy: 0.5567 - val_loss: 2.7497 - val_accuracy: 0.6525
Epoch 67/100
5/5 [==============================] - 0s 8ms/step - loss: 2.7678 - accuracy: 0.5567 - val_loss: 2.7411 - val_accuracy: 0.6459
Epoch 68/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7543 - accuracy: 0.5714 - val_loss: 2.7325 - val_accuracy: 0.6459
Epoch 69/100
5/5 [==============================] - 0s 10ms/step - loss: 2.7460 - accuracy: 0.5632 - val_loss: 2.7238 - val_accuracy: 0.6459
Epoch 70/100
5/5 [==============================] - 0s 9ms/step - loss: 2.7331 - accuracy: 0.5862 - val_loss: 2.7152 - val_accuracy: 0.6459
Epoch 71/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7309 - accuracy: 0.5731 - val_loss: 2.7066 - val_accuracy: 0.6459
Epoch 72/100
5/5 [==============================] - 0s 11ms/step - loss: 2.7201 - accuracy: 0.5764 - val_loss: 2.6981 - val_accuracy: 0.6557
Epoch 73/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7087 - accuracy: 0.5928 - val_loss: 2.6894 - val_accuracy: 0.6623
Epoch 74/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6997 - accuracy: 0.5813 - val_loss: 2.6808 - val_accuracy: 0.6656
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 2.6967 - accuracy: 0.6010 - val_loss: 2.6724 - val_accuracy: 0.6656
Epoch 76/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6880 - accuracy: 0.5993 - val_loss: 2.6638 - val_accuracy: 0.6689
Epoch 77/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6838 - accuracy: 0.6043 - val_loss: 2.6554 - val_accuracy: 0.6754
Epoch 78/100
5/5 [==============================] - 0s 9ms/step - loss: 2.6689 - accuracy: 0.6256 - val_loss: 2.6469 - val_accuracy: 0.6754
Epoch 79/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6534 - accuracy: 0.6338 - val_loss: 2.6384 - val_accuracy: 0.6852
Epoch 80/100
5/5 [==============================] - 0s 10ms/step - loss: 2.6597 - accuracy: 0.6059 - val_loss: 2.6300 - val_accuracy: 0.6918
Epoch 81/100
5/5 [==============================] - 0s 15ms/step - loss: 2.6494 - accuracy: 0.5895 - val_loss: 2.6216 - val_accuracy: 0.6951
Epoch 82/100
5/5 [==============================] - 0s 8ms/step - loss: 2.6361 - accuracy: 0.6059 - val_loss: 2.6132 - val_accuracy: 0.6951
Epoch 83/100
5/5 [==============================] - 0s 11ms/step - loss: 2.6287 - accuracy: 0.6305 - val_loss: 2.6049 - val_accuracy: 0.6984
Epoch 84/100
5/5 [==============================] - 0s 12ms/step - loss: 2.6213 - accuracy: 0.6535 - val_loss: 2.5964 - val_accuracy: 0.6984
Epoch 85/100
5/5 [==============================] - 0s 9ms/step - loss: 2.6125 - accuracy: 0.6322 - val_loss: 2.5881 - val_accuracy: 0.6984
Epoch 86/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5891 - accuracy: 0.6470 - val_loss: 2.5797 - val_accuracy: 0.6984
Epoch 87/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5954 - accuracy: 0.6256 - val_loss: 2.5715 - val_accuracy: 0.6984
Epoch 88/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5823 - accuracy: 0.6355 - val_loss: 2.5632 - val_accuracy: 0.6984
Epoch 89/100
5/5 [==============================] - 0s 9ms/step - loss: 2.5776 - accuracy: 0.6486 - val_loss: 2.5551 - val_accuracy: 0.6984
Epoch 90/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5725 - accuracy: 0.6535 - val_loss: 2.5469 - val_accuracy: 0.6951
Epoch 91/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5707 - accuracy: 0.6273 - val_loss: 2.5389 - val_accuracy: 0.6951
Epoch 92/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5503 - accuracy: 0.6453 - val_loss: 2.5309 - val_accuracy: 0.6951
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5552 - accuracy: 0.6223 - val_loss: 2.5228 - val_accuracy: 0.6984
Epoch 94/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5414 - accuracy: 0.6420 - val_loss: 2.5147 - val_accuracy: 0.6984
Epoch 95/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5281 - accuracy: 0.6650 - val_loss: 2.5066 - val_accuracy: 0.6984
Epoch 96/100
5/5 [==============================] - 0s 11ms/step - loss: 2.5267 - accuracy: 0.6322 - val_loss: 2.4985 - val_accuracy: 0.7082
Epoch 97/100
5/5 [==============================] - 0s 9ms/step - loss: 2.5149 - accuracy: 0.6650 - val_loss: 2.4905 - val_accuracy: 0.7049
Epoch 98/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5041 - accuracy: 0.6634 - val_loss: 2.4825 - val_accuracy: 0.7115
Epoch 99/100
5/5 [==============================] - 0s 13ms/step - loss: 2.4957 - accuracy: 0.6552 - val_loss: 2.4744 - val_accuracy: 0.7148
Epoch 100/100
5/5 [==============================] - 0s 13ms/step - loss: 2.4966 - accuracy: 0.6437 - val_loss: 2.4664 - val_accuracy: 0.7148
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 2, 'hidden_units': 32, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.9, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 128
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
5/5 [==============================] - 1s 63ms/step - loss: 3.3981 - accuracy: 0.3902 - val_loss: 3.4153 - val_accuracy: 0.2204
Epoch 2/100
5/5 [==============================] - 0s 14ms/step - loss: 3.3819 - accuracy: 0.4066 - val_loss: 3.4015 - val_accuracy: 0.2237
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3638 - accuracy: 0.4000 - val_loss: 3.3895 - val_accuracy: 0.2368
Epoch 4/100
5/5 [==============================] - 0s 13ms/step - loss: 3.3491 - accuracy: 0.4098 - val_loss: 3.3783 - val_accuracy: 0.2664
Epoch 5/100
5/5 [==============================] - 0s 13ms/step - loss: 3.3374 - accuracy: 0.4279 - val_loss: 3.3676 - val_accuracy: 0.2763
Epoch 6/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3305 - accuracy: 0.4246 - val_loss: 3.3572 - val_accuracy: 0.2961
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 3.3293 - accuracy: 0.4230 - val_loss: 3.3464 - val_accuracy: 0.3059
Epoch 8/100
5/5 [==============================] - 0s 15ms/step - loss: 3.3082 - accuracy: 0.4262 - val_loss: 3.3360 - val_accuracy: 0.3224
Epoch 9/100
5/5 [==============================] - 0s 8ms/step - loss: 3.2924 - accuracy: 0.4590 - val_loss: 3.3260 - val_accuracy: 0.3454
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2860 - accuracy: 0.4738 - val_loss: 3.3158 - val_accuracy: 0.3553
Epoch 11/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2830 - accuracy: 0.4279 - val_loss: 3.3056 - val_accuracy: 0.3684
Epoch 12/100
5/5 [==============================] - 0s 8ms/step - loss: 3.2656 - accuracy: 0.4689 - val_loss: 3.2954 - val_accuracy: 0.3947
Epoch 13/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2538 - accuracy: 0.4721 - val_loss: 3.2850 - val_accuracy: 0.4013
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 3.2528 - accuracy: 0.4607 - val_loss: 3.2747 - val_accuracy: 0.4046
Epoch 15/100
5/5 [==============================] - 0s 9ms/step - loss: 3.2333 - accuracy: 0.4852 - val_loss: 3.2644 - val_accuracy: 0.4243
Epoch 16/100
5/5 [==============================] - 0s 11ms/step - loss: 3.2307 - accuracy: 0.4951 - val_loss: 3.2545 - val_accuracy: 0.4243
Epoch 17/100
5/5 [==============================] - 0s 13ms/step - loss: 3.2168 - accuracy: 0.4918 - val_loss: 3.2444 - val_accuracy: 0.4474
Epoch 18/100
5/5 [==============================] - 0s 16ms/step - loss: 3.2054 - accuracy: 0.5049 - val_loss: 3.2346 - val_accuracy: 0.4638
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 3.1989 - accuracy: 0.5230 - val_loss: 3.2246 - val_accuracy: 0.4803
Epoch 20/100
5/5 [==============================] - 0s 13ms/step - loss: 3.1847 - accuracy: 0.5148 - val_loss: 3.2147 - val_accuracy: 0.4868
Epoch 21/100
5/5 [==============================] - 0s 8ms/step - loss: 3.1748 - accuracy: 0.5213 - val_loss: 3.2047 - val_accuracy: 0.4934
Epoch 22/100
5/5 [==============================] - 0s 13ms/step - loss: 3.1662 - accuracy: 0.5344 - val_loss: 3.1949 - val_accuracy: 0.4967
Epoch 23/100
5/5 [==============================] - 0s 9ms/step - loss: 3.1588 - accuracy: 0.5311 - val_loss: 3.1853 - val_accuracy: 0.4967
Epoch 24/100
5/5 [==============================] - 0s 13ms/step - loss: 3.1445 - accuracy: 0.5475 - val_loss: 3.1754 - val_accuracy: 0.5066
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 3.1379 - accuracy: 0.5508 - val_loss: 3.1657 - val_accuracy: 0.5099
Epoch 26/100
5/5 [==============================] - 0s 15ms/step - loss: 3.1256 - accuracy: 0.5623 - val_loss: 3.1560 - val_accuracy: 0.5099
Epoch 27/100
5/5 [==============================] - 0s 12ms/step - loss: 3.1256 - accuracy: 0.5705 - val_loss: 3.1463 - val_accuracy: 0.5099
Epoch 28/100
5/5 [==============================] - 0s 11ms/step - loss: 3.1090 - accuracy: 0.5656 - val_loss: 3.1368 - val_accuracy: 0.5263
Epoch 29/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0978 - accuracy: 0.5787 - val_loss: 3.1273 - val_accuracy: 0.5263
Epoch 30/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0917 - accuracy: 0.5623 - val_loss: 3.1178 - val_accuracy: 0.5329
Epoch 31/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0837 - accuracy: 0.5590 - val_loss: 3.1082 - val_accuracy: 0.5362
Epoch 32/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0656 - accuracy: 0.5885 - val_loss: 3.0985 - val_accuracy: 0.5428
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0495 - accuracy: 0.5869 - val_loss: 3.0889 - val_accuracy: 0.5493
Epoch 34/100
5/5 [==============================] - 0s 10ms/step - loss: 3.0527 - accuracy: 0.6115 - val_loss: 3.0795 - val_accuracy: 0.5658
Epoch 35/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0364 - accuracy: 0.5738 - val_loss: 3.0702 - val_accuracy: 0.5724
Epoch 36/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0281 - accuracy: 0.6016 - val_loss: 3.0609 - val_accuracy: 0.5822
Epoch 37/100
5/5 [==============================] - 0s 15ms/step - loss: 3.0175 - accuracy: 0.6033 - val_loss: 3.0517 - val_accuracy: 0.5855
Epoch 38/100
5/5 [==============================] - 0s 11ms/step - loss: 3.0091 - accuracy: 0.6033 - val_loss: 3.0424 - val_accuracy: 0.5888
Epoch 39/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0090 - accuracy: 0.6016 - val_loss: 3.0331 - val_accuracy: 0.5921
Epoch 40/100
5/5 [==============================] - 0s 9ms/step - loss: 2.9988 - accuracy: 0.6082 - val_loss: 3.0239 - val_accuracy: 0.5888
Epoch 41/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9829 - accuracy: 0.6197 - val_loss: 3.0147 - val_accuracy: 0.5921
Epoch 42/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9741 - accuracy: 0.6197 - val_loss: 3.0055 - val_accuracy: 0.5954
Epoch 43/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9623 - accuracy: 0.6246 - val_loss: 2.9964 - val_accuracy: 0.6053
Epoch 44/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9533 - accuracy: 0.6246 - val_loss: 2.9873 - val_accuracy: 0.6118
Epoch 45/100
5/5 [==============================] - 0s 11ms/step - loss: 2.9480 - accuracy: 0.6115 - val_loss: 2.9781 - val_accuracy: 0.6250
Epoch 46/100
5/5 [==============================] - 0s 15ms/step - loss: 2.9410 - accuracy: 0.6279 - val_loss: 2.9692 - val_accuracy: 0.6250
Epoch 47/100
5/5 [==============================] - 0s 8ms/step - loss: 2.9389 - accuracy: 0.6098 - val_loss: 2.9603 - val_accuracy: 0.6349
Epoch 48/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9168 - accuracy: 0.6311 - val_loss: 2.9512 - val_accuracy: 0.6349
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 2.9128 - accuracy: 0.6361 - val_loss: 2.9422 - val_accuracy: 0.6349
Epoch 50/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8923 - accuracy: 0.6377 - val_loss: 2.9332 - val_accuracy: 0.6316
Epoch 51/100
5/5 [==============================] - 0s 9ms/step - loss: 2.8945 - accuracy: 0.6295 - val_loss: 2.9242 - val_accuracy: 0.6382
Epoch 52/100
5/5 [==============================] - 0s 9ms/step - loss: 2.8873 - accuracy: 0.6541 - val_loss: 2.9154 - val_accuracy: 0.6382
Epoch 53/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8751 - accuracy: 0.6262 - val_loss: 2.9066 - val_accuracy: 0.6382
Epoch 54/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8687 - accuracy: 0.6344 - val_loss: 2.8978 - val_accuracy: 0.6414
Epoch 55/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8582 - accuracy: 0.6426 - val_loss: 2.8889 - val_accuracy: 0.6414
Epoch 56/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8425 - accuracy: 0.6590 - val_loss: 2.8801 - val_accuracy: 0.6414
Epoch 57/100
5/5 [==============================] - 0s 10ms/step - loss: 2.8370 - accuracy: 0.6557 - val_loss: 2.8715 - val_accuracy: 0.6447
Epoch 58/100
5/5 [==============================] - 0s 14ms/step - loss: 2.8224 - accuracy: 0.6721 - val_loss: 2.8626 - val_accuracy: 0.6480
Epoch 59/100
5/5 [==============================] - 0s 16ms/step - loss: 2.8213 - accuracy: 0.6607 - val_loss: 2.8540 - val_accuracy: 0.6480
Epoch 60/100
5/5 [==============================] - 0s 12ms/step - loss: 2.8169 - accuracy: 0.6279 - val_loss: 2.8454 - val_accuracy: 0.6480
Epoch 61/100
5/5 [==============================] - 0s 13ms/step - loss: 2.8017 - accuracy: 0.6623 - val_loss: 2.8368 - val_accuracy: 0.6513
Epoch 62/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7970 - accuracy: 0.6639 - val_loss: 2.8282 - val_accuracy: 0.6513
Epoch 63/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7909 - accuracy: 0.6590 - val_loss: 2.8197 - val_accuracy: 0.6513
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7794 - accuracy: 0.6869 - val_loss: 2.8114 - val_accuracy: 0.6612
Epoch 65/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7666 - accuracy: 0.6557 - val_loss: 2.8031 - val_accuracy: 0.6612
Epoch 66/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7621 - accuracy: 0.6557 - val_loss: 2.7946 - val_accuracy: 0.6612
Epoch 67/100
5/5 [==============================] - 0s 9ms/step - loss: 2.7524 - accuracy: 0.6656 - val_loss: 2.7862 - val_accuracy: 0.6678
Epoch 68/100
5/5 [==============================] - 0s 12ms/step - loss: 2.7444 - accuracy: 0.6721 - val_loss: 2.7779 - val_accuracy: 0.6711
Epoch 69/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7353 - accuracy: 0.6803 - val_loss: 2.7695 - val_accuracy: 0.6711
Epoch 70/100
5/5 [==============================] - 0s 14ms/step - loss: 2.7289 - accuracy: 0.6656 - val_loss: 2.7612 - val_accuracy: 0.6678
Epoch 71/100
5/5 [==============================] - 0s 9ms/step - loss: 2.7239 - accuracy: 0.6639 - val_loss: 2.7529 - val_accuracy: 0.6678
Epoch 72/100
5/5 [==============================] - 0s 9ms/step - loss: 2.7120 - accuracy: 0.6902 - val_loss: 2.7446 - val_accuracy: 0.6711
Epoch 73/100
5/5 [==============================] - 0s 12ms/step - loss: 2.6907 - accuracy: 0.6967 - val_loss: 2.7363 - val_accuracy: 0.6678
Epoch 74/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6901 - accuracy: 0.6754 - val_loss: 2.7281 - val_accuracy: 0.6678
Epoch 75/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6811 - accuracy: 0.6934 - val_loss: 2.7200 - val_accuracy: 0.6711
Epoch 76/100
5/5 [==============================] - 0s 11ms/step - loss: 2.6759 - accuracy: 0.6754 - val_loss: 2.7118 - val_accuracy: 0.6711
Epoch 77/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6650 - accuracy: 0.6902 - val_loss: 2.7037 - val_accuracy: 0.6711
Epoch 78/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6613 - accuracy: 0.6967 - val_loss: 2.6955 - val_accuracy: 0.6711
Epoch 79/100
5/5 [==============================] - 0s 12ms/step - loss: 2.6502 - accuracy: 0.6984 - val_loss: 2.6874 - val_accuracy: 0.6711
Epoch 80/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6395 - accuracy: 0.7082 - val_loss: 2.6792 - val_accuracy: 0.6711
Epoch 81/100
5/5 [==============================] - 0s 14ms/step - loss: 2.6248 - accuracy: 0.7016 - val_loss: 2.6711 - val_accuracy: 0.6711
Epoch 82/100
5/5 [==============================] - 0s 8ms/step - loss: 2.6241 - accuracy: 0.6836 - val_loss: 2.6632 - val_accuracy: 0.6711
Epoch 83/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6197 - accuracy: 0.6836 - val_loss: 2.6550 - val_accuracy: 0.6711
Epoch 84/100
5/5 [==============================] - 0s 13ms/step - loss: 2.6060 - accuracy: 0.7033 - val_loss: 2.6471 - val_accuracy: 0.6711
Epoch 85/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5942 - accuracy: 0.7131 - val_loss: 2.6391 - val_accuracy: 0.6743
Epoch 86/100
5/5 [==============================] - 0s 8ms/step - loss: 2.5848 - accuracy: 0.7131 - val_loss: 2.6312 - val_accuracy: 0.6743
Epoch 87/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5833 - accuracy: 0.6918 - val_loss: 2.6234 - val_accuracy: 0.6743
Epoch 88/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5815 - accuracy: 0.7066 - val_loss: 2.6157 - val_accuracy: 0.6743
Epoch 89/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5669 - accuracy: 0.7131 - val_loss: 2.6076 - val_accuracy: 0.6743
Epoch 90/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5610 - accuracy: 0.7164 - val_loss: 2.5997 - val_accuracy: 0.6743
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5504 - accuracy: 0.7066 - val_loss: 2.5920 - val_accuracy: 0.6743
Epoch 92/100
5/5 [==============================] - 0s 15ms/step - loss: 2.5411 - accuracy: 0.7131 - val_loss: 2.5842 - val_accuracy: 0.6743
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5384 - accuracy: 0.7164 - val_loss: 2.5763 - val_accuracy: 0.6743
Epoch 94/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5249 - accuracy: 0.7082 - val_loss: 2.5686 - val_accuracy: 0.6743
Epoch 95/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5179 - accuracy: 0.6984 - val_loss: 2.5607 - val_accuracy: 0.6743
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5083 - accuracy: 0.7000 - val_loss: 2.5528 - val_accuracy: 0.6743
Epoch 97/100
5/5 [==============================] - 0s 12ms/step - loss: 2.5036 - accuracy: 0.7180 - val_loss: 2.5450 - val_accuracy: 0.6743
Epoch 98/100
5/5 [==============================] - 0s 9ms/step - loss: 2.4987 - accuracy: 0.7033 - val_loss: 2.5374 - val_accuracy: 0.6743
Epoch 99/100
5/5 [==============================] - 0s 9ms/step - loss: 2.4897 - accuracy: 0.7180 - val_loss: 2.5298 - val_accuracy: 0.6743
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 2.4761 - accuracy: 0.7361 - val_loss: 2.5221 - val_accuracy: 0.6776
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 10
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 1, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 65ms/step - loss: 3.6413 - accuracy: 0.4844 - val_loss: 2.2323 - val_accuracy: 0.8262
Epoch 2/100
5/5 [==============================] - 0s 14ms/step - loss: 2.3978 - accuracy: 0.7061 - val_loss: 1.8907 - val_accuracy: 0.8164
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 1.9451 - accuracy: 0.7931 - val_loss: 1.5793 - val_accuracy: 0.8164
Epoch 4/100
5/5 [==============================] - 0s 13ms/step - loss: 1.4311 - accuracy: 0.8522 - val_loss: 1.4708 - val_accuracy: 0.8164
Epoch 5/100
5/5 [==============================] - 0s 13ms/step - loss: 1.2529 - accuracy: 0.8506 - val_loss: 1.2919 - val_accuracy: 0.8164
Epoch 6/100
5/5 [==============================] - 0s 13ms/step - loss: 1.0078 - accuracy: 0.8621 - val_loss: 1.1445 - val_accuracy: 0.8164
Epoch 7/100
5/5 [==============================] - 0s 11ms/step - loss: 1.0119 - accuracy: 0.8456 - val_loss: 1.0797 - val_accuracy: 0.8164
Epoch 8/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8587 - accuracy: 0.8473 - val_loss: 1.0622 - val_accuracy: 0.8164
Epoch 9/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7625 - accuracy: 0.8752 - val_loss: 0.9934 - val_accuracy: 0.8164
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7069 - accuracy: 0.8654 - val_loss: 0.8867 - val_accuracy: 0.8164
Epoch 11/100
5/5 [==============================] - 0s 14ms/step - loss: 0.6665 - accuracy: 0.8555 - val_loss: 0.9358 - val_accuracy: 0.8164
Epoch 12/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5686 - accuracy: 0.8752 - val_loss: 0.8945 - val_accuracy: 0.8164
Epoch 13/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6018 - accuracy: 0.8522 - val_loss: 0.8793 - val_accuracy: 0.8164
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5986 - accuracy: 0.8604 - val_loss: 0.7659 - val_accuracy: 0.8164
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5797 - accuracy: 0.8588 - val_loss: 0.7839 - val_accuracy: 0.8164
Epoch 16/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5259 - accuracy: 0.8703 - val_loss: 0.8242 - val_accuracy: 0.8164
Epoch 17/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5704 - accuracy: 0.8555 - val_loss: 0.7534 - val_accuracy: 0.8164
Epoch 18/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5163 - accuracy: 0.8654 - val_loss: 0.7558 - val_accuracy: 0.8164
Epoch 19/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5839 - accuracy: 0.8506 - val_loss: 0.7469 - val_accuracy: 0.8164
Epoch 20/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5401 - accuracy: 0.8522 - val_loss: 0.7766 - val_accuracy: 0.8164
Epoch 21/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5082 - accuracy: 0.8785 - val_loss: 0.7578 - val_accuracy: 0.8164
Epoch 22/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4976 - accuracy: 0.8801 - val_loss: 0.7731 - val_accuracy: 0.8164
Epoch 23/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5414 - accuracy: 0.8637 - val_loss: 0.7569 - val_accuracy: 0.8164
Epoch 24/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5409 - accuracy: 0.8539 - val_loss: 0.7950 - val_accuracy: 0.8164
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5027 - accuracy: 0.8851 - val_loss: 0.7835 - val_accuracy: 0.8164
Epoch 26/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5270 - accuracy: 0.8686 - val_loss: 0.6870 - val_accuracy: 0.8164
Epoch 27/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5089 - accuracy: 0.8670 - val_loss: 0.7005 - val_accuracy: 0.8164
Epoch 28/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5028 - accuracy: 0.8736 - val_loss: 0.7648 - val_accuracy: 0.8164
Epoch 29/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5086 - accuracy: 0.8588 - val_loss: 0.7295 - val_accuracy: 0.8164
Epoch 30/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5019 - accuracy: 0.8654 - val_loss: 0.7169 - val_accuracy: 0.8164
Epoch 31/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5023 - accuracy: 0.8571 - val_loss: 0.7260 - val_accuracy: 0.8164
Epoch 32/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4947 - accuracy: 0.8752 - val_loss: 0.7131 - val_accuracy: 0.8164
Epoch 33/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4838 - accuracy: 0.8768 - val_loss: 0.6651 - val_accuracy: 0.8164
Epoch 34/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4932 - accuracy: 0.8637 - val_loss: 0.8103 - val_accuracy: 0.8164
Epoch 35/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5218 - accuracy: 0.8539 - val_loss: 0.6743 - val_accuracy: 0.8164
Epoch 36/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4866 - accuracy: 0.8686 - val_loss: 0.6813 - val_accuracy: 0.8164
Epoch 37/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4891 - accuracy: 0.8670 - val_loss: 0.6695 - val_accuracy: 0.8164
Epoch 38/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5086 - accuracy: 0.8637 - val_loss: 0.6915 - val_accuracy: 0.8164
Epoch 39/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4873 - accuracy: 0.8703 - val_loss: 0.7386 - val_accuracy: 0.8164
Epoch 40/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4973 - accuracy: 0.8621 - val_loss: 0.6539 - val_accuracy: 0.8164
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4728 - accuracy: 0.8867 - val_loss: 0.7258 - val_accuracy: 0.8164
Epoch 42/100
5/5 [==============================] - 0s 10ms/step - loss: 0.5227 - accuracy: 0.8621 - val_loss: 0.7301 - val_accuracy: 0.8164
Epoch 43/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4877 - accuracy: 0.8686 - val_loss: 0.6962 - val_accuracy: 0.8164
Epoch 44/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4939 - accuracy: 0.8621 - val_loss: 0.7075 - val_accuracy: 0.8164
Epoch 45/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4984 - accuracy: 0.8752 - val_loss: 0.6994 - val_accuracy: 0.8164
Epoch 46/100
5/5 [==============================] - 0s 9ms/step - loss: 0.4804 - accuracy: 0.8719 - val_loss: 0.7462 - val_accuracy: 0.8164
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4895 - accuracy: 0.8654 - val_loss: 0.7445 - val_accuracy: 0.8164
Epoch 48/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4925 - accuracy: 0.8785 - val_loss: 0.6675 - val_accuracy: 0.8164
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4882 - accuracy: 0.8801 - val_loss: 0.7822 - val_accuracy: 0.8164
Epoch 50/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4845 - accuracy: 0.8768 - val_loss: 0.6844 - val_accuracy: 0.8164
Epoch 51/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4844 - accuracy: 0.8752 - val_loss: 0.7251 - val_accuracy: 0.8164
Epoch 52/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5002 - accuracy: 0.8637 - val_loss: 0.6809 - val_accuracy: 0.8164
Epoch 53/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5108 - accuracy: 0.8654 - val_loss: 0.6902 - val_accuracy: 0.8164
Epoch 54/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4791 - accuracy: 0.8768 - val_loss: 0.6479 - val_accuracy: 0.8164
Epoch 55/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5000 - accuracy: 0.8637 - val_loss: 0.6266 - val_accuracy: 0.8164
Epoch 56/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4821 - accuracy: 0.8654 - val_loss: 0.7082 - val_accuracy: 0.8164
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4708 - accuracy: 0.8801 - val_loss: 0.7712 - val_accuracy: 0.8164
Epoch 58/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4792 - accuracy: 0.8752 - val_loss: 0.6276 - val_accuracy: 0.8164
Epoch 59/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4694 - accuracy: 0.8637 - val_loss: 0.6382 - val_accuracy: 0.8164
Epoch 60/100
5/5 [==============================] - 0s 17ms/step - loss: 0.4735 - accuracy: 0.8670 - val_loss: 0.7667 - val_accuracy: 0.8164
Epoch 61/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5096 - accuracy: 0.8604 - val_loss: 0.6391 - val_accuracy: 0.8164
Epoch 62/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4672 - accuracy: 0.8851 - val_loss: 0.6341 - val_accuracy: 0.8164
Epoch 63/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4915 - accuracy: 0.8621 - val_loss: 0.7345 - val_accuracy: 0.8164
Epoch 64/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4884 - accuracy: 0.8637 - val_loss: 0.7160 - val_accuracy: 0.8164
Epoch 65/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4704 - accuracy: 0.8719 - val_loss: 0.7966 - val_accuracy: 0.8164
Epoch 66/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5015 - accuracy: 0.8637 - val_loss: 0.6750 - val_accuracy: 0.8164
Epoch 67/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4885 - accuracy: 0.8736 - val_loss: 0.7238 - val_accuracy: 0.8164
Epoch 68/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4829 - accuracy: 0.8736 - val_loss: 0.6461 - val_accuracy: 0.8164
Epoch 69/100
5/5 [==============================] - 0s 10ms/step - loss: 0.5012 - accuracy: 0.8752 - val_loss: 0.6384 - val_accuracy: 0.8164
Epoch 70/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4911 - accuracy: 0.8703 - val_loss: 0.6933 - val_accuracy: 0.8164
Epoch 71/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4646 - accuracy: 0.8752 - val_loss: 0.6397 - val_accuracy: 0.8164
Epoch 72/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4950 - accuracy: 0.8719 - val_loss: 0.6498 - val_accuracy: 0.8164
Epoch 73/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4818 - accuracy: 0.8654 - val_loss: 0.6483 - val_accuracy: 0.8164
Epoch 74/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4701 - accuracy: 0.8801 - val_loss: 0.6560 - val_accuracy: 0.8164
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4892 - accuracy: 0.8703 - val_loss: 0.6651 - val_accuracy: 0.8164
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4730 - accuracy: 0.8801 - val_loss: 0.6272 - val_accuracy: 0.8164
Epoch 77/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4705 - accuracy: 0.8736 - val_loss: 0.6437 - val_accuracy: 0.8164
Epoch 78/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4852 - accuracy: 0.8736 - val_loss: 0.6327 - val_accuracy: 0.8164
Epoch 79/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4905 - accuracy: 0.8703 - val_loss: 0.5552 - val_accuracy: 0.8164
Epoch 80/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4707 - accuracy: 0.8752 - val_loss: 0.5894 - val_accuracy: 0.8164
Epoch 81/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4698 - accuracy: 0.8785 - val_loss: 0.6683 - val_accuracy: 0.8164
Epoch 82/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4875 - accuracy: 0.8818 - val_loss: 0.6099 - val_accuracy: 0.8164
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4979 - accuracy: 0.8555 - val_loss: 0.5947 - val_accuracy: 0.8164
Epoch 84/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4786 - accuracy: 0.8719 - val_loss: 0.6049 - val_accuracy: 0.8164
Epoch 85/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4880 - accuracy: 0.8637 - val_loss: 0.5623 - val_accuracy: 0.8164
Epoch 86/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4785 - accuracy: 0.8768 - val_loss: 0.5922 - val_accuracy: 0.8164
Epoch 87/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4587 - accuracy: 0.8785 - val_loss: 0.7083 - val_accuracy: 0.8164
Epoch 88/100
5/5 [==============================] - 0s 9ms/step - loss: 0.4813 - accuracy: 0.8801 - val_loss: 0.5977 - val_accuracy: 0.8164
Epoch 89/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4573 - accuracy: 0.8719 - val_loss: 0.5596 - val_accuracy: 0.8295
Epoch 90/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4861 - accuracy: 0.8654 - val_loss: 0.6192 - val_accuracy: 0.8164
Epoch 91/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4855 - accuracy: 0.8736 - val_loss: 0.5770 - val_accuracy: 0.8164
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4696 - accuracy: 0.8736 - val_loss: 0.5551 - val_accuracy: 0.8164
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4703 - accuracy: 0.8719 - val_loss: 0.6466 - val_accuracy: 0.8164
Epoch 94/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5000 - accuracy: 0.8654 - val_loss: 0.6458 - val_accuracy: 0.8164
Epoch 95/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4754 - accuracy: 0.8752 - val_loss: 0.6431 - val_accuracy: 0.8164
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4630 - accuracy: 0.8670 - val_loss: 0.5294 - val_accuracy: 0.8295
Epoch 97/100
5/5 [==============================] - 0s 17ms/step - loss: 0.4789 - accuracy: 0.8703 - val_loss: 0.5639 - val_accuracy: 0.8295
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4830 - accuracy: 0.8670 - val_loss: 0.5587 - val_accuracy: 0.8262
Epoch 99/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4851 - accuracy: 0.8686 - val_loss: 0.5140 - val_accuracy: 0.8492
Epoch 100/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4806 - accuracy: 0.8719 - val_loss: 0.5677 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 1, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 63ms/step - loss: 3.5881 - accuracy: 0.5304 - val_loss: 2.1687 - val_accuracy: 0.8721
Epoch 2/100
5/5 [==============================] - 0s 13ms/step - loss: 2.2892 - accuracy: 0.7291 - val_loss: 1.7477 - val_accuracy: 0.8721
Epoch 3/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8662 - accuracy: 0.7833 - val_loss: 1.4690 - val_accuracy: 0.8721
Epoch 4/100
5/5 [==============================] - 0s 12ms/step - loss: 1.4566 - accuracy: 0.8325 - val_loss: 1.2330 - val_accuracy: 0.8721
Epoch 5/100
5/5 [==============================] - 0s 13ms/step - loss: 1.3082 - accuracy: 0.8424 - val_loss: 1.1347 - val_accuracy: 0.8721
Epoch 6/100
5/5 [==============================] - 0s 16ms/step - loss: 1.0993 - accuracy: 0.8276 - val_loss: 1.0349 - val_accuracy: 0.8721
Epoch 7/100
5/5 [==============================] - 0s 13ms/step - loss: 0.9498 - accuracy: 0.8473 - val_loss: 0.8760 - val_accuracy: 0.8721
Epoch 8/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8629 - accuracy: 0.8489 - val_loss: 0.8984 - val_accuracy: 0.8721
Epoch 9/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7879 - accuracy: 0.8670 - val_loss: 0.8432 - val_accuracy: 0.8721
Epoch 10/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7437 - accuracy: 0.8506 - val_loss: 0.7295 - val_accuracy: 0.8721
Epoch 11/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7184 - accuracy: 0.8391 - val_loss: 0.6753 - val_accuracy: 0.8721
Epoch 12/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6384 - accuracy: 0.8621 - val_loss: 0.6467 - val_accuracy: 0.8721
Epoch 13/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6472 - accuracy: 0.8407 - val_loss: 0.6863 - val_accuracy: 0.8721
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6264 - accuracy: 0.8588 - val_loss: 0.6863 - val_accuracy: 0.8721
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5883 - accuracy: 0.8555 - val_loss: 0.6040 - val_accuracy: 0.8721
Epoch 16/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5997 - accuracy: 0.8522 - val_loss: 0.5913 - val_accuracy: 0.8721
Epoch 17/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5700 - accuracy: 0.8555 - val_loss: 0.6076 - val_accuracy: 0.8721
Epoch 18/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5603 - accuracy: 0.8555 - val_loss: 0.6466 - val_accuracy: 0.8721
Epoch 19/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5863 - accuracy: 0.8358 - val_loss: 0.6356 - val_accuracy: 0.8721
Epoch 20/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5727 - accuracy: 0.8539 - val_loss: 0.5708 - val_accuracy: 0.8721
Epoch 21/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6107 - accuracy: 0.8391 - val_loss: 0.5853 - val_accuracy: 0.8721
Epoch 22/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5744 - accuracy: 0.8571 - val_loss: 0.5760 - val_accuracy: 0.8721
Epoch 23/100
5/5 [==============================] - 0s 17ms/step - loss: 0.5882 - accuracy: 0.8342 - val_loss: 0.5806 - val_accuracy: 0.8721
Epoch 24/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5733 - accuracy: 0.8424 - val_loss: 0.6280 - val_accuracy: 0.8721
Epoch 25/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5754 - accuracy: 0.8456 - val_loss: 0.6207 - val_accuracy: 0.8721
Epoch 26/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5571 - accuracy: 0.8473 - val_loss: 0.5890 - val_accuracy: 0.8721
Epoch 27/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5636 - accuracy: 0.8391 - val_loss: 0.5933 - val_accuracy: 0.8721
Epoch 28/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5653 - accuracy: 0.8473 - val_loss: 0.5597 - val_accuracy: 0.8721
Epoch 29/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5467 - accuracy: 0.8407 - val_loss: 0.5457 - val_accuracy: 0.8721
Epoch 30/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5732 - accuracy: 0.8276 - val_loss: 0.5746 - val_accuracy: 0.8721
Epoch 31/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5567 - accuracy: 0.8407 - val_loss: 0.5517 - val_accuracy: 0.8721
Epoch 32/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5414 - accuracy: 0.8654 - val_loss: 0.5618 - val_accuracy: 0.8721
Epoch 33/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5350 - accuracy: 0.8473 - val_loss: 0.5627 - val_accuracy: 0.8721
Epoch 34/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5247 - accuracy: 0.8571 - val_loss: 0.5202 - val_accuracy: 0.8721
Epoch 35/100
5/5 [==============================] - 0s 15ms/step - loss: 0.5647 - accuracy: 0.8325 - val_loss: 0.5723 - val_accuracy: 0.8721
Epoch 36/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5263 - accuracy: 0.8654 - val_loss: 0.5933 - val_accuracy: 0.8721
Epoch 37/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5245 - accuracy: 0.8571 - val_loss: 0.5576 - val_accuracy: 0.8721
Epoch 38/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5429 - accuracy: 0.8571 - val_loss: 0.5196 - val_accuracy: 0.8721
Epoch 39/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5650 - accuracy: 0.8424 - val_loss: 0.5695 - val_accuracy: 0.8721
Epoch 40/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5286 - accuracy: 0.8588 - val_loss: 0.5671 - val_accuracy: 0.8721
Epoch 41/100
5/5 [==============================] - 0s 10ms/step - loss: 0.5504 - accuracy: 0.8456 - val_loss: 0.5462 - val_accuracy: 0.8721
Epoch 42/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5400 - accuracy: 0.8539 - val_loss: 0.5804 - val_accuracy: 0.8721
Epoch 43/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5462 - accuracy: 0.8358 - val_loss: 0.5258 - val_accuracy: 0.8721
Epoch 44/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5548 - accuracy: 0.8456 - val_loss: 0.5245 - val_accuracy: 0.8721
Epoch 45/100
5/5 [==============================] - 0s 17ms/step - loss: 0.5631 - accuracy: 0.8325 - val_loss: 0.5565 - val_accuracy: 0.8721
Epoch 46/100
5/5 [==============================] - 0s 15ms/step - loss: 0.5431 - accuracy: 0.8407 - val_loss: 0.5533 - val_accuracy: 0.8721
Epoch 47/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5217 - accuracy: 0.8555 - val_loss: 0.5295 - val_accuracy: 0.8721
Epoch 48/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5217 - accuracy: 0.8555 - val_loss: 0.5031 - val_accuracy: 0.8721
Epoch 49/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5396 - accuracy: 0.8407 - val_loss: 0.5471 - val_accuracy: 0.8721
Epoch 50/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5121 - accuracy: 0.8736 - val_loss: 0.5473 - val_accuracy: 0.8721
Epoch 51/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5370 - accuracy: 0.8506 - val_loss: 0.5459 - val_accuracy: 0.8721
Epoch 52/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5644 - accuracy: 0.8440 - val_loss: 0.5372 - val_accuracy: 0.8721
Epoch 53/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5326 - accuracy: 0.8539 - val_loss: 0.5441 - val_accuracy: 0.8721
Epoch 54/100
5/5 [==============================] - 0s 17ms/step - loss: 0.5122 - accuracy: 0.8522 - val_loss: 0.5098 - val_accuracy: 0.8721
Epoch 55/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5413 - accuracy: 0.8424 - val_loss: 0.5408 - val_accuracy: 0.8721
Epoch 56/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5441 - accuracy: 0.8424 - val_loss: 0.5231 - val_accuracy: 0.8721
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5239 - accuracy: 0.8506 - val_loss: 0.5424 - val_accuracy: 0.8721
Epoch 58/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5273 - accuracy: 0.8456 - val_loss: 0.5028 - val_accuracy: 0.8721
Epoch 59/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5200 - accuracy: 0.8489 - val_loss: 0.5567 - val_accuracy: 0.8721
Epoch 60/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5325 - accuracy: 0.8670 - val_loss: 0.5276 - val_accuracy: 0.8721
Epoch 61/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5310 - accuracy: 0.8506 - val_loss: 0.4966 - val_accuracy: 0.8721
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5158 - accuracy: 0.8670 - val_loss: 0.5566 - val_accuracy: 0.8721
Epoch 63/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5480 - accuracy: 0.8473 - val_loss: 0.4883 - val_accuracy: 0.8721
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5467 - accuracy: 0.8440 - val_loss: 0.4914 - val_accuracy: 0.8721
Epoch 65/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5171 - accuracy: 0.8456 - val_loss: 0.4959 - val_accuracy: 0.8721
Epoch 66/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5170 - accuracy: 0.8571 - val_loss: 0.5361 - val_accuracy: 0.8721
Epoch 67/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5275 - accuracy: 0.8342 - val_loss: 0.4721 - val_accuracy: 0.8721
Epoch 68/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5432 - accuracy: 0.8440 - val_loss: 0.4878 - val_accuracy: 0.8721
Epoch 69/100
5/5 [==============================] - 0s 10ms/step - loss: 0.5207 - accuracy: 0.8456 - val_loss: 0.4892 - val_accuracy: 0.8721
Epoch 70/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5362 - accuracy: 0.8522 - val_loss: 0.4953 - val_accuracy: 0.8721
Epoch 71/100
5/5 [==============================] - 0s 18ms/step - loss: 0.5338 - accuracy: 0.8309 - val_loss: 0.5013 - val_accuracy: 0.8721
Epoch 72/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5196 - accuracy: 0.8571 - val_loss: 0.5092 - val_accuracy: 0.8721
Epoch 73/100
5/5 [==============================] - 0s 15ms/step - loss: 0.5326 - accuracy: 0.8440 - val_loss: 0.4719 - val_accuracy: 0.8721
Epoch 74/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5259 - accuracy: 0.8637 - val_loss: 0.4976 - val_accuracy: 0.8721
Epoch 75/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5117 - accuracy: 0.8555 - val_loss: 0.4582 - val_accuracy: 0.8721
Epoch 76/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5319 - accuracy: 0.8604 - val_loss: 0.4960 - val_accuracy: 0.8721
Epoch 77/100
5/5 [==============================] - 0s 15ms/step - loss: 0.5100 - accuracy: 0.8522 - val_loss: 0.4844 - val_accuracy: 0.8721
Epoch 78/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5368 - accuracy: 0.8555 - val_loss: 0.4682 - val_accuracy: 0.8721
Epoch 79/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5126 - accuracy: 0.8588 - val_loss: 0.5196 - val_accuracy: 0.8721
Epoch 80/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5414 - accuracy: 0.8374 - val_loss: 0.4972 - val_accuracy: 0.8721
Epoch 81/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5328 - accuracy: 0.8391 - val_loss: 0.4799 - val_accuracy: 0.8721
Epoch 82/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5201 - accuracy: 0.8571 - val_loss: 0.4637 - val_accuracy: 0.8721
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5120 - accuracy: 0.8407 - val_loss: 0.4821 - val_accuracy: 0.8721
Epoch 84/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5201 - accuracy: 0.8440 - val_loss: 0.4568 - val_accuracy: 0.8721
Epoch 85/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5347 - accuracy: 0.8358 - val_loss: 0.4688 - val_accuracy: 0.8721
Epoch 86/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5586 - accuracy: 0.8259 - val_loss: 0.4585 - val_accuracy: 0.8721
Epoch 87/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5152 - accuracy: 0.8489 - val_loss: 0.4613 - val_accuracy: 0.8721
Epoch 88/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5168 - accuracy: 0.8374 - val_loss: 0.4612 - val_accuracy: 0.8721
Epoch 89/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5177 - accuracy: 0.8424 - val_loss: 0.5125 - val_accuracy: 0.8721
Epoch 90/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5339 - accuracy: 0.8473 - val_loss: 0.4799 - val_accuracy: 0.8721
Epoch 91/100
5/5 [==============================] - 0s 15ms/step - loss: 0.5042 - accuracy: 0.8588 - val_loss: 0.4780 - val_accuracy: 0.8721
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5151 - accuracy: 0.8588 - val_loss: 0.5287 - val_accuracy: 0.8721
Epoch 93/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5384 - accuracy: 0.8276 - val_loss: 0.4605 - val_accuracy: 0.8721
Epoch 94/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5081 - accuracy: 0.8571 - val_loss: 0.5094 - val_accuracy: 0.8721
Epoch 95/100
5/5 [==============================] - 0s 17ms/step - loss: 0.5274 - accuracy: 0.8407 - val_loss: 0.4605 - val_accuracy: 0.8721
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5214 - accuracy: 0.8473 - val_loss: 0.4487 - val_accuracy: 0.8787
Epoch 97/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5234 - accuracy: 0.8539 - val_loss: 0.4508 - val_accuracy: 0.8885
Epoch 98/100
5/5 [==============================] - 0s 15ms/step - loss: 0.5227 - accuracy: 0.8621 - val_loss: 0.4504 - val_accuracy: 0.8885
Epoch 99/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5035 - accuracy: 0.8506 - val_loss: 0.4475 - val_accuracy: 0.8918
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5388 - accuracy: 0.8571 - val_loss: 0.4519 - val_accuracy: 0.8754
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 1, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 128
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
5/5 [==============================] - 1s 65ms/step - loss: 3.4520 - accuracy: 0.5869 - val_loss: 2.1824 - val_accuracy: 0.8586
Epoch 2/100
5/5 [==============================] - 0s 18ms/step - loss: 2.3145 - accuracy: 0.7410 - val_loss: 1.7659 - val_accuracy: 0.8618
Epoch 3/100
5/5 [==============================] - 0s 10ms/step - loss: 1.7849 - accuracy: 0.8213 - val_loss: 1.4888 - val_accuracy: 0.8618
Epoch 4/100
5/5 [==============================] - 0s 14ms/step - loss: 1.4962 - accuracy: 0.8246 - val_loss: 1.3147 - val_accuracy: 0.8618
Epoch 5/100
5/5 [==============================] - 0s 13ms/step - loss: 1.1668 - accuracy: 0.8803 - val_loss: 1.1338 - val_accuracy: 0.8618
Epoch 6/100
5/5 [==============================] - 0s 15ms/step - loss: 0.9796 - accuracy: 0.8738 - val_loss: 1.1138 - val_accuracy: 0.8618
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9971 - accuracy: 0.8410 - val_loss: 0.9381 - val_accuracy: 0.8618
Epoch 8/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8290 - accuracy: 0.8557 - val_loss: 0.8910 - val_accuracy: 0.8618
Epoch 9/100
5/5 [==============================] - 0s 15ms/step - loss: 0.7590 - accuracy: 0.8623 - val_loss: 0.8877 - val_accuracy: 0.8618
Epoch 10/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6835 - accuracy: 0.8607 - val_loss: 0.7459 - val_accuracy: 0.8618
Epoch 11/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6697 - accuracy: 0.8672 - val_loss: 0.7166 - val_accuracy: 0.8618
Epoch 12/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5777 - accuracy: 0.8770 - val_loss: 0.7407 - val_accuracy: 0.8618
Epoch 13/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5852 - accuracy: 0.8738 - val_loss: 0.6894 - val_accuracy: 0.8618
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5565 - accuracy: 0.8738 - val_loss: 0.7076 - val_accuracy: 0.8618
Epoch 15/100
5/5 [==============================] - 0s 15ms/step - loss: 0.5145 - accuracy: 0.8820 - val_loss: 0.6563 - val_accuracy: 0.8618
Epoch 16/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5374 - accuracy: 0.8705 - val_loss: 0.6451 - val_accuracy: 0.8618
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5452 - accuracy: 0.8656 - val_loss: 0.7058 - val_accuracy: 0.8618
Epoch 18/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5575 - accuracy: 0.8508 - val_loss: 0.6974 - val_accuracy: 0.8618
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5136 - accuracy: 0.8852 - val_loss: 0.6279 - val_accuracy: 0.8618
Epoch 20/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5025 - accuracy: 0.8770 - val_loss: 0.6510 - val_accuracy: 0.8618
Epoch 21/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5081 - accuracy: 0.8754 - val_loss: 0.6423 - val_accuracy: 0.8618
Epoch 22/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5167 - accuracy: 0.8623 - val_loss: 0.6903 - val_accuracy: 0.8618
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5199 - accuracy: 0.8738 - val_loss: 0.6742 - val_accuracy: 0.8618
Epoch 24/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5106 - accuracy: 0.8754 - val_loss: 0.6565 - val_accuracy: 0.8618
Epoch 25/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5287 - accuracy: 0.8639 - val_loss: 0.6438 - val_accuracy: 0.8618
Epoch 26/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5139 - accuracy: 0.8803 - val_loss: 0.6946 - val_accuracy: 0.8618
Epoch 27/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4998 - accuracy: 0.8787 - val_loss: 0.6942 - val_accuracy: 0.8618
Epoch 28/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4935 - accuracy: 0.8787 - val_loss: 0.6503 - val_accuracy: 0.8618
Epoch 29/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4656 - accuracy: 0.8836 - val_loss: 0.6646 - val_accuracy: 0.8618
Epoch 30/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4885 - accuracy: 0.8623 - val_loss: 0.6340 - val_accuracy: 0.8618
Epoch 31/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5012 - accuracy: 0.8639 - val_loss: 0.6182 - val_accuracy: 0.8618
Epoch 32/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4641 - accuracy: 0.8803 - val_loss: 0.5766 - val_accuracy: 0.8618
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4813 - accuracy: 0.8623 - val_loss: 0.6334 - val_accuracy: 0.8618
Epoch 34/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4992 - accuracy: 0.8574 - val_loss: 0.6225 - val_accuracy: 0.8618
Epoch 35/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4919 - accuracy: 0.8803 - val_loss: 0.6159 - val_accuracy: 0.8618
Epoch 36/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4985 - accuracy: 0.8689 - val_loss: 0.6725 - val_accuracy: 0.8618
Epoch 37/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4852 - accuracy: 0.8934 - val_loss: 0.6325 - val_accuracy: 0.8618
Epoch 38/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4789 - accuracy: 0.8902 - val_loss: 0.6354 - val_accuracy: 0.8618
Epoch 39/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4819 - accuracy: 0.8852 - val_loss: 0.6448 - val_accuracy: 0.8618
Epoch 40/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4752 - accuracy: 0.8852 - val_loss: 0.6210 - val_accuracy: 0.8618
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4828 - accuracy: 0.8820 - val_loss: 0.5906 - val_accuracy: 0.8618
Epoch 42/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4702 - accuracy: 0.8836 - val_loss: 0.6211 - val_accuracy: 0.8618
Epoch 43/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5203 - accuracy: 0.8623 - val_loss: 0.5864 - val_accuracy: 0.8618
Epoch 44/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4575 - accuracy: 0.8820 - val_loss: 0.5713 - val_accuracy: 0.8618
Epoch 45/100
5/5 [==============================] - 0s 9ms/step - loss: 0.4785 - accuracy: 0.8721 - val_loss: 0.5809 - val_accuracy: 0.8618
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4590 - accuracy: 0.8902 - val_loss: 0.6600 - val_accuracy: 0.8618
Epoch 47/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4755 - accuracy: 0.8820 - val_loss: 0.6101 - val_accuracy: 0.8618
Epoch 48/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4820 - accuracy: 0.8672 - val_loss: 0.6468 - val_accuracy: 0.8618
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4777 - accuracy: 0.8820 - val_loss: 0.6308 - val_accuracy: 0.8618
Epoch 50/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4885 - accuracy: 0.8705 - val_loss: 0.5765 - val_accuracy: 0.8618
Epoch 51/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4929 - accuracy: 0.8754 - val_loss: 0.5849 - val_accuracy: 0.8618
Epoch 52/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4677 - accuracy: 0.8623 - val_loss: 0.6433 - val_accuracy: 0.8618
Epoch 53/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4699 - accuracy: 0.8836 - val_loss: 0.6157 - val_accuracy: 0.8618
Epoch 54/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4844 - accuracy: 0.8721 - val_loss: 0.5852 - val_accuracy: 0.8618
Epoch 55/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4729 - accuracy: 0.8754 - val_loss: 0.6567 - val_accuracy: 0.8618
Epoch 56/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4733 - accuracy: 0.8820 - val_loss: 0.6317 - val_accuracy: 0.8618
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4961 - accuracy: 0.8574 - val_loss: 0.5788 - val_accuracy: 0.8618
Epoch 58/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4771 - accuracy: 0.8689 - val_loss: 0.6075 - val_accuracy: 0.8618
Epoch 59/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4677 - accuracy: 0.8820 - val_loss: 0.6047 - val_accuracy: 0.8618
Epoch 60/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4805 - accuracy: 0.8689 - val_loss: 0.5856 - val_accuracy: 0.8618
Epoch 61/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4898 - accuracy: 0.8738 - val_loss: 0.5756 - val_accuracy: 0.8618
Epoch 62/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4626 - accuracy: 0.8770 - val_loss: 0.5846 - val_accuracy: 0.8618
Epoch 63/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4679 - accuracy: 0.8820 - val_loss: 0.5921 - val_accuracy: 0.8618
Epoch 64/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4956 - accuracy: 0.8672 - val_loss: 0.5801 - val_accuracy: 0.8618
Epoch 65/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4858 - accuracy: 0.8754 - val_loss: 0.5876 - val_accuracy: 0.8618
Epoch 66/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4560 - accuracy: 0.8934 - val_loss: 0.5930 - val_accuracy: 0.8618
Epoch 67/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4594 - accuracy: 0.8770 - val_loss: 0.5899 - val_accuracy: 0.8618
Epoch 68/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4915 - accuracy: 0.8590 - val_loss: 0.5741 - val_accuracy: 0.8618
Epoch 69/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4879 - accuracy: 0.8770 - val_loss: 0.5683 - val_accuracy: 0.8618
Epoch 70/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4662 - accuracy: 0.8885 - val_loss: 0.5930 - val_accuracy: 0.8618
Epoch 71/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4888 - accuracy: 0.8738 - val_loss: 0.6270 - val_accuracy: 0.8618
Epoch 72/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4746 - accuracy: 0.8705 - val_loss: 0.5966 - val_accuracy: 0.8618
Epoch 73/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4862 - accuracy: 0.8672 - val_loss: 0.5666 - val_accuracy: 0.8618
Epoch 74/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4970 - accuracy: 0.8689 - val_loss: 0.5867 - val_accuracy: 0.8618
Epoch 75/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4651 - accuracy: 0.8803 - val_loss: 0.5868 - val_accuracy: 0.8618
Epoch 76/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4993 - accuracy: 0.8541 - val_loss: 0.5881 - val_accuracy: 0.8618
Epoch 77/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4686 - accuracy: 0.8803 - val_loss: 0.5586 - val_accuracy: 0.8553
Epoch 78/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4635 - accuracy: 0.8705 - val_loss: 0.5822 - val_accuracy: 0.8618
Epoch 79/100
5/5 [==============================] - 0s 9ms/step - loss: 0.4838 - accuracy: 0.8541 - val_loss: 0.5705 - val_accuracy: 0.8586
Epoch 80/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4767 - accuracy: 0.8738 - val_loss: 0.5886 - val_accuracy: 0.8618
Epoch 81/100
5/5 [==============================] - 0s 9ms/step - loss: 0.4659 - accuracy: 0.8689 - val_loss: 0.5481 - val_accuracy: 0.8586
Epoch 82/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4676 - accuracy: 0.8705 - val_loss: 0.6154 - val_accuracy: 0.8618
Epoch 83/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4682 - accuracy: 0.8787 - val_loss: 0.5799 - val_accuracy: 0.8618
Epoch 84/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4730 - accuracy: 0.8738 - val_loss: 0.5866 - val_accuracy: 0.8618
Epoch 85/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4561 - accuracy: 0.8738 - val_loss: 0.5745 - val_accuracy: 0.8618
Epoch 86/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4664 - accuracy: 0.8787 - val_loss: 0.5957 - val_accuracy: 0.8618
Epoch 87/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4563 - accuracy: 0.8918 - val_loss: 0.5681 - val_accuracy: 0.8520
Epoch 88/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4652 - accuracy: 0.8705 - val_loss: 0.5610 - val_accuracy: 0.8553
Epoch 89/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4810 - accuracy: 0.8820 - val_loss: 0.5568 - val_accuracy: 0.8355
Epoch 90/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4617 - accuracy: 0.8885 - val_loss: 0.5730 - val_accuracy: 0.8618
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4749 - accuracy: 0.8820 - val_loss: 0.5689 - val_accuracy: 0.8618
Epoch 92/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4658 - accuracy: 0.8902 - val_loss: 0.5762 - val_accuracy: 0.8520
Epoch 93/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4468 - accuracy: 0.8984 - val_loss: 0.5961 - val_accuracy: 0.8586
Epoch 94/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4704 - accuracy: 0.8770 - val_loss: 0.5611 - val_accuracy: 0.8586
Epoch 95/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4482 - accuracy: 0.8852 - val_loss: 0.5687 - val_accuracy: 0.8520
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4808 - accuracy: 0.8754 - val_loss: 0.5745 - val_accuracy: 0.8586
Epoch 97/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4856 - accuracy: 0.8754 - val_loss: 0.5607 - val_accuracy: 0.8454
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4627 - accuracy: 0.8820 - val_loss: 0.5767 - val_accuracy: 0.8553
Epoch 99/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4723 - accuracy: 0.8820 - val_loss: 0.5619 - val_accuracy: 0.8553
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4651 - accuracy: 0.8590 - val_loss: 0.5623 - val_accuracy: 0.8553
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Best score: 0.8501222318090308
Best parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 64, 'batch_size': 512, 'learning_rate_decay': 1e-06, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.3, 'momentum': 0.99, 'batch_norm': True, 'initializers': 'glorot_uniform'}
Best model is in 10 experiment

Experiment 3 Result Analysis¶

The inclusion of weight initialization in the training process seems to have had an interesting, yet not entirely positive, impact on model performance.

  • Still No Significant Improvement on Accuracy

    Adding weight initialization did not lead to a substantial increase in model accuracy. This could suggest the model's performance could be bounded by other factors, such as the need for a more sophisticated model architecture or more representative training data.

  • Best Performance Peaked Early

    I observed that the model's best performance occurred before the end of training is indicative of the fact that at some point, further training leads to overfitting or is no longer beneficial. By including early stopping in the training process, halt training when the model's performance on the validation set begins to degrade, would be helpful prevent overfitting.

  • K-Fold Cross-Validation Variation

    In this case, varying the number of folds in K-Fold cross-validation didn't make much difference. This is might be a good sign, suggesting that the model is not sensitive to the specific splits of the data. I will choose to use 3 folds for cross-validation is a practical decision that will reduce computational load.

Experiment 4: Kfold = 3, batch_normalization, weight initialization, early-stopping¶

In [71]:
from keras.callbacks import EarlyStopping
# I am not sure how to include early stopping into my model. I asked GPT4, accessed on Jan 29th.

early_stopping = EarlyStopping(monitor='val_loss',  # Monitor validation loss
                               patience=10,         # Number of epochs with no improvement after which training will be stopped
                               verbose=1,           # To display messages
                               restore_best_weights=True)  # Restores model weights from the epoch with the best value of the monitored quantity.
In [72]:
n_iter = 10
best_score = 0
best_params = {}

for i in range(n_iter):
    print(f"Experiment number: {i+1}")
    sampled_params = {k: np.random.choice(list(v)) for k,v in param_space.items()} # use random search
    model_params = {k:v for k, v in sampled_params.items() if k != 'batch_size'}
    if model_params['optimizer'] != 'momentum':
        model_params['momentum'] = None
    if model_params['optimizer'] != 'Adam':
        model_params['adam_beta_1'] = None
        model_params['adam_beta_2'] = None
    if model_params['optimizer'] != 'RMSprop':
        model_params['rho'] = None

    cv_scores = []
    for train_index, val_index in cross_validator.split(X_train): # I am confused about the data splits here, asked GPT4, accessed on Jan 27th
        X_current_train, X_val = X_train[train_index], X_train[val_index]
        y_current_train, y_val = y_train[train_index], y_train[val_index]
        model = create_model(**model_params)
        print("Model parameters:", model_params)
        print("Batch size:", sampled_params['batch_size'])
        print("X_current_train shape:", X_current_train.shape)
        print("y_current_train shape:", y_current_train.shape)
        history = model.fit(
            X_current_train, y_current_train, 
            epochs=100, 
            batch_size=sampled_params['batch_size'],
            verbose=1,
            validation_data=(X_val, y_val),
            callbacks=[early_stopping]
        )
        plot_loss(history)
        plot_accuracy(history)
        y_val_pred = model.predict(X_val) # the evaluation and scoring part, I am not sure which libraries to use. Asked GPT4, accessed on Jan 27th
        y_val_pred_classes = np.argmax(y_val_pred, axis=1)
        y_true_classes = np.argmax(y_val, axis=1)
        
        scoring = accuracy_score(y_true_classes, y_val_pred_classes)
        cv_scores.append(scoring)
    mean_cv_scores = np.mean(cv_scores)
        
    if mean_cv_scores > best_score:
        best_score = mean_cv_scores
        if sampled_params['optimizer'] == 'momentum':
            sampled_params['adam_beta_1'] = None
            sampled_params['adam_beta_2'] = None
            sampled_params['rho'] = None
        if sampled_params['optimizer'] == 'RMSprop':
            sampled_params['adam_beta_1'] = None
            sampled_params['adam_beta_2'] = None
            sampled_params['momentum'] = None
        if sampled_params['optimizer'] == 'Adam':
            sampled_params['momentum'] = None
            sampled_params['rho'] = None
        best_params = {k: v for k, v in sampled_params.items() if v is not None}
               
print("Best score:", best_score)
print("Best parameters:", best_params)
print(f"Best model is in {i+1} experiment")

Experiment number: 1
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'random_uniform'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 2s 88ms/step - loss: 11.3030 - accuracy: 0.3498 - val_loss: 11.0709 - val_accuracy: 0.2852
Epoch 2/100
5/5 [==============================] - 0s 17ms/step - loss: 10.9112 - accuracy: 0.4598 - val_loss: 10.7110 - val_accuracy: 0.5016
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 10.5445 - accuracy: 0.5271 - val_loss: 10.3579 - val_accuracy: 0.6361
Epoch 4/100
5/5 [==============================] - 0s 17ms/step - loss: 10.1921 - accuracy: 0.5665 - val_loss: 10.0105 - val_accuracy: 0.6951
Epoch 5/100
5/5 [==============================] - 0s 17ms/step - loss: 9.8383 - accuracy: 0.6190 - val_loss: 9.6669 - val_accuracy: 0.7508
Epoch 6/100
5/5 [==============================] - 0s 16ms/step - loss: 9.5102 - accuracy: 0.6108 - val_loss: 9.3295 - val_accuracy: 0.7770
Epoch 7/100
5/5 [==============================] - 0s 18ms/step - loss: 9.1678 - accuracy: 0.6617 - val_loss: 9.0019 - val_accuracy: 0.8033
Epoch 8/100
5/5 [==============================] - 0s 16ms/step - loss: 8.8463 - accuracy: 0.6782 - val_loss: 8.6782 - val_accuracy: 0.7967
Epoch 9/100
5/5 [==============================] - 0s 16ms/step - loss: 8.5277 - accuracy: 0.6700 - val_loss: 8.3598 - val_accuracy: 0.8197
Epoch 10/100
5/5 [==============================] - 0s 17ms/step - loss: 8.2100 - accuracy: 0.6897 - val_loss: 8.0467 - val_accuracy: 0.8328
Epoch 11/100
5/5 [==============================] - 0s 16ms/step - loss: 7.9053 - accuracy: 0.6814 - val_loss: 7.7417 - val_accuracy: 0.8328
Epoch 12/100
5/5 [==============================] - 0s 16ms/step - loss: 7.5844 - accuracy: 0.7176 - val_loss: 7.4404 - val_accuracy: 0.8426
Epoch 13/100
5/5 [==============================] - 0s 13ms/step - loss: 7.2895 - accuracy: 0.7225 - val_loss: 7.1431 - val_accuracy: 0.8557
Epoch 14/100
5/5 [==============================] - 0s 14ms/step - loss: 7.0005 - accuracy: 0.7406 - val_loss: 6.8507 - val_accuracy: 0.8754
Epoch 15/100
5/5 [==============================] - 0s 16ms/step - loss: 6.7041 - accuracy: 0.7471 - val_loss: 6.5601 - val_accuracy: 0.8656
Epoch 16/100
5/5 [==============================] - 0s 15ms/step - loss: 6.4215 - accuracy: 0.7307 - val_loss: 6.2732 - val_accuracy: 0.8426
Epoch 17/100
5/5 [==============================] - 0s 14ms/step - loss: 6.1381 - accuracy: 0.7471 - val_loss: 5.9928 - val_accuracy: 0.8426
Epoch 18/100
5/5 [==============================] - 0s 13ms/step - loss: 5.8519 - accuracy: 0.7570 - val_loss: 5.7164 - val_accuracy: 0.8361
Epoch 19/100
5/5 [==============================] - 0s 14ms/step - loss: 5.5642 - accuracy: 0.7701 - val_loss: 5.4450 - val_accuracy: 0.8361
Epoch 20/100
5/5 [==============================] - 0s 19ms/step - loss: 5.3231 - accuracy: 0.7668 - val_loss: 5.1819 - val_accuracy: 0.8295
Epoch 21/100
5/5 [==============================] - 0s 17ms/step - loss: 5.0718 - accuracy: 0.7718 - val_loss: 4.9209 - val_accuracy: 0.8164
Epoch 22/100
5/5 [==============================] - 0s 18ms/step - loss: 4.7929 - accuracy: 0.7947 - val_loss: 4.6670 - val_accuracy: 0.8164
Epoch 23/100
5/5 [==============================] - 0s 16ms/step - loss: 4.5532 - accuracy: 0.7915 - val_loss: 4.4229 - val_accuracy: 0.8164
Epoch 24/100
5/5 [==============================] - 0s 16ms/step - loss: 4.3154 - accuracy: 0.7865 - val_loss: 4.1822 - val_accuracy: 0.8164
Epoch 25/100
5/5 [==============================] - 0s 16ms/step - loss: 4.0548 - accuracy: 0.8079 - val_loss: 3.9508 - val_accuracy: 0.8164
Epoch 26/100
5/5 [==============================] - 0s 17ms/step - loss: 3.8234 - accuracy: 0.8177 - val_loss: 3.7276 - val_accuracy: 0.8164
Epoch 27/100
5/5 [==============================] - 0s 18ms/step - loss: 3.6071 - accuracy: 0.8144 - val_loss: 3.5059 - val_accuracy: 0.8164
Epoch 28/100
5/5 [==============================] - 0s 16ms/step - loss: 3.3962 - accuracy: 0.8112 - val_loss: 3.2973 - val_accuracy: 0.8164
Epoch 29/100
5/5 [==============================] - 0s 17ms/step - loss: 3.1729 - accuracy: 0.8391 - val_loss: 3.1005 - val_accuracy: 0.8164
Epoch 30/100
5/5 [==============================] - 0s 18ms/step - loss: 2.9730 - accuracy: 0.8391 - val_loss: 2.9123 - val_accuracy: 0.8164
Epoch 31/100
5/5 [==============================] - 0s 15ms/step - loss: 2.7737 - accuracy: 0.8506 - val_loss: 2.7305 - val_accuracy: 0.8164
Epoch 32/100
5/5 [==============================] - 0s 18ms/step - loss: 2.6025 - accuracy: 0.8456 - val_loss: 2.5533 - val_accuracy: 0.8164
Epoch 33/100
5/5 [==============================] - 0s 18ms/step - loss: 2.4152 - accuracy: 0.8456 - val_loss: 2.3836 - val_accuracy: 0.8164
Epoch 34/100
5/5 [==============================] - 0s 16ms/step - loss: 2.2351 - accuracy: 0.8588 - val_loss: 2.2260 - val_accuracy: 0.8164
Epoch 35/100
5/5 [==============================] - 0s 19ms/step - loss: 2.0967 - accuracy: 0.8374 - val_loss: 2.0789 - val_accuracy: 0.8164
Epoch 36/100
5/5 [==============================] - 0s 18ms/step - loss: 1.9239 - accuracy: 0.8604 - val_loss: 1.9304 - val_accuracy: 0.8164
Epoch 37/100
5/5 [==============================] - 0s 19ms/step - loss: 1.7701 - accuracy: 0.8654 - val_loss: 1.7944 - val_accuracy: 0.8164
Epoch 38/100
5/5 [==============================] - 0s 15ms/step - loss: 1.6354 - accuracy: 0.8736 - val_loss: 1.6715 - val_accuracy: 0.8164
Epoch 39/100
5/5 [==============================] - 0s 15ms/step - loss: 1.4931 - accuracy: 0.8752 - val_loss: 1.5494 - val_accuracy: 0.8164
Epoch 40/100
5/5 [==============================] - 0s 16ms/step - loss: 1.3676 - accuracy: 0.8834 - val_loss: 1.4399 - val_accuracy: 0.8164
Epoch 41/100
5/5 [==============================] - 0s 14ms/step - loss: 1.2637 - accuracy: 0.8719 - val_loss: 1.3419 - val_accuracy: 0.8164
Epoch 42/100
5/5 [==============================] - 0s 15ms/step - loss: 1.1582 - accuracy: 0.8588 - val_loss: 1.2462 - val_accuracy: 0.8164
Epoch 43/100
5/5 [==============================] - 0s 14ms/step - loss: 1.0667 - accuracy: 0.8621 - val_loss: 1.1563 - val_accuracy: 0.8164
Epoch 44/100
5/5 [==============================] - 0s 18ms/step - loss: 0.9604 - accuracy: 0.8703 - val_loss: 1.0747 - val_accuracy: 0.8164
Epoch 45/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8825 - accuracy: 0.8719 - val_loss: 0.9983 - val_accuracy: 0.8164
Epoch 46/100
5/5 [==============================] - 0s 16ms/step - loss: 0.7815 - accuracy: 0.8818 - val_loss: 0.9312 - val_accuracy: 0.8164
Epoch 47/100
5/5 [==============================] - 0s 17ms/step - loss: 0.7289 - accuracy: 0.8785 - val_loss: 0.8701 - val_accuracy: 0.8164
Epoch 48/100
5/5 [==============================] - 0s 14ms/step - loss: 0.6675 - accuracy: 0.8670 - val_loss: 0.8191 - val_accuracy: 0.8164
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6102 - accuracy: 0.8768 - val_loss: 0.7692 - val_accuracy: 0.8164
Epoch 50/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5590 - accuracy: 0.8637 - val_loss: 0.7336 - val_accuracy: 0.8164
Epoch 51/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5233 - accuracy: 0.8703 - val_loss: 0.6978 - val_accuracy: 0.8164
Epoch 52/100
5/5 [==============================] - 0s 18ms/step - loss: 0.4889 - accuracy: 0.8801 - val_loss: 0.6679 - val_accuracy: 0.8164
Epoch 53/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4673 - accuracy: 0.8703 - val_loss: 0.6538 - val_accuracy: 0.8164
Epoch 54/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4487 - accuracy: 0.8654 - val_loss: 0.6357 - val_accuracy: 0.8164
Epoch 55/100
5/5 [==============================] - 0s 17ms/step - loss: 0.4306 - accuracy: 0.8785 - val_loss: 0.6222 - val_accuracy: 0.8164
Epoch 56/100
5/5 [==============================] - 0s 18ms/step - loss: 0.4263 - accuracy: 0.8719 - val_loss: 0.6160 - val_accuracy: 0.8164
Epoch 57/100
5/5 [==============================] - 0s 17ms/step - loss: 0.4138 - accuracy: 0.8752 - val_loss: 0.6103 - val_accuracy: 0.8164
Epoch 58/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4237 - accuracy: 0.8736 - val_loss: 0.6025 - val_accuracy: 0.8164
Epoch 59/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4092 - accuracy: 0.8752 - val_loss: 0.6031 - val_accuracy: 0.8164
Epoch 60/100
5/5 [==============================] - 0s 15ms/step - loss: 0.4103 - accuracy: 0.8719 - val_loss: 0.5995 - val_accuracy: 0.8164
Epoch 61/100
5/5 [==============================] - 0s 15ms/step - loss: 0.3982 - accuracy: 0.8719 - val_loss: 0.5951 - val_accuracy: 0.8164
Epoch 62/100
5/5 [==============================] - 0s 17ms/step - loss: 0.3992 - accuracy: 0.8768 - val_loss: 0.5932 - val_accuracy: 0.8164
Epoch 63/100
5/5 [==============================] - 0s 18ms/step - loss: 0.3907 - accuracy: 0.8785 - val_loss: 0.5903 - val_accuracy: 0.8164
Epoch 64/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3929 - accuracy: 0.8703 - val_loss: 0.5852 - val_accuracy: 0.8164
Epoch 65/100
5/5 [==============================] - 0s 17ms/step - loss: 0.3840 - accuracy: 0.8719 - val_loss: 0.5800 - val_accuracy: 0.8164
Epoch 66/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3862 - accuracy: 0.8719 - val_loss: 0.5814 - val_accuracy: 0.8164
Epoch 67/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3887 - accuracy: 0.8686 - val_loss: 0.5788 - val_accuracy: 0.8164
Epoch 68/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3790 - accuracy: 0.8768 - val_loss: 0.5780 - val_accuracy: 0.8164
Epoch 69/100
5/5 [==============================] - 0s 17ms/step - loss: 0.3856 - accuracy: 0.8703 - val_loss: 0.5774 - val_accuracy: 0.8164
Epoch 70/100
5/5 [==============================] - 0s 14ms/step - loss: 0.3827 - accuracy: 0.8719 - val_loss: 0.5749 - val_accuracy: 0.8164
Epoch 71/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3853 - accuracy: 0.8785 - val_loss: 0.5754 - val_accuracy: 0.8164
Epoch 72/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3797 - accuracy: 0.8785 - val_loss: 0.5722 - val_accuracy: 0.8164
Epoch 73/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3855 - accuracy: 0.8719 - val_loss: 0.5739 - val_accuracy: 0.8164
Epoch 74/100
5/5 [==============================] - 0s 20ms/step - loss: 0.3855 - accuracy: 0.8736 - val_loss: 0.5734 - val_accuracy: 0.8164
Epoch 75/100
5/5 [==============================] - 0s 14ms/step - loss: 0.3805 - accuracy: 0.8752 - val_loss: 0.5688 - val_accuracy: 0.8164
Epoch 76/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3724 - accuracy: 0.8801 - val_loss: 0.5634 - val_accuracy: 0.8164
Epoch 77/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3845 - accuracy: 0.8768 - val_loss: 0.5591 - val_accuracy: 0.8164
Epoch 78/100
5/5 [==============================] - 0s 17ms/step - loss: 0.3784 - accuracy: 0.8670 - val_loss: 0.5586 - val_accuracy: 0.8164
Epoch 79/100
5/5 [==============================] - 0s 19ms/step - loss: 0.3759 - accuracy: 0.8736 - val_loss: 0.5604 - val_accuracy: 0.8164
Epoch 80/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3844 - accuracy: 0.8736 - val_loss: 0.5540 - val_accuracy: 0.8164
Epoch 81/100
5/5 [==============================] - 0s 15ms/step - loss: 0.3778 - accuracy: 0.8768 - val_loss: 0.5577 - val_accuracy: 0.8164
Epoch 82/100
5/5 [==============================] - 0s 14ms/step - loss: 0.3732 - accuracy: 0.8703 - val_loss: 0.5523 - val_accuracy: 0.8164
Epoch 83/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3821 - accuracy: 0.8719 - val_loss: 0.5490 - val_accuracy: 0.8164
Epoch 84/100
5/5 [==============================] - 0s 18ms/step - loss: 0.3741 - accuracy: 0.8752 - val_loss: 0.5455 - val_accuracy: 0.8164
Epoch 85/100
5/5 [==============================] - 0s 17ms/step - loss: 0.3662 - accuracy: 0.8768 - val_loss: 0.5433 - val_accuracy: 0.8164
Epoch 86/100
5/5 [==============================] - 0s 17ms/step - loss: 0.3707 - accuracy: 0.8768 - val_loss: 0.5385 - val_accuracy: 0.8164
Epoch 87/100
5/5 [==============================] - 0s 19ms/step - loss: 0.3838 - accuracy: 0.8686 - val_loss: 0.5333 - val_accuracy: 0.8164
Epoch 88/100
5/5 [==============================] - 0s 14ms/step - loss: 0.3747 - accuracy: 0.8818 - val_loss: 0.5419 - val_accuracy: 0.8164
Epoch 89/100
5/5 [==============================] - 0s 14ms/step - loss: 0.3734 - accuracy: 0.8703 - val_loss: 0.5279 - val_accuracy: 0.8164
Epoch 90/100
5/5 [==============================] - 0s 15ms/step - loss: 0.3741 - accuracy: 0.8752 - val_loss: 0.5306 - val_accuracy: 0.8164
Epoch 91/100
5/5 [==============================] - 0s 17ms/step - loss: 0.3746 - accuracy: 0.8736 - val_loss: 0.5324 - val_accuracy: 0.8164
Epoch 92/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3745 - accuracy: 0.8752 - val_loss: 0.5277 - val_accuracy: 0.8164
Epoch 93/100
5/5 [==============================] - 0s 17ms/step - loss: 0.3749 - accuracy: 0.8785 - val_loss: 0.5297 - val_accuracy: 0.8164
Epoch 94/100
5/5 [==============================] - 0s 15ms/step - loss: 0.3635 - accuracy: 0.8818 - val_loss: 0.5250 - val_accuracy: 0.8164
Epoch 95/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3737 - accuracy: 0.8736 - val_loss: 0.5202 - val_accuracy: 0.8164
Epoch 96/100
5/5 [==============================] - 0s 14ms/step - loss: 0.3658 - accuracy: 0.8801 - val_loss: 0.5192 - val_accuracy: 0.8164
Epoch 97/100
5/5 [==============================] - 0s 15ms/step - loss: 0.3783 - accuracy: 0.8752 - val_loss: 0.5123 - val_accuracy: 0.8164
Epoch 98/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3721 - accuracy: 0.8736 - val_loss: 0.5253 - val_accuracy: 0.8164
Epoch 99/100
5/5 [==============================] - 0s 16ms/step - loss: 0.3803 - accuracy: 0.8686 - val_loss: 0.5132 - val_accuracy: 0.8164
Epoch 100/100
5/5 [==============================] - 0s 14ms/step - loss: 0.3660 - accuracy: 0.8785 - val_loss: 0.5082 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'random_uniform'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 2s 84ms/step - loss: 10.8703 - accuracy: 0.3038 - val_loss: 10.6331 - val_accuracy: 0.0689
Epoch 2/100
5/5 [==============================] - 0s 16ms/step - loss: 10.4663 - accuracy: 0.4007 - val_loss: 10.2616 - val_accuracy: 0.2852
Epoch 3/100
5/5 [==============================] - 0s 17ms/step - loss: 10.1103 - accuracy: 0.4663 - val_loss: 9.8979 - val_accuracy: 0.5574
Epoch 4/100
5/5 [==============================] - 0s 16ms/step - loss: 9.7489 - accuracy: 0.5074 - val_loss: 9.5443 - val_accuracy: 0.7410
Epoch 5/100
5/5 [==============================] - 0s 15ms/step - loss: 9.4144 - accuracy: 0.5386 - val_loss: 9.2008 - val_accuracy: 0.8066
Epoch 6/100
5/5 [==============================] - 0s 14ms/step - loss: 9.0614 - accuracy: 0.5911 - val_loss: 8.8666 - val_accuracy: 0.8525
Epoch 7/100
5/5 [==============================] - 0s 13ms/step - loss: 8.7261 - accuracy: 0.6190 - val_loss: 8.5410 - val_accuracy: 0.8787
Epoch 8/100
5/5 [==============================] - 0s 14ms/step - loss: 8.4109 - accuracy: 0.6585 - val_loss: 8.2245 - val_accuracy: 0.8885
Epoch 9/100
5/5 [==============================] - 0s 13ms/step - loss: 8.0910 - accuracy: 0.6732 - val_loss: 7.9126 - val_accuracy: 0.8918
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 7.7714 - accuracy: 0.6880 - val_loss: 7.6036 - val_accuracy: 0.8951
Epoch 11/100
5/5 [==============================] - 0s 14ms/step - loss: 7.4594 - accuracy: 0.7028 - val_loss: 7.3027 - val_accuracy: 0.8984
Epoch 12/100
5/5 [==============================] - 0s 12ms/step - loss: 7.1756 - accuracy: 0.7061 - val_loss: 7.0059 - val_accuracy: 0.8984
Epoch 13/100
5/5 [==============================] - 0s 16ms/step - loss: 6.8967 - accuracy: 0.7176 - val_loss: 6.7158 - val_accuracy: 0.8918
Epoch 14/100
5/5 [==============================] - 0s 13ms/step - loss: 6.5982 - accuracy: 0.7126 - val_loss: 6.4305 - val_accuracy: 0.8951
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 6.3130 - accuracy: 0.7110 - val_loss: 6.1493 - val_accuracy: 0.9016
Epoch 16/100
5/5 [==============================] - 0s 13ms/step - loss: 6.0483 - accuracy: 0.7143 - val_loss: 5.8714 - val_accuracy: 0.8984
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 5.7684 - accuracy: 0.7061 - val_loss: 5.6060 - val_accuracy: 0.8918
Epoch 18/100
5/5 [==============================] - 0s 13ms/step - loss: 5.5292 - accuracy: 0.7258 - val_loss: 5.3474 - val_accuracy: 0.8820
Epoch 19/100
5/5 [==============================] - 0s 13ms/step - loss: 5.2645 - accuracy: 0.7438 - val_loss: 5.0945 - val_accuracy: 0.8820
Epoch 20/100
5/5 [==============================] - 0s 13ms/step - loss: 5.0220 - accuracy: 0.7389 - val_loss: 4.8471 - val_accuracy: 0.8787
Epoch 21/100
5/5 [==============================] - 0s 13ms/step - loss: 4.7624 - accuracy: 0.7635 - val_loss: 4.6044 - val_accuracy: 0.8721
Epoch 22/100
5/5 [==============================] - 0s 13ms/step - loss: 4.5095 - accuracy: 0.7767 - val_loss: 4.3685 - val_accuracy: 0.8721
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 4.2903 - accuracy: 0.7718 - val_loss: 4.1395 - val_accuracy: 0.8721
Epoch 24/100
5/5 [==============================] - 0s 13ms/step - loss: 4.0571 - accuracy: 0.7783 - val_loss: 3.9140 - val_accuracy: 0.8721
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 3.8575 - accuracy: 0.7849 - val_loss: 3.6956 - val_accuracy: 0.8721
Epoch 26/100
5/5 [==============================] - 0s 12ms/step - loss: 3.6187 - accuracy: 0.7800 - val_loss: 3.4846 - val_accuracy: 0.8721
Epoch 27/100
5/5 [==============================] - 0s 13ms/step - loss: 3.4060 - accuracy: 0.8062 - val_loss: 3.2810 - val_accuracy: 0.8721
Epoch 28/100
5/5 [==============================] - 0s 12ms/step - loss: 3.1989 - accuracy: 0.8259 - val_loss: 3.0824 - val_accuracy: 0.8721
Epoch 29/100
5/5 [==============================] - 0s 12ms/step - loss: 3.0183 - accuracy: 0.8046 - val_loss: 2.8897 - val_accuracy: 0.8721
Epoch 30/100
5/5 [==============================] - 0s 11ms/step - loss: 2.8492 - accuracy: 0.7898 - val_loss: 2.7057 - val_accuracy: 0.8721
Epoch 31/100
5/5 [==============================] - 0s 16ms/step - loss: 2.6445 - accuracy: 0.8161 - val_loss: 2.5327 - val_accuracy: 0.8721
Epoch 32/100
5/5 [==============================] - 0s 13ms/step - loss: 2.4900 - accuracy: 0.8161 - val_loss: 2.3656 - val_accuracy: 0.8721
Epoch 33/100
5/5 [==============================] - 0s 13ms/step - loss: 2.3021 - accuracy: 0.8325 - val_loss: 2.2055 - val_accuracy: 0.8721
Epoch 34/100
5/5 [==============================] - 0s 13ms/step - loss: 2.1474 - accuracy: 0.8292 - val_loss: 2.0534 - val_accuracy: 0.8721
Epoch 35/100
5/5 [==============================] - 0s 15ms/step - loss: 1.9990 - accuracy: 0.8522 - val_loss: 1.9111 - val_accuracy: 0.8721
Epoch 36/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8649 - accuracy: 0.8391 - val_loss: 1.7714 - val_accuracy: 0.8721
Epoch 37/100
5/5 [==============================] - 0s 13ms/step - loss: 1.7320 - accuracy: 0.8522 - val_loss: 1.6392 - val_accuracy: 0.8721
Epoch 38/100
5/5 [==============================] - 0s 12ms/step - loss: 1.5891 - accuracy: 0.8621 - val_loss: 1.5206 - val_accuracy: 0.8721
Epoch 39/100
5/5 [==============================] - 0s 13ms/step - loss: 1.4686 - accuracy: 0.8637 - val_loss: 1.4065 - val_accuracy: 0.8721
Epoch 40/100
5/5 [==============================] - 0s 13ms/step - loss: 1.3620 - accuracy: 0.8440 - val_loss: 1.2946 - val_accuracy: 0.8721
Epoch 41/100
5/5 [==============================] - 0s 13ms/step - loss: 1.2457 - accuracy: 0.8506 - val_loss: 1.1891 - val_accuracy: 0.8721
Epoch 42/100
5/5 [==============================] - 0s 11ms/step - loss: 1.1540 - accuracy: 0.8407 - val_loss: 1.0974 - val_accuracy: 0.8721
Epoch 43/100
5/5 [==============================] - 0s 13ms/step - loss: 1.0594 - accuracy: 0.8604 - val_loss: 1.0088 - val_accuracy: 0.8721
Epoch 44/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9580 - accuracy: 0.8555 - val_loss: 0.9245 - val_accuracy: 0.8721
Epoch 45/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8900 - accuracy: 0.8539 - val_loss: 0.8552 - val_accuracy: 0.8721
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8168 - accuracy: 0.8489 - val_loss: 0.7960 - val_accuracy: 0.8721
Epoch 47/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7462 - accuracy: 0.8456 - val_loss: 0.7350 - val_accuracy: 0.8721
Epoch 48/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6807 - accuracy: 0.8555 - val_loss: 0.6809 - val_accuracy: 0.8721
Epoch 49/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6392 - accuracy: 0.8621 - val_loss: 0.6312 - val_accuracy: 0.8721
Epoch 50/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5829 - accuracy: 0.8604 - val_loss: 0.5876 - val_accuracy: 0.8721
Epoch 51/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5508 - accuracy: 0.8522 - val_loss: 0.5504 - val_accuracy: 0.8721
Epoch 52/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5111 - accuracy: 0.8440 - val_loss: 0.5263 - val_accuracy: 0.8721
Epoch 53/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4975 - accuracy: 0.8539 - val_loss: 0.5123 - val_accuracy: 0.8721
Epoch 54/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4828 - accuracy: 0.8539 - val_loss: 0.4962 - val_accuracy: 0.8721
Epoch 55/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4721 - accuracy: 0.8489 - val_loss: 0.4863 - val_accuracy: 0.8721
Epoch 56/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4694 - accuracy: 0.8555 - val_loss: 0.4790 - val_accuracy: 0.8721
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4596 - accuracy: 0.8440 - val_loss: 0.4770 - val_accuracy: 0.8721
Epoch 58/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4574 - accuracy: 0.8555 - val_loss: 0.4712 - val_accuracy: 0.8721
Epoch 59/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4410 - accuracy: 0.8621 - val_loss: 0.4683 - val_accuracy: 0.8721
Epoch 60/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4474 - accuracy: 0.8489 - val_loss: 0.4671 - val_accuracy: 0.8721
Epoch 61/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4508 - accuracy: 0.8621 - val_loss: 0.4627 - val_accuracy: 0.8721
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4521 - accuracy: 0.8473 - val_loss: 0.4611 - val_accuracy: 0.8721
Epoch 63/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4451 - accuracy: 0.8342 - val_loss: 0.4566 - val_accuracy: 0.8721
Epoch 64/100
5/5 [==============================] - 0s 23ms/step - loss: 0.4386 - accuracy: 0.8637 - val_loss: 0.4549 - val_accuracy: 0.8721
Epoch 65/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4308 - accuracy: 0.8473 - val_loss: 0.4523 - val_accuracy: 0.8721
Epoch 66/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4318 - accuracy: 0.8571 - val_loss: 0.4494 - val_accuracy: 0.8721
Epoch 67/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4336 - accuracy: 0.8588 - val_loss: 0.4487 - val_accuracy: 0.8721
Epoch 68/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4375 - accuracy: 0.8473 - val_loss: 0.4448 - val_accuracy: 0.8721
Epoch 69/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4274 - accuracy: 0.8621 - val_loss: 0.4428 - val_accuracy: 0.8721
Epoch 70/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4301 - accuracy: 0.8456 - val_loss: 0.4425 - val_accuracy: 0.8721
Epoch 71/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4198 - accuracy: 0.8555 - val_loss: 0.4418 - val_accuracy: 0.8721
Epoch 72/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4333 - accuracy: 0.8571 - val_loss: 0.4422 - val_accuracy: 0.8721
Epoch 73/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4375 - accuracy: 0.8604 - val_loss: 0.4400 - val_accuracy: 0.8721
Epoch 74/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4228 - accuracy: 0.8555 - val_loss: 0.4353 - val_accuracy: 0.8721
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4268 - accuracy: 0.8456 - val_loss: 0.4340 - val_accuracy: 0.8721
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4311 - accuracy: 0.8539 - val_loss: 0.4323 - val_accuracy: 0.8721
Epoch 77/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4169 - accuracy: 0.8539 - val_loss: 0.4306 - val_accuracy: 0.8721
Epoch 78/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4273 - accuracy: 0.8571 - val_loss: 0.4350 - val_accuracy: 0.8721
Epoch 79/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4341 - accuracy: 0.8506 - val_loss: 0.4282 - val_accuracy: 0.8721
Epoch 80/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4257 - accuracy: 0.8522 - val_loss: 0.4271 - val_accuracy: 0.8721
Epoch 81/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4319 - accuracy: 0.8522 - val_loss: 0.4238 - val_accuracy: 0.8721
Epoch 82/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4259 - accuracy: 0.8440 - val_loss: 0.4231 - val_accuracy: 0.8721
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4258 - accuracy: 0.8539 - val_loss: 0.4259 - val_accuracy: 0.8721
Epoch 84/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4236 - accuracy: 0.8506 - val_loss: 0.4196 - val_accuracy: 0.8721
Epoch 85/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4213 - accuracy: 0.8571 - val_loss: 0.4186 - val_accuracy: 0.8721
Epoch 86/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4249 - accuracy: 0.8539 - val_loss: 0.4171 - val_accuracy: 0.8721
Epoch 87/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4208 - accuracy: 0.8555 - val_loss: 0.4139 - val_accuracy: 0.8721
Epoch 88/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4303 - accuracy: 0.8506 - val_loss: 0.4161 - val_accuracy: 0.8721
Epoch 89/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4274 - accuracy: 0.8604 - val_loss: 0.4157 - val_accuracy: 0.8721
Epoch 90/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4235 - accuracy: 0.8522 - val_loss: 0.4119 - val_accuracy: 0.8721
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4219 - accuracy: 0.8670 - val_loss: 0.4071 - val_accuracy: 0.8721
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4240 - accuracy: 0.8506 - val_loss: 0.4160 - val_accuracy: 0.8721
Epoch 93/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4318 - accuracy: 0.8522 - val_loss: 0.4069 - val_accuracy: 0.8721
Epoch 94/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4225 - accuracy: 0.8555 - val_loss: 0.4043 - val_accuracy: 0.8721
Epoch 95/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4232 - accuracy: 0.8473 - val_loss: 0.4013 - val_accuracy: 0.8721
Epoch 96/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4166 - accuracy: 0.8604 - val_loss: 0.3982 - val_accuracy: 0.8721
Epoch 97/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4254 - accuracy: 0.8489 - val_loss: 0.4004 - val_accuracy: 0.8721
Epoch 98/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4052 - accuracy: 0.8456 - val_loss: 0.3934 - val_accuracy: 0.8721
Epoch 99/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4205 - accuracy: 0.8522 - val_loss: 0.3957 - val_accuracy: 0.8721
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4142 - accuracy: 0.8522 - val_loss: 0.3958 - val_accuracy: 0.8721
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 2, 'hidden_units': 64, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.9995, 'rho': None, 'batch_norm': True, 'initializers': 'random_uniform'}
Batch size: 128
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
5/5 [==============================] - 1s 67ms/step - loss: 10.8236 - accuracy: 0.3230 - val_loss: 10.5551 - val_accuracy: 0.6316
Epoch 2/100
5/5 [==============================] - 0s 12ms/step - loss: 10.4367 - accuracy: 0.4098 - val_loss: 10.2063 - val_accuracy: 0.6711
Epoch 3/100
5/5 [==============================] - 0s 13ms/step - loss: 10.0528 - accuracy: 0.5016 - val_loss: 9.8624 - val_accuracy: 0.6875
Epoch 4/100
5/5 [==============================] - 0s 12ms/step - loss: 9.6942 - accuracy: 0.5820 - val_loss: 9.5260 - val_accuracy: 0.6941
Epoch 5/100
5/5 [==============================] - 0s 15ms/step - loss: 9.3447 - accuracy: 0.5984 - val_loss: 9.1912 - val_accuracy: 0.7039
Epoch 6/100
5/5 [==============================] - 0s 13ms/step - loss: 8.9880 - accuracy: 0.6410 - val_loss: 8.8616 - val_accuracy: 0.7039
Epoch 7/100
5/5 [==============================] - 0s 14ms/step - loss: 8.6482 - accuracy: 0.6918 - val_loss: 8.5375 - val_accuracy: 0.7171
Epoch 8/100
5/5 [==============================] - 0s 13ms/step - loss: 8.3333 - accuracy: 0.6639 - val_loss: 8.2190 - val_accuracy: 0.7336
Epoch 9/100
5/5 [==============================] - 0s 13ms/step - loss: 7.9998 - accuracy: 0.6984 - val_loss: 7.9058 - val_accuracy: 0.7434
Epoch 10/100
5/5 [==============================] - 0s 14ms/step - loss: 7.6934 - accuracy: 0.7148 - val_loss: 7.5971 - val_accuracy: 0.7500
Epoch 11/100
5/5 [==============================] - 0s 14ms/step - loss: 7.3725 - accuracy: 0.7311 - val_loss: 7.2936 - val_accuracy: 0.7697
Epoch 12/100
5/5 [==============================] - 0s 14ms/step - loss: 7.0998 - accuracy: 0.7197 - val_loss: 6.9958 - val_accuracy: 0.7697
Epoch 13/100
5/5 [==============================] - 0s 14ms/step - loss: 6.7846 - accuracy: 0.7426 - val_loss: 6.6992 - val_accuracy: 0.7928
Epoch 14/100
5/5 [==============================] - 0s 13ms/step - loss: 6.4921 - accuracy: 0.7459 - val_loss: 6.4110 - val_accuracy: 0.8125
Epoch 15/100
5/5 [==============================] - 0s 14ms/step - loss: 6.2188 - accuracy: 0.7197 - val_loss: 6.1291 - val_accuracy: 0.8322
Epoch 16/100
5/5 [==============================] - 0s 14ms/step - loss: 5.9432 - accuracy: 0.7557 - val_loss: 5.8508 - val_accuracy: 0.8289
Epoch 17/100
5/5 [==============================] - 0s 14ms/step - loss: 5.6779 - accuracy: 0.7557 - val_loss: 5.5792 - val_accuracy: 0.8421
Epoch 18/100
5/5 [==============================] - 0s 12ms/step - loss: 5.4035 - accuracy: 0.7689 - val_loss: 5.3125 - val_accuracy: 0.8487
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 5.1408 - accuracy: 0.7590 - val_loss: 5.0507 - val_accuracy: 0.8421
Epoch 20/100
5/5 [==============================] - 0s 14ms/step - loss: 4.8760 - accuracy: 0.7885 - val_loss: 4.7978 - val_accuracy: 0.8421
Epoch 21/100
5/5 [==============================] - 0s 13ms/step - loss: 4.6613 - accuracy: 0.7902 - val_loss: 4.5523 - val_accuracy: 0.8520
Epoch 22/100
5/5 [==============================] - 0s 13ms/step - loss: 4.4092 - accuracy: 0.8082 - val_loss: 4.3063 - val_accuracy: 0.8586
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 4.1636 - accuracy: 0.8082 - val_loss: 4.0715 - val_accuracy: 0.8618
Epoch 24/100
5/5 [==============================] - 0s 13ms/step - loss: 3.9206 - accuracy: 0.8344 - val_loss: 3.8467 - val_accuracy: 0.8618
Epoch 25/100
5/5 [==============================] - 0s 15ms/step - loss: 3.7296 - accuracy: 0.8164 - val_loss: 3.6256 - val_accuracy: 0.8618
Epoch 26/100
5/5 [==============================] - 0s 15ms/step - loss: 3.5150 - accuracy: 0.8066 - val_loss: 3.4196 - val_accuracy: 0.8618
Epoch 27/100
5/5 [==============================] - 0s 13ms/step - loss: 3.2979 - accuracy: 0.8426 - val_loss: 3.2154 - val_accuracy: 0.8618
Epoch 28/100
5/5 [==============================] - 0s 13ms/step - loss: 3.0893 - accuracy: 0.8557 - val_loss: 3.0195 - val_accuracy: 0.8618
Epoch 29/100
5/5 [==============================] - 0s 13ms/step - loss: 2.9092 - accuracy: 0.8459 - val_loss: 2.8327 - val_accuracy: 0.8618
Epoch 30/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7199 - accuracy: 0.8607 - val_loss: 2.6505 - val_accuracy: 0.8618
Epoch 31/100
5/5 [==============================] - 0s 13ms/step - loss: 2.5186 - accuracy: 0.8770 - val_loss: 2.4804 - val_accuracy: 0.8618
Epoch 32/100
5/5 [==============================] - 0s 13ms/step - loss: 2.3518 - accuracy: 0.8738 - val_loss: 2.3159 - val_accuracy: 0.8618
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 2.2085 - accuracy: 0.8820 - val_loss: 2.1596 - val_accuracy: 0.8618
Epoch 34/100
5/5 [==============================] - 0s 12ms/step - loss: 2.0509 - accuracy: 0.8525 - val_loss: 2.0117 - val_accuracy: 0.8618
Epoch 35/100
5/5 [==============================] - 0s 14ms/step - loss: 1.9015 - accuracy: 0.8836 - val_loss: 1.8692 - val_accuracy: 0.8618
Epoch 36/100
5/5 [==============================] - 0s 14ms/step - loss: 1.7428 - accuracy: 0.8836 - val_loss: 1.7395 - val_accuracy: 0.8618
Epoch 37/100
5/5 [==============================] - 0s 14ms/step - loss: 1.6181 - accuracy: 0.8770 - val_loss: 1.6135 - val_accuracy: 0.8618
Epoch 38/100
5/5 [==============================] - 0s 12ms/step - loss: 1.5149 - accuracy: 0.8639 - val_loss: 1.4966 - val_accuracy: 0.8618
Epoch 39/100
5/5 [==============================] - 0s 12ms/step - loss: 1.3785 - accuracy: 0.8754 - val_loss: 1.3831 - val_accuracy: 0.8618
Epoch 40/100
5/5 [==============================] - 0s 14ms/step - loss: 1.2888 - accuracy: 0.8705 - val_loss: 1.2828 - val_accuracy: 0.8618
Epoch 41/100
5/5 [==============================] - 0s 13ms/step - loss: 1.1578 - accuracy: 0.8885 - val_loss: 1.1880 - val_accuracy: 0.8618
Epoch 42/100
5/5 [==============================] - 0s 15ms/step - loss: 1.0717 - accuracy: 0.8607 - val_loss: 1.1035 - val_accuracy: 0.8618
Epoch 43/100
5/5 [==============================] - 0s 16ms/step - loss: 0.9895 - accuracy: 0.8820 - val_loss: 1.0251 - val_accuracy: 0.8618
Epoch 44/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8996 - accuracy: 0.8885 - val_loss: 0.9517 - val_accuracy: 0.8618
Epoch 45/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8139 - accuracy: 0.8852 - val_loss: 0.8839 - val_accuracy: 0.8618
Epoch 46/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7472 - accuracy: 0.8918 - val_loss: 0.8200 - val_accuracy: 0.8618
Epoch 47/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6897 - accuracy: 0.8836 - val_loss: 0.7670 - val_accuracy: 0.8618
Epoch 48/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6413 - accuracy: 0.8770 - val_loss: 0.7178 - val_accuracy: 0.8618
Epoch 49/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5745 - accuracy: 0.8836 - val_loss: 0.6778 - val_accuracy: 0.8618
Epoch 50/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5418 - accuracy: 0.8705 - val_loss: 0.6424 - val_accuracy: 0.8618
Epoch 51/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5085 - accuracy: 0.8836 - val_loss: 0.6134 - val_accuracy: 0.8618
Epoch 52/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4733 - accuracy: 0.8738 - val_loss: 0.5905 - val_accuracy: 0.8618
Epoch 53/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4516 - accuracy: 0.8770 - val_loss: 0.5765 - val_accuracy: 0.8618
Epoch 54/100
5/5 [==============================] - 0s 17ms/step - loss: 0.4385 - accuracy: 0.8738 - val_loss: 0.5619 - val_accuracy: 0.8618
Epoch 55/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4255 - accuracy: 0.8770 - val_loss: 0.5518 - val_accuracy: 0.8618
Epoch 56/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4180 - accuracy: 0.8820 - val_loss: 0.5450 - val_accuracy: 0.8618
Epoch 57/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4177 - accuracy: 0.8754 - val_loss: 0.5404 - val_accuracy: 0.8618
Epoch 58/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4118 - accuracy: 0.8770 - val_loss: 0.5342 - val_accuracy: 0.8618
Epoch 59/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4019 - accuracy: 0.8803 - val_loss: 0.5301 - val_accuracy: 0.8618
Epoch 60/100
5/5 [==============================] - 0s 11ms/step - loss: 0.3962 - accuracy: 0.8754 - val_loss: 0.5258 - val_accuracy: 0.8618
Epoch 61/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3937 - accuracy: 0.8820 - val_loss: 0.5250 - val_accuracy: 0.8618
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3902 - accuracy: 0.8721 - val_loss: 0.5194 - val_accuracy: 0.8618
Epoch 63/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3780 - accuracy: 0.8852 - val_loss: 0.5176 - val_accuracy: 0.8618
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3821 - accuracy: 0.8672 - val_loss: 0.5163 - val_accuracy: 0.8618
Epoch 65/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3863 - accuracy: 0.8754 - val_loss: 0.5140 - val_accuracy: 0.8618
Epoch 66/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3914 - accuracy: 0.8705 - val_loss: 0.5136 - val_accuracy: 0.8618
Epoch 67/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3854 - accuracy: 0.8705 - val_loss: 0.5148 - val_accuracy: 0.8618
Epoch 68/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3856 - accuracy: 0.8803 - val_loss: 0.5102 - val_accuracy: 0.8618
Epoch 69/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3758 - accuracy: 0.8803 - val_loss: 0.5099 - val_accuracy: 0.8618
Epoch 70/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3953 - accuracy: 0.8705 - val_loss: 0.5098 - val_accuracy: 0.8618
Epoch 71/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3958 - accuracy: 0.8705 - val_loss: 0.5105 - val_accuracy: 0.8618
Epoch 72/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3854 - accuracy: 0.8787 - val_loss: 0.5089 - val_accuracy: 0.8618
Epoch 73/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3753 - accuracy: 0.8803 - val_loss: 0.5076 - val_accuracy: 0.8618
Epoch 74/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3758 - accuracy: 0.8803 - val_loss: 0.5042 - val_accuracy: 0.8618
Epoch 75/100
5/5 [==============================] - 0s 11ms/step - loss: 0.3802 - accuracy: 0.8820 - val_loss: 0.5059 - val_accuracy: 0.8618
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3935 - accuracy: 0.8574 - val_loss: 0.5014 - val_accuracy: 0.8618
Epoch 77/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3821 - accuracy: 0.8721 - val_loss: 0.5005 - val_accuracy: 0.8618
Epoch 78/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3689 - accuracy: 0.8787 - val_loss: 0.4987 - val_accuracy: 0.8618
Epoch 79/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3755 - accuracy: 0.8656 - val_loss: 0.4974 - val_accuracy: 0.8618
Epoch 80/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3747 - accuracy: 0.8787 - val_loss: 0.4966 - val_accuracy: 0.8618
Epoch 81/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3750 - accuracy: 0.8754 - val_loss: 0.4940 - val_accuracy: 0.8618
Epoch 82/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3856 - accuracy: 0.8656 - val_loss: 0.4941 - val_accuracy: 0.8618
Epoch 83/100
5/5 [==============================] - 0s 15ms/step - loss: 0.3751 - accuracy: 0.8820 - val_loss: 0.5012 - val_accuracy: 0.8618
Epoch 84/100
5/5 [==============================] - 0s 11ms/step - loss: 0.3864 - accuracy: 0.8689 - val_loss: 0.4950 - val_accuracy: 0.8618
Epoch 85/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3829 - accuracy: 0.8787 - val_loss: 0.4885 - val_accuracy: 0.8618
Epoch 86/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3613 - accuracy: 0.8902 - val_loss: 0.4918 - val_accuracy: 0.8618
Epoch 87/100
5/5 [==============================] - 0s 9ms/step - loss: 0.3586 - accuracy: 0.8934 - val_loss: 0.4899 - val_accuracy: 0.8618
Epoch 88/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3655 - accuracy: 0.8738 - val_loss: 0.4878 - val_accuracy: 0.8618
Epoch 89/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3743 - accuracy: 0.8803 - val_loss: 0.4879 - val_accuracy: 0.8618
Epoch 90/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3646 - accuracy: 0.8836 - val_loss: 0.4855 - val_accuracy: 0.8618
Epoch 91/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3602 - accuracy: 0.8787 - val_loss: 0.4829 - val_accuracy: 0.8618
Epoch 92/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3584 - accuracy: 0.8705 - val_loss: 0.4785 - val_accuracy: 0.8618
Epoch 93/100
5/5 [==============================] - 0s 13ms/step - loss: 0.3622 - accuracy: 0.8738 - val_loss: 0.4798 - val_accuracy: 0.8618
Epoch 94/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3583 - accuracy: 0.8803 - val_loss: 0.4765 - val_accuracy: 0.8618
Epoch 95/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3613 - accuracy: 0.8820 - val_loss: 0.4774 - val_accuracy: 0.8618
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3612 - accuracy: 0.8738 - val_loss: 0.4738 - val_accuracy: 0.8618
Epoch 97/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3548 - accuracy: 0.8820 - val_loss: 0.4719 - val_accuracy: 0.8618
Epoch 98/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3590 - accuracy: 0.8705 - val_loss: 0.4699 - val_accuracy: 0.8618
Epoch 99/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3544 - accuracy: 0.8705 - val_loss: 0.4665 - val_accuracy: 0.8618
Epoch 100/100
5/5 [==============================] - 0s 12ms/step - loss: 0.3577 - accuracy: 0.8836 - val_loss: 0.4643 - val_accuracy: 0.8618
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Experiment number: 2
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.8, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 265ms/step - loss: 2.8172 - accuracy: 0.2479 - val_loss: 2.5614 - val_accuracy: 0.3541
Epoch 2/100
2/2 [==============================] - 0s 40ms/step - loss: 2.7138 - accuracy: 0.2857 - val_loss: 2.5173 - val_accuracy: 0.6623
Epoch 3/100
2/2 [==============================] - 0s 40ms/step - loss: 2.6368 - accuracy: 0.3481 - val_loss: 2.4641 - val_accuracy: 0.8197
Epoch 4/100
2/2 [==============================] - 0s 26ms/step - loss: 2.5007 - accuracy: 0.4860 - val_loss: 2.4101 - val_accuracy: 0.8492
Epoch 5/100
2/2 [==============================] - 0s 34ms/step - loss: 2.4500 - accuracy: 0.5484 - val_loss: 2.3585 - val_accuracy: 0.8393
Epoch 6/100
2/2 [==============================] - 0s 51ms/step - loss: 2.3797 - accuracy: 0.6174 - val_loss: 2.3086 - val_accuracy: 0.8525
Epoch 7/100
2/2 [==============================] - 0s 50ms/step - loss: 2.3326 - accuracy: 0.6388 - val_loss: 2.2620 - val_accuracy: 0.8590
Epoch 8/100
2/2 [==============================] - 0s 50ms/step - loss: 2.2693 - accuracy: 0.6782 - val_loss: 2.2183 - val_accuracy: 0.8328
Epoch 9/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2076 - accuracy: 0.7291 - val_loss: 2.1811 - val_accuracy: 0.8295
Epoch 10/100
2/2 [==============================] - 0s 42ms/step - loss: 2.1745 - accuracy: 0.7176 - val_loss: 2.1471 - val_accuracy: 0.8164
Epoch 11/100
2/2 [==============================] - 0s 41ms/step - loss: 2.1205 - accuracy: 0.7635 - val_loss: 2.1131 - val_accuracy: 0.8164
Epoch 12/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0792 - accuracy: 0.7767 - val_loss: 2.0805 - val_accuracy: 0.8164
Epoch 13/100
2/2 [==============================] - 0s 36ms/step - loss: 2.0312 - accuracy: 0.7898 - val_loss: 2.0489 - val_accuracy: 0.8164
Epoch 14/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9935 - accuracy: 0.8161 - val_loss: 2.0169 - val_accuracy: 0.8164
Epoch 15/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9452 - accuracy: 0.8424 - val_loss: 1.9860 - val_accuracy: 0.8164
Epoch 16/100
2/2 [==============================] - 0s 36ms/step - loss: 1.9354 - accuracy: 0.8243 - val_loss: 1.9574 - val_accuracy: 0.8164
Epoch 17/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8812 - accuracy: 0.8374 - val_loss: 1.9295 - val_accuracy: 0.8164
Epoch 18/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8425 - accuracy: 0.8407 - val_loss: 1.9021 - val_accuracy: 0.8164
Epoch 19/100
2/2 [==============================] - 0s 36ms/step - loss: 1.8224 - accuracy: 0.8522 - val_loss: 1.8756 - val_accuracy: 0.8164
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7967 - accuracy: 0.8374 - val_loss: 1.8506 - val_accuracy: 0.8164
Epoch 21/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7779 - accuracy: 0.8473 - val_loss: 1.8269 - val_accuracy: 0.8164
Epoch 22/100
2/2 [==============================] - 0s 35ms/step - loss: 1.7421 - accuracy: 0.8489 - val_loss: 1.8039 - val_accuracy: 0.8164
Epoch 23/100
2/2 [==============================] - 0s 36ms/step - loss: 1.7115 - accuracy: 0.8604 - val_loss: 1.7818 - val_accuracy: 0.8164
Epoch 24/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6707 - accuracy: 0.8571 - val_loss: 1.7607 - val_accuracy: 0.8164
Epoch 25/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6746 - accuracy: 0.8522 - val_loss: 1.7407 - val_accuracy: 0.8164
Epoch 26/100
2/2 [==============================] - 0s 34ms/step - loss: 1.6440 - accuracy: 0.8637 - val_loss: 1.7218 - val_accuracy: 0.8164
Epoch 27/100
2/2 [==============================] - 0s 30ms/step - loss: 1.6194 - accuracy: 0.8654 - val_loss: 1.7043 - val_accuracy: 0.8164
Epoch 28/100
2/2 [==============================] - 0s 50ms/step - loss: 1.6146 - accuracy: 0.8555 - val_loss: 1.6871 - val_accuracy: 0.8164
Epoch 29/100
2/2 [==============================] - 0s 27ms/step - loss: 1.5579 - accuracy: 0.8900 - val_loss: 1.6701 - val_accuracy: 0.8164
Epoch 30/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5563 - accuracy: 0.8801 - val_loss: 1.6537 - val_accuracy: 0.8164
Epoch 31/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5504 - accuracy: 0.8834 - val_loss: 1.6379 - val_accuracy: 0.8164
Epoch 32/100
2/2 [==============================] - 0s 38ms/step - loss: 1.5194 - accuracy: 0.8883 - val_loss: 1.6228 - val_accuracy: 0.8164
Epoch 33/100
2/2 [==============================] - 0s 35ms/step - loss: 1.5035 - accuracy: 0.8588 - val_loss: 1.6070 - val_accuracy: 0.8164
Epoch 34/100
2/2 [==============================] - 0s 33ms/step - loss: 1.4868 - accuracy: 0.8752 - val_loss: 1.5917 - val_accuracy: 0.8164
Epoch 35/100
2/2 [==============================] - 0s 29ms/step - loss: 1.4641 - accuracy: 0.8719 - val_loss: 1.5774 - val_accuracy: 0.8164
Epoch 36/100
2/2 [==============================] - 0s 30ms/step - loss: 1.4506 - accuracy: 0.8719 - val_loss: 1.5635 - val_accuracy: 0.8164
Epoch 37/100
2/2 [==============================] - 0s 36ms/step - loss: 1.4313 - accuracy: 0.8818 - val_loss: 1.5492 - val_accuracy: 0.8164
Epoch 38/100
2/2 [==============================] - 0s 30ms/step - loss: 1.4340 - accuracy: 0.8719 - val_loss: 1.5346 - val_accuracy: 0.8164
Epoch 39/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4161 - accuracy: 0.8719 - val_loss: 1.5196 - val_accuracy: 0.8164
Epoch 40/100
2/2 [==============================] - 0s 50ms/step - loss: 1.3814 - accuracy: 0.8834 - val_loss: 1.5050 - val_accuracy: 0.8164
Epoch 41/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3617 - accuracy: 0.8883 - val_loss: 1.4908 - val_accuracy: 0.8164
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 1.3606 - accuracy: 0.8768 - val_loss: 1.4786 - val_accuracy: 0.8164
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3394 - accuracy: 0.8883 - val_loss: 1.4670 - val_accuracy: 0.8164
Epoch 44/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3323 - accuracy: 0.8703 - val_loss: 1.4553 - val_accuracy: 0.8164
Epoch 45/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3069 - accuracy: 0.8719 - val_loss: 1.4438 - val_accuracy: 0.8164
Epoch 46/100
2/2 [==============================] - 0s 34ms/step - loss: 1.2935 - accuracy: 0.8785 - val_loss: 1.4326 - val_accuracy: 0.8164
Epoch 47/100
2/2 [==============================] - 0s 36ms/step - loss: 1.2839 - accuracy: 0.8900 - val_loss: 1.4208 - val_accuracy: 0.8164
Epoch 48/100
2/2 [==============================] - 0s 33ms/step - loss: 1.2596 - accuracy: 0.8883 - val_loss: 1.4072 - val_accuracy: 0.8164
Epoch 49/100
2/2 [==============================] - 0s 45ms/step - loss: 1.2516 - accuracy: 0.8900 - val_loss: 1.3921 - val_accuracy: 0.8164
Epoch 50/100
2/2 [==============================] - 0s 48ms/step - loss: 1.2443 - accuracy: 0.8916 - val_loss: 1.3783 - val_accuracy: 0.8164
Epoch 51/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2221 - accuracy: 0.8834 - val_loss: 1.3660 - val_accuracy: 0.8164
Epoch 52/100
2/2 [==============================] - 0s 50ms/step - loss: 1.2120 - accuracy: 0.8768 - val_loss: 1.3542 - val_accuracy: 0.8164
Epoch 53/100
2/2 [==============================] - 0s 54ms/step - loss: 1.1946 - accuracy: 0.8900 - val_loss: 1.3424 - val_accuracy: 0.8164
Epoch 54/100
2/2 [==============================] - 0s 78ms/step - loss: 1.1736 - accuracy: 0.8949 - val_loss: 1.3299 - val_accuracy: 0.8164
Epoch 55/100
2/2 [==============================] - 0s 45ms/step - loss: 1.1688 - accuracy: 0.8785 - val_loss: 1.3179 - val_accuracy: 0.8164
Epoch 56/100
2/2 [==============================] - 0s 51ms/step - loss: 1.1680 - accuracy: 0.8949 - val_loss: 1.3075 - val_accuracy: 0.8164
Epoch 57/100
2/2 [==============================] - 0s 55ms/step - loss: 1.1418 - accuracy: 0.8801 - val_loss: 1.2989 - val_accuracy: 0.8164
Epoch 58/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1309 - accuracy: 0.8916 - val_loss: 1.2900 - val_accuracy: 0.8164
Epoch 59/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1083 - accuracy: 0.9048 - val_loss: 1.2803 - val_accuracy: 0.8164
Epoch 60/100
2/2 [==============================] - 0s 52ms/step - loss: 1.1162 - accuracy: 0.8752 - val_loss: 1.2705 - val_accuracy: 0.8164
Epoch 61/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0910 - accuracy: 0.8949 - val_loss: 1.2612 - val_accuracy: 0.8164
Epoch 62/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0867 - accuracy: 0.8883 - val_loss: 1.2509 - val_accuracy: 0.8164
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 1.0641 - accuracy: 0.8883 - val_loss: 1.2405 - val_accuracy: 0.8164
Epoch 64/100
2/2 [==============================] - 0s 32ms/step - loss: 1.0518 - accuracy: 0.8834 - val_loss: 1.2306 - val_accuracy: 0.8164
Epoch 65/100
2/2 [==============================] - 0s 36ms/step - loss: 1.0356 - accuracy: 0.8966 - val_loss: 1.2193 - val_accuracy: 0.8164
Epoch 66/100
2/2 [==============================] - 0s 48ms/step - loss: 1.0381 - accuracy: 0.8933 - val_loss: 1.2079 - val_accuracy: 0.8164
Epoch 67/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0177 - accuracy: 0.8867 - val_loss: 1.1983 - val_accuracy: 0.8164
Epoch 68/100
2/2 [==============================] - 0s 37ms/step - loss: 1.0119 - accuracy: 0.8867 - val_loss: 1.1909 - val_accuracy: 0.8164
Epoch 69/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9840 - accuracy: 0.8966 - val_loss: 1.1836 - val_accuracy: 0.8164
Epoch 70/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9960 - accuracy: 0.8867 - val_loss: 1.1746 - val_accuracy: 0.8164
Epoch 71/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9839 - accuracy: 0.8966 - val_loss: 1.1640 - val_accuracy: 0.8164
Epoch 72/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9757 - accuracy: 0.8900 - val_loss: 1.1518 - val_accuracy: 0.8164
Epoch 73/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9561 - accuracy: 0.8998 - val_loss: 1.1400 - val_accuracy: 0.8164
Epoch 74/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9494 - accuracy: 0.8883 - val_loss: 1.1318 - val_accuracy: 0.8164
Epoch 75/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9511 - accuracy: 0.8768 - val_loss: 1.1256 - val_accuracy: 0.8164
Epoch 76/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9201 - accuracy: 0.8933 - val_loss: 1.1199 - val_accuracy: 0.8164
Epoch 77/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9167 - accuracy: 0.8883 - val_loss: 1.1131 - val_accuracy: 0.8164
Epoch 78/100
2/2 [==============================] - 0s 31ms/step - loss: 0.9142 - accuracy: 0.8834 - val_loss: 1.1031 - val_accuracy: 0.8164
Epoch 79/100
2/2 [==============================] - 0s 34ms/step - loss: 0.9040 - accuracy: 0.8966 - val_loss: 1.0915 - val_accuracy: 0.8164
Epoch 80/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8861 - accuracy: 0.8933 - val_loss: 1.0799 - val_accuracy: 0.8164
Epoch 81/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8835 - accuracy: 0.8966 - val_loss: 1.0702 - val_accuracy: 0.8164
Epoch 82/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8617 - accuracy: 0.8982 - val_loss: 1.0644 - val_accuracy: 0.8164
Epoch 83/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8487 - accuracy: 0.8966 - val_loss: 1.0602 - val_accuracy: 0.8164
Epoch 84/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8465 - accuracy: 0.8916 - val_loss: 1.0549 - val_accuracy: 0.8164
Epoch 85/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8510 - accuracy: 0.8916 - val_loss: 1.0470 - val_accuracy: 0.8164
Epoch 86/100
2/2 [==============================] - 0s 35ms/step - loss: 0.8329 - accuracy: 0.8834 - val_loss: 1.0371 - val_accuracy: 0.8164
Epoch 87/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8198 - accuracy: 0.8900 - val_loss: 1.0262 - val_accuracy: 0.8164
Epoch 88/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8075 - accuracy: 0.8916 - val_loss: 1.0187 - val_accuracy: 0.8164
Epoch 89/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8100 - accuracy: 0.8867 - val_loss: 1.0145 - val_accuracy: 0.8164
Epoch 90/100
2/2 [==============================] - 0s 40ms/step - loss: 0.7863 - accuracy: 0.8949 - val_loss: 1.0083 - val_accuracy: 0.8164
Epoch 91/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7669 - accuracy: 0.9080 - val_loss: 0.9994 - val_accuracy: 0.8164
Epoch 92/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7799 - accuracy: 0.8916 - val_loss: 0.9902 - val_accuracy: 0.8164
Epoch 93/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7687 - accuracy: 0.8933 - val_loss: 0.9818 - val_accuracy: 0.8164
Epoch 94/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7665 - accuracy: 0.8916 - val_loss: 0.9742 - val_accuracy: 0.8164
Epoch 95/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7415 - accuracy: 0.8916 - val_loss: 0.9653 - val_accuracy: 0.8164
Epoch 96/100
2/2 [==============================] - 0s 46ms/step - loss: 0.7349 - accuracy: 0.9048 - val_loss: 0.9572 - val_accuracy: 0.8164
Epoch 97/100
2/2 [==============================] - 0s 45ms/step - loss: 0.7291 - accuracy: 0.8867 - val_loss: 0.9511 - val_accuracy: 0.8164
Epoch 98/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7310 - accuracy: 0.8851 - val_loss: 0.9451 - val_accuracy: 0.8164
Epoch 99/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7138 - accuracy: 0.8883 - val_loss: 0.9390 - val_accuracy: 0.8164
Epoch 100/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7089 - accuracy: 0.8998 - val_loss: 0.9333 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.8, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 262ms/step - loss: 2.6556 - accuracy: 0.3612 - val_loss: 2.4518 - val_accuracy: 0.7246
Epoch 2/100
2/2 [==============================] - 0s 56ms/step - loss: 2.5973 - accuracy: 0.4039 - val_loss: 2.4235 - val_accuracy: 0.8033
Epoch 3/100
2/2 [==============================] - 0s 51ms/step - loss: 2.5115 - accuracy: 0.4663 - val_loss: 2.3850 - val_accuracy: 0.8525
Epoch 4/100
2/2 [==============================] - 0s 51ms/step - loss: 2.4331 - accuracy: 0.5501 - val_loss: 2.3407 - val_accuracy: 0.8623
Epoch 5/100
2/2 [==============================] - 0s 48ms/step - loss: 2.3782 - accuracy: 0.6108 - val_loss: 2.2919 - val_accuracy: 0.8689
Epoch 6/100
2/2 [==============================] - 0s 58ms/step - loss: 2.3235 - accuracy: 0.6453 - val_loss: 2.2415 - val_accuracy: 0.8852
Epoch 7/100
2/2 [==============================] - 0s 46ms/step - loss: 2.2756 - accuracy: 0.6864 - val_loss: 2.1922 - val_accuracy: 0.8918
Epoch 8/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2274 - accuracy: 0.6995 - val_loss: 2.1454 - val_accuracy: 0.9016
Epoch 9/100
2/2 [==============================] - 0s 44ms/step - loss: 2.1446 - accuracy: 0.7340 - val_loss: 2.1004 - val_accuracy: 0.8754
Epoch 10/100
2/2 [==============================] - 0s 45ms/step - loss: 2.1111 - accuracy: 0.7406 - val_loss: 2.0583 - val_accuracy: 0.8754
Epoch 11/100
2/2 [==============================] - 0s 43ms/step - loss: 2.0470 - accuracy: 0.7767 - val_loss: 2.0185 - val_accuracy: 0.8754
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0217 - accuracy: 0.7882 - val_loss: 1.9830 - val_accuracy: 0.8754
Epoch 13/100
2/2 [==============================] - 0s 45ms/step - loss: 1.9936 - accuracy: 0.8062 - val_loss: 1.9495 - val_accuracy: 0.8754
Epoch 14/100
2/2 [==============================] - 0s 45ms/step - loss: 1.9464 - accuracy: 0.8046 - val_loss: 1.9177 - val_accuracy: 0.8721
Epoch 15/100
2/2 [==============================] - 0s 42ms/step - loss: 1.9180 - accuracy: 0.8128 - val_loss: 1.8874 - val_accuracy: 0.8721
Epoch 16/100
2/2 [==============================] - 0s 45ms/step - loss: 1.8807 - accuracy: 0.8276 - val_loss: 1.8579 - val_accuracy: 0.8721
Epoch 17/100
2/2 [==============================] - 0s 43ms/step - loss: 1.8615 - accuracy: 0.8259 - val_loss: 1.8284 - val_accuracy: 0.8721
Epoch 18/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8265 - accuracy: 0.8194 - val_loss: 1.7991 - val_accuracy: 0.8721
Epoch 19/100
2/2 [==============================] - 0s 46ms/step - loss: 1.8161 - accuracy: 0.8210 - val_loss: 1.7708 - val_accuracy: 0.8721
Epoch 20/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7845 - accuracy: 0.8342 - val_loss: 1.7445 - val_accuracy: 0.8721
Epoch 21/100
2/2 [==============================] - 0s 38ms/step - loss: 1.7518 - accuracy: 0.8292 - val_loss: 1.7198 - val_accuracy: 0.8721
Epoch 22/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7409 - accuracy: 0.8292 - val_loss: 1.6965 - val_accuracy: 0.8721
Epoch 23/100
2/2 [==============================] - 0s 42ms/step - loss: 1.7132 - accuracy: 0.8342 - val_loss: 1.6748 - val_accuracy: 0.8721
Epoch 24/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6647 - accuracy: 0.8456 - val_loss: 1.6538 - val_accuracy: 0.8721
Epoch 25/100
2/2 [==============================] - 0s 43ms/step - loss: 1.6497 - accuracy: 0.8292 - val_loss: 1.6334 - val_accuracy: 0.8721
Epoch 26/100
2/2 [==============================] - 0s 45ms/step - loss: 1.6209 - accuracy: 0.8637 - val_loss: 1.6129 - val_accuracy: 0.8721
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 1.6200 - accuracy: 0.8407 - val_loss: 1.5923 - val_accuracy: 0.8721
Epoch 28/100
2/2 [==============================] - 0s 47ms/step - loss: 1.6126 - accuracy: 0.8309 - val_loss: 1.5734 - val_accuracy: 0.8721
Epoch 29/100
2/2 [==============================] - 0s 41ms/step - loss: 1.5614 - accuracy: 0.8604 - val_loss: 1.5556 - val_accuracy: 0.8721
Epoch 30/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5483 - accuracy: 0.8571 - val_loss: 1.5378 - val_accuracy: 0.8721
Epoch 31/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5249 - accuracy: 0.8555 - val_loss: 1.5206 - val_accuracy: 0.8721
Epoch 32/100
2/2 [==============================] - 0s 43ms/step - loss: 1.5087 - accuracy: 0.8555 - val_loss: 1.5037 - val_accuracy: 0.8721
Epoch 33/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4986 - accuracy: 0.8522 - val_loss: 1.4881 - val_accuracy: 0.8721
Epoch 34/100
2/2 [==============================] - 0s 42ms/step - loss: 1.4722 - accuracy: 0.8588 - val_loss: 1.4735 - val_accuracy: 0.8721
Epoch 35/100
2/2 [==============================] - 0s 44ms/step - loss: 1.4628 - accuracy: 0.8555 - val_loss: 1.4584 - val_accuracy: 0.8721
Epoch 36/100
2/2 [==============================] - 0s 50ms/step - loss: 1.4470 - accuracy: 0.8555 - val_loss: 1.4421 - val_accuracy: 0.8721
Epoch 37/100
2/2 [==============================] - 0s 45ms/step - loss: 1.4340 - accuracy: 0.8621 - val_loss: 1.4269 - val_accuracy: 0.8721
Epoch 38/100
2/2 [==============================] - 0s 43ms/step - loss: 1.4208 - accuracy: 0.8588 - val_loss: 1.4119 - val_accuracy: 0.8721
Epoch 39/100
2/2 [==============================] - 0s 41ms/step - loss: 1.3982 - accuracy: 0.8555 - val_loss: 1.3963 - val_accuracy: 0.8721
Epoch 40/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3843 - accuracy: 0.8670 - val_loss: 1.3816 - val_accuracy: 0.8721
Epoch 41/100
2/2 [==============================] - 0s 44ms/step - loss: 1.3581 - accuracy: 0.8621 - val_loss: 1.3671 - val_accuracy: 0.8721
Epoch 42/100
2/2 [==============================] - 0s 51ms/step - loss: 1.3422 - accuracy: 0.8703 - val_loss: 1.3528 - val_accuracy: 0.8721
Epoch 43/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3376 - accuracy: 0.8719 - val_loss: 1.3379 - val_accuracy: 0.8721
Epoch 44/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3192 - accuracy: 0.8604 - val_loss: 1.3222 - val_accuracy: 0.8721
Epoch 45/100
2/2 [==============================] - 0s 46ms/step - loss: 1.3011 - accuracy: 0.8768 - val_loss: 1.3074 - val_accuracy: 0.8721
Epoch 46/100
2/2 [==============================] - 0s 53ms/step - loss: 1.2815 - accuracy: 0.8604 - val_loss: 1.2939 - val_accuracy: 0.8721
Epoch 47/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2707 - accuracy: 0.8637 - val_loss: 1.2808 - val_accuracy: 0.8721
Epoch 48/100
2/2 [==============================] - 0s 35ms/step - loss: 1.2619 - accuracy: 0.8686 - val_loss: 1.2686 - val_accuracy: 0.8721
Epoch 49/100
2/2 [==============================] - 0s 31ms/step - loss: 1.2459 - accuracy: 0.8670 - val_loss: 1.2566 - val_accuracy: 0.8721
Epoch 50/100
2/2 [==============================] - 0s 50ms/step - loss: 1.2230 - accuracy: 0.8719 - val_loss: 1.2452 - val_accuracy: 0.8721
Epoch 51/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2222 - accuracy: 0.8719 - val_loss: 1.2344 - val_accuracy: 0.8721
Epoch 52/100
2/2 [==============================] - 0s 54ms/step - loss: 1.2053 - accuracy: 0.8670 - val_loss: 1.2225 - val_accuracy: 0.8721
Epoch 53/100
2/2 [==============================] - 0s 36ms/step - loss: 1.1779 - accuracy: 0.8768 - val_loss: 1.2101 - val_accuracy: 0.8721
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 1.1944 - accuracy: 0.8588 - val_loss: 1.1989 - val_accuracy: 0.8721
Epoch 55/100
2/2 [==============================] - 0s 41ms/step - loss: 1.1634 - accuracy: 0.8539 - val_loss: 1.1883 - val_accuracy: 0.8721
Epoch 56/100
2/2 [==============================] - 0s 39ms/step - loss: 1.1553 - accuracy: 0.8703 - val_loss: 1.1767 - val_accuracy: 0.8721
Epoch 57/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1370 - accuracy: 0.8654 - val_loss: 1.1640 - val_accuracy: 0.8721
Epoch 58/100
2/2 [==============================] - 0s 32ms/step - loss: 1.1424 - accuracy: 0.8604 - val_loss: 1.1514 - val_accuracy: 0.8721
Epoch 59/100
2/2 [==============================] - 0s 40ms/step - loss: 1.1292 - accuracy: 0.8506 - val_loss: 1.1398 - val_accuracy: 0.8721
Epoch 60/100
2/2 [==============================] - 0s 34ms/step - loss: 1.1155 - accuracy: 0.8506 - val_loss: 1.1294 - val_accuracy: 0.8721
Epoch 61/100
2/2 [==============================] - 0s 49ms/step - loss: 1.0959 - accuracy: 0.8719 - val_loss: 1.1192 - val_accuracy: 0.8721
Epoch 62/100
2/2 [==============================] - 0s 43ms/step - loss: 1.0743 - accuracy: 0.8785 - val_loss: 1.1089 - val_accuracy: 0.8721
Epoch 63/100
2/2 [==============================] - 0s 51ms/step - loss: 1.0574 - accuracy: 0.8818 - val_loss: 1.0985 - val_accuracy: 0.8721
Epoch 64/100
2/2 [==============================] - 0s 48ms/step - loss: 1.0600 - accuracy: 0.8703 - val_loss: 1.0884 - val_accuracy: 0.8721
Epoch 65/100
2/2 [==============================] - 0s 51ms/step - loss: 1.0507 - accuracy: 0.8801 - val_loss: 1.0779 - val_accuracy: 0.8721
Epoch 66/100
2/2 [==============================] - 0s 34ms/step - loss: 1.0282 - accuracy: 0.8736 - val_loss: 1.0670 - val_accuracy: 0.8721
Epoch 67/100
2/2 [==============================] - 0s 38ms/step - loss: 1.0249 - accuracy: 0.8654 - val_loss: 1.0573 - val_accuracy: 0.8721
Epoch 68/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0196 - accuracy: 0.8621 - val_loss: 1.0480 - val_accuracy: 0.8721
Epoch 69/100
2/2 [==============================] - 0s 30ms/step - loss: 1.0014 - accuracy: 0.8588 - val_loss: 1.0377 - val_accuracy: 0.8721
Epoch 70/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9982 - accuracy: 0.8670 - val_loss: 1.0277 - val_accuracy: 0.8721
Epoch 71/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9847 - accuracy: 0.8818 - val_loss: 1.0182 - val_accuracy: 0.8721
Epoch 72/100
2/2 [==============================] - 0s 43ms/step - loss: 0.9681 - accuracy: 0.8768 - val_loss: 1.0088 - val_accuracy: 0.8721
Epoch 73/100
2/2 [==============================] - 0s 41ms/step - loss: 0.9467 - accuracy: 0.8752 - val_loss: 0.9989 - val_accuracy: 0.8721
Epoch 74/100
2/2 [==============================] - 0s 65ms/step - loss: 0.9341 - accuracy: 0.8686 - val_loss: 0.9888 - val_accuracy: 0.8721
Epoch 75/100
2/2 [==============================] - 0s 50ms/step - loss: 0.9378 - accuracy: 0.8686 - val_loss: 0.9781 - val_accuracy: 0.8721
Epoch 76/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9388 - accuracy: 0.8686 - val_loss: 0.9690 - val_accuracy: 0.8721
Epoch 77/100
2/2 [==============================] - 0s 51ms/step - loss: 0.9119 - accuracy: 0.8801 - val_loss: 0.9607 - val_accuracy: 0.8721
Epoch 78/100
2/2 [==============================] - 0s 51ms/step - loss: 0.9060 - accuracy: 0.8703 - val_loss: 0.9535 - val_accuracy: 0.8721
Epoch 79/100
2/2 [==============================] - 0s 39ms/step - loss: 0.9117 - accuracy: 0.8736 - val_loss: 0.9463 - val_accuracy: 0.8721
Epoch 80/100
2/2 [==============================] - 0s 40ms/step - loss: 0.8850 - accuracy: 0.8752 - val_loss: 0.9375 - val_accuracy: 0.8721
Epoch 81/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8973 - accuracy: 0.8686 - val_loss: 0.9277 - val_accuracy: 0.8721
Epoch 82/100
2/2 [==============================] - 0s 38ms/step - loss: 0.8761 - accuracy: 0.8654 - val_loss: 0.9176 - val_accuracy: 0.8721
Epoch 83/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8662 - accuracy: 0.8768 - val_loss: 0.9087 - val_accuracy: 0.8721
Epoch 84/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8581 - accuracy: 0.8670 - val_loss: 0.9012 - val_accuracy: 0.8721
Epoch 85/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8455 - accuracy: 0.8637 - val_loss: 0.8929 - val_accuracy: 0.8721
Epoch 86/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8424 - accuracy: 0.8654 - val_loss: 0.8843 - val_accuracy: 0.8721
Epoch 87/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8242 - accuracy: 0.8785 - val_loss: 0.8769 - val_accuracy: 0.8721
Epoch 88/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8257 - accuracy: 0.8604 - val_loss: 0.8689 - val_accuracy: 0.8721
Epoch 89/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8157 - accuracy: 0.8703 - val_loss: 0.8599 - val_accuracy: 0.8721
Epoch 90/100
2/2 [==============================] - 0s 32ms/step - loss: 0.7848 - accuracy: 0.8966 - val_loss: 0.8510 - val_accuracy: 0.8721
Epoch 91/100
2/2 [==============================] - 0s 29ms/step - loss: 0.7861 - accuracy: 0.8834 - val_loss: 0.8432 - val_accuracy: 0.8721
Epoch 92/100
2/2 [==============================] - 0s 39ms/step - loss: 0.8017 - accuracy: 0.8670 - val_loss: 0.8355 - val_accuracy: 0.8721
Epoch 93/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7955 - accuracy: 0.8637 - val_loss: 0.8277 - val_accuracy: 0.8721
Epoch 94/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7649 - accuracy: 0.8785 - val_loss: 0.8200 - val_accuracy: 0.8721
Epoch 95/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7506 - accuracy: 0.8736 - val_loss: 0.8123 - val_accuracy: 0.8721
Epoch 96/100
2/2 [==============================] - 0s 53ms/step - loss: 0.7343 - accuracy: 0.8834 - val_loss: 0.8041 - val_accuracy: 0.8721
Epoch 97/100
2/2 [==============================] - 0s 42ms/step - loss: 0.7485 - accuracy: 0.8818 - val_loss: 0.7964 - val_accuracy: 0.8721
Epoch 98/100
2/2 [==============================] - 0s 39ms/step - loss: 0.7291 - accuracy: 0.8801 - val_loss: 0.7907 - val_accuracy: 0.8721
Epoch 99/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7181 - accuracy: 0.8801 - val_loss: 0.7842 - val_accuracy: 0.8721
Epoch 100/100
2/2 [==============================] - 0s 43ms/step - loss: 0.7067 - accuracy: 0.8768 - val_loss: 0.7763 - val_accuracy: 0.8721
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 128, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.001, 'dropout_rate': 0.4, 'momentum': 0.8, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 253ms/step - loss: 2.7792 - accuracy: 0.2508 - val_loss: 2.5746 - val_accuracy: 0.5888
Epoch 2/100
2/2 [==============================] - 0s 30ms/step - loss: 2.7049 - accuracy: 0.3098 - val_loss: 2.5441 - val_accuracy: 0.6941
Epoch 3/100
2/2 [==============================] - 0s 35ms/step - loss: 2.5954 - accuracy: 0.4279 - val_loss: 2.5029 - val_accuracy: 0.7303
Epoch 4/100
2/2 [==============================] - 0s 39ms/step - loss: 2.4840 - accuracy: 0.5689 - val_loss: 2.4604 - val_accuracy: 0.7434
Epoch 5/100
2/2 [==============================] - 0s 31ms/step - loss: 2.3948 - accuracy: 0.6213 - val_loss: 2.4179 - val_accuracy: 0.7500
Epoch 6/100
2/2 [==============================] - 0s 30ms/step - loss: 2.3195 - accuracy: 0.6770 - val_loss: 2.3728 - val_accuracy: 0.7599
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 2.2908 - accuracy: 0.7246 - val_loss: 2.3269 - val_accuracy: 0.7566
Epoch 8/100
2/2 [==============================] - 0s 33ms/step - loss: 2.2305 - accuracy: 0.7115 - val_loss: 2.2822 - val_accuracy: 0.7664
Epoch 9/100
2/2 [==============================] - 0s 42ms/step - loss: 2.1849 - accuracy: 0.7508 - val_loss: 2.2378 - val_accuracy: 0.7895
Epoch 10/100
2/2 [==============================] - 0s 46ms/step - loss: 2.1229 - accuracy: 0.7836 - val_loss: 2.1941 - val_accuracy: 0.8125
Epoch 11/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1109 - accuracy: 0.7770 - val_loss: 2.1498 - val_accuracy: 0.8224
Epoch 12/100
2/2 [==============================] - 0s 49ms/step - loss: 2.0584 - accuracy: 0.7967 - val_loss: 2.1086 - val_accuracy: 0.8322
Epoch 13/100
2/2 [==============================] - 0s 48ms/step - loss: 2.0291 - accuracy: 0.7984 - val_loss: 2.0704 - val_accuracy: 0.8454
Epoch 14/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0055 - accuracy: 0.7836 - val_loss: 2.0343 - val_accuracy: 0.8520
Epoch 15/100
2/2 [==============================] - 0s 51ms/step - loss: 1.9741 - accuracy: 0.8131 - val_loss: 2.0023 - val_accuracy: 0.8553
Epoch 16/100
2/2 [==============================] - 0s 51ms/step - loss: 1.9137 - accuracy: 0.8377 - val_loss: 1.9734 - val_accuracy: 0.8553
Epoch 17/100
2/2 [==============================] - 0s 40ms/step - loss: 1.8921 - accuracy: 0.8344 - val_loss: 1.9449 - val_accuracy: 0.8553
Epoch 18/100
2/2 [==============================] - 0s 50ms/step - loss: 1.8473 - accuracy: 0.8508 - val_loss: 1.9155 - val_accuracy: 0.8520
Epoch 19/100
2/2 [==============================] - 0s 49ms/step - loss: 1.8259 - accuracy: 0.8475 - val_loss: 1.8862 - val_accuracy: 0.8520
Epoch 20/100
2/2 [==============================] - 0s 38ms/step - loss: 1.8049 - accuracy: 0.8377 - val_loss: 1.8577 - val_accuracy: 0.8520
Epoch 21/100
2/2 [==============================] - 0s 87ms/step - loss: 1.7712 - accuracy: 0.8525 - val_loss: 1.8303 - val_accuracy: 0.8553
Epoch 22/100
2/2 [==============================] - 0s 44ms/step - loss: 1.7527 - accuracy: 0.8574 - val_loss: 1.8046 - val_accuracy: 0.8553
Epoch 23/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7209 - accuracy: 0.8656 - val_loss: 1.7809 - val_accuracy: 0.8553
Epoch 24/100
2/2 [==============================] - 0s 39ms/step - loss: 1.7021 - accuracy: 0.8590 - val_loss: 1.7584 - val_accuracy: 0.8651
Epoch 25/100
2/2 [==============================] - 0s 38ms/step - loss: 1.6672 - accuracy: 0.8557 - val_loss: 1.7372 - val_accuracy: 0.8618
Epoch 26/100
2/2 [==============================] - 0s 37ms/step - loss: 1.6593 - accuracy: 0.8721 - val_loss: 1.7171 - val_accuracy: 0.8618
Epoch 27/100
2/2 [==============================] - 0s 35ms/step - loss: 1.6173 - accuracy: 0.8787 - val_loss: 1.6977 - val_accuracy: 0.8618
Epoch 28/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6213 - accuracy: 0.8639 - val_loss: 1.6781 - val_accuracy: 0.8618
Epoch 29/100
2/2 [==============================] - 0s 34ms/step - loss: 1.5881 - accuracy: 0.8770 - val_loss: 1.6584 - val_accuracy: 0.8618
Epoch 30/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5601 - accuracy: 0.8869 - val_loss: 1.6385 - val_accuracy: 0.8618
Epoch 31/100
2/2 [==============================] - 0s 42ms/step - loss: 1.5522 - accuracy: 0.8705 - val_loss: 1.6189 - val_accuracy: 0.8618
Epoch 32/100
2/2 [==============================] - 0s 45ms/step - loss: 1.5358 - accuracy: 0.8705 - val_loss: 1.5996 - val_accuracy: 0.8618
Epoch 33/100
2/2 [==============================] - 0s 48ms/step - loss: 1.5080 - accuracy: 0.8787 - val_loss: 1.5814 - val_accuracy: 0.8618
Epoch 34/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4900 - accuracy: 0.8754 - val_loss: 1.5638 - val_accuracy: 0.8618
Epoch 35/100
2/2 [==============================] - 0s 32ms/step - loss: 1.4745 - accuracy: 0.8852 - val_loss: 1.5465 - val_accuracy: 0.8618
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 1.4611 - accuracy: 0.8918 - val_loss: 1.5300 - val_accuracy: 0.8618
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 1.4437 - accuracy: 0.8820 - val_loss: 1.5141 - val_accuracy: 0.8618
Epoch 38/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4130 - accuracy: 0.8918 - val_loss: 1.4987 - val_accuracy: 0.8618
Epoch 39/100
2/2 [==============================] - 0s 35ms/step - loss: 1.4068 - accuracy: 0.8770 - val_loss: 1.4835 - val_accuracy: 0.8618
Epoch 40/100
2/2 [==============================] - 0s 38ms/step - loss: 1.3988 - accuracy: 0.8738 - val_loss: 1.4686 - val_accuracy: 0.8618
Epoch 41/100
2/2 [==============================] - 0s 37ms/step - loss: 1.3832 - accuracy: 0.8754 - val_loss: 1.4539 - val_accuracy: 0.8618
Epoch 42/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3586 - accuracy: 0.8820 - val_loss: 1.4396 - val_accuracy: 0.8618
Epoch 43/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3534 - accuracy: 0.8787 - val_loss: 1.4257 - val_accuracy: 0.8618
Epoch 44/100
2/2 [==============================] - 0s 33ms/step - loss: 1.3197 - accuracy: 0.8885 - val_loss: 1.4120 - val_accuracy: 0.8618
Epoch 45/100
2/2 [==============================] - 0s 34ms/step - loss: 1.3152 - accuracy: 0.8754 - val_loss: 1.3986 - val_accuracy: 0.8618
Epoch 46/100
2/2 [==============================] - 0s 32ms/step - loss: 1.3145 - accuracy: 0.8869 - val_loss: 1.3852 - val_accuracy: 0.8618
Epoch 47/100
2/2 [==============================] - 0s 41ms/step - loss: 1.2914 - accuracy: 0.8820 - val_loss: 1.3718 - val_accuracy: 0.8618
Epoch 48/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2766 - accuracy: 0.8820 - val_loss: 1.3582 - val_accuracy: 0.8618
Epoch 49/100
2/2 [==============================] - 0s 40ms/step - loss: 1.2724 - accuracy: 0.8721 - val_loss: 1.3448 - val_accuracy: 0.8618
Epoch 50/100
2/2 [==============================] - 0s 32ms/step - loss: 1.2465 - accuracy: 0.8852 - val_loss: 1.3318 - val_accuracy: 0.8618
Epoch 51/100
2/2 [==============================] - 0s 46ms/step - loss: 1.2416 - accuracy: 0.8770 - val_loss: 1.3193 - val_accuracy: 0.8618
Epoch 52/100
2/2 [==============================] - 0s 42ms/step - loss: 1.2268 - accuracy: 0.8885 - val_loss: 1.3073 - val_accuracy: 0.8618
Epoch 53/100
2/2 [==============================] - 0s 44ms/step - loss: 1.1954 - accuracy: 0.8951 - val_loss: 1.2957 - val_accuracy: 0.8618
Epoch 54/100
2/2 [==============================] - 0s 47ms/step - loss: 1.1806 - accuracy: 0.8902 - val_loss: 1.2843 - val_accuracy: 0.8618
Epoch 55/100
2/2 [==============================] - 0s 49ms/step - loss: 1.1719 - accuracy: 0.8918 - val_loss: 1.2728 - val_accuracy: 0.8618
Epoch 56/100
2/2 [==============================] - 0s 34ms/step - loss: 1.1596 - accuracy: 0.8918 - val_loss: 1.2608 - val_accuracy: 0.8618
Epoch 57/100
2/2 [==============================] - 0s 43ms/step - loss: 1.1308 - accuracy: 0.8967 - val_loss: 1.2486 - val_accuracy: 0.8618
Epoch 58/100
2/2 [==============================] - 0s 52ms/step - loss: 1.1499 - accuracy: 0.8836 - val_loss: 1.2367 - val_accuracy: 0.8618
Epoch 59/100
2/2 [==============================] - 0s 55ms/step - loss: 1.1515 - accuracy: 0.8656 - val_loss: 1.2248 - val_accuracy: 0.8618
Epoch 60/100
2/2 [==============================] - 0s 48ms/step - loss: 1.0969 - accuracy: 0.9098 - val_loss: 1.2130 - val_accuracy: 0.8618
Epoch 61/100
2/2 [==============================] - 0s 53ms/step - loss: 1.0927 - accuracy: 0.8902 - val_loss: 1.2019 - val_accuracy: 0.8618
Epoch 62/100
2/2 [==============================] - 0s 48ms/step - loss: 1.0847 - accuracy: 0.8951 - val_loss: 1.1904 - val_accuracy: 0.8618
Epoch 63/100
2/2 [==============================] - 0s 50ms/step - loss: 1.0766 - accuracy: 0.8836 - val_loss: 1.1794 - val_accuracy: 0.8618
Epoch 64/100
2/2 [==============================] - 0s 44ms/step - loss: 1.0691 - accuracy: 0.8902 - val_loss: 1.1687 - val_accuracy: 0.8618
Epoch 65/100
2/2 [==============================] - 0s 42ms/step - loss: 1.0470 - accuracy: 0.8918 - val_loss: 1.1587 - val_accuracy: 0.8618
Epoch 66/100
2/2 [==============================] - 0s 51ms/step - loss: 1.0530 - accuracy: 0.8869 - val_loss: 1.1501 - val_accuracy: 0.8618
Epoch 67/100
2/2 [==============================] - 0s 45ms/step - loss: 1.0538 - accuracy: 0.8738 - val_loss: 1.1410 - val_accuracy: 0.8618
Epoch 68/100
2/2 [==============================] - 0s 54ms/step - loss: 1.0147 - accuracy: 0.9049 - val_loss: 1.1305 - val_accuracy: 0.8618
Epoch 69/100
2/2 [==============================] - 0s 44ms/step - loss: 1.0154 - accuracy: 0.8984 - val_loss: 1.1195 - val_accuracy: 0.8618
Epoch 70/100
2/2 [==============================] - 0s 47ms/step - loss: 1.0059 - accuracy: 0.8934 - val_loss: 1.1085 - val_accuracy: 0.8618
Epoch 71/100
2/2 [==============================] - 0s 49ms/step - loss: 0.9701 - accuracy: 0.8951 - val_loss: 1.0976 - val_accuracy: 0.8618
Epoch 72/100
2/2 [==============================] - 0s 45ms/step - loss: 0.9718 - accuracy: 0.8934 - val_loss: 1.0868 - val_accuracy: 0.8618
Epoch 73/100
2/2 [==============================] - 0s 52ms/step - loss: 0.9597 - accuracy: 0.9016 - val_loss: 1.0769 - val_accuracy: 0.8618
Epoch 74/100
2/2 [==============================] - 0s 52ms/step - loss: 0.9448 - accuracy: 0.8984 - val_loss: 1.0672 - val_accuracy: 0.8618
Epoch 75/100
2/2 [==============================] - 0s 32ms/step - loss: 0.9383 - accuracy: 0.9098 - val_loss: 1.0586 - val_accuracy: 0.8618
Epoch 76/100
2/2 [==============================] - 0s 47ms/step - loss: 0.9137 - accuracy: 0.9016 - val_loss: 1.0495 - val_accuracy: 0.8618
Epoch 77/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9238 - accuracy: 0.8934 - val_loss: 1.0396 - val_accuracy: 0.8618
Epoch 78/100
2/2 [==============================] - 0s 48ms/step - loss: 0.8948 - accuracy: 0.8951 - val_loss: 1.0299 - val_accuracy: 0.8618
Epoch 79/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8843 - accuracy: 0.9049 - val_loss: 1.0208 - val_accuracy: 0.8618
Epoch 80/100
2/2 [==============================] - 0s 42ms/step - loss: 0.9012 - accuracy: 0.8869 - val_loss: 1.0125 - val_accuracy: 0.8618
Epoch 81/100
2/2 [==============================] - 0s 45ms/step - loss: 0.8780 - accuracy: 0.9000 - val_loss: 1.0035 - val_accuracy: 0.8618
Epoch 82/100
2/2 [==============================] - 0s 50ms/step - loss: 0.8607 - accuracy: 0.8918 - val_loss: 0.9946 - val_accuracy: 0.8618
Epoch 83/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8530 - accuracy: 0.8951 - val_loss: 0.9861 - val_accuracy: 0.8618
Epoch 84/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8577 - accuracy: 0.8820 - val_loss: 0.9770 - val_accuracy: 0.8618
Epoch 85/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8161 - accuracy: 0.9131 - val_loss: 0.9677 - val_accuracy: 0.8618
Epoch 86/100
2/2 [==============================] - 0s 34ms/step - loss: 0.8195 - accuracy: 0.9115 - val_loss: 0.9586 - val_accuracy: 0.8618
Epoch 87/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8239 - accuracy: 0.8934 - val_loss: 0.9498 - val_accuracy: 0.8618
Epoch 88/100
2/2 [==============================] - 0s 37ms/step - loss: 0.8074 - accuracy: 0.9016 - val_loss: 0.9413 - val_accuracy: 0.8618
Epoch 89/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7917 - accuracy: 0.9082 - val_loss: 0.9334 - val_accuracy: 0.8618
Epoch 90/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7740 - accuracy: 0.9115 - val_loss: 0.9257 - val_accuracy: 0.8618
Epoch 91/100
2/2 [==============================] - 0s 33ms/step - loss: 0.7796 - accuracy: 0.9000 - val_loss: 0.9189 - val_accuracy: 0.8618
Epoch 92/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7749 - accuracy: 0.9049 - val_loss: 0.9121 - val_accuracy: 0.8618
Epoch 93/100
2/2 [==============================] - 0s 49ms/step - loss: 0.7594 - accuracy: 0.9049 - val_loss: 0.9042 - val_accuracy: 0.8618
Epoch 94/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7479 - accuracy: 0.8934 - val_loss: 0.8960 - val_accuracy: 0.8618
Epoch 95/100
2/2 [==============================] - 0s 38ms/step - loss: 0.7300 - accuracy: 0.9115 - val_loss: 0.8880 - val_accuracy: 0.8618
Epoch 96/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7165 - accuracy: 0.9148 - val_loss: 0.8803 - val_accuracy: 0.8618
Epoch 97/100
2/2 [==============================] - 0s 36ms/step - loss: 0.7222 - accuracy: 0.8967 - val_loss: 0.8732 - val_accuracy: 0.8618
Epoch 98/100
2/2 [==============================] - 0s 35ms/step - loss: 0.7099 - accuracy: 0.9197 - val_loss: 0.8669 - val_accuracy: 0.8618
Epoch 99/100
2/2 [==============================] - 0s 41ms/step - loss: 0.7234 - accuracy: 0.8951 - val_loss: 0.8606 - val_accuracy: 0.8618
Epoch 100/100
2/2 [==============================] - 0s 37ms/step - loss: 0.7041 - accuracy: 0.9000 - val_loss: 0.8533 - val_accuracy: 0.8618
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 3
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 32, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.8, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'he_uniform'}
Batch size: 256
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
3/3 [==============================] - 1s 117ms/step - loss: 3.8426 - accuracy: 0.1856 - val_loss: 3.8021 - val_accuracy: 0.1541
Epoch 2/100
3/3 [==============================] - 0s 23ms/step - loss: 3.8204 - accuracy: 0.1823 - val_loss: 3.7989 - val_accuracy: 0.1541
Epoch 3/100
3/3 [==============================] - 0s 16ms/step - loss: 3.8422 - accuracy: 0.1954 - val_loss: 3.7949 - val_accuracy: 0.1541
Epoch 4/100
3/3 [==============================] - 0s 18ms/step - loss: 3.8260 - accuracy: 0.1888 - val_loss: 3.7905 - val_accuracy: 0.1574
Epoch 5/100
3/3 [==============================] - 0s 24ms/step - loss: 3.8151 - accuracy: 0.1905 - val_loss: 3.7860 - val_accuracy: 0.1574
Epoch 6/100
3/3 [==============================] - 0s 24ms/step - loss: 3.7961 - accuracy: 0.2069 - val_loss: 3.7813 - val_accuracy: 0.1574
Epoch 7/100
3/3 [==============================] - 0s 18ms/step - loss: 3.8018 - accuracy: 0.1921 - val_loss: 3.7766 - val_accuracy: 0.1607
Epoch 8/100
3/3 [==============================] - 0s 28ms/step - loss: 3.8062 - accuracy: 0.2003 - val_loss: 3.7718 - val_accuracy: 0.1607
Epoch 9/100
3/3 [==============================] - 0s 20ms/step - loss: 3.7979 - accuracy: 0.1970 - val_loss: 3.7671 - val_accuracy: 0.1607
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 3.8075 - accuracy: 0.1970 - val_loss: 3.7623 - val_accuracy: 0.1607
Epoch 11/100
3/3 [==============================] - 0s 21ms/step - loss: 3.8309 - accuracy: 0.1839 - val_loss: 3.7576 - val_accuracy: 0.1607
Epoch 12/100
3/3 [==============================] - 0s 25ms/step - loss: 3.8195 - accuracy: 0.1790 - val_loss: 3.7529 - val_accuracy: 0.1607
Epoch 13/100
3/3 [==============================] - 0s 24ms/step - loss: 3.7854 - accuracy: 0.1987 - val_loss: 3.7482 - val_accuracy: 0.1607
Epoch 14/100
3/3 [==============================] - 0s 26ms/step - loss: 3.7526 - accuracy: 0.1921 - val_loss: 3.7436 - val_accuracy: 0.1607
Epoch 15/100
3/3 [==============================] - 0s 26ms/step - loss: 3.7736 - accuracy: 0.2085 - val_loss: 3.7390 - val_accuracy: 0.1607
Epoch 16/100
3/3 [==============================] - 0s 19ms/step - loss: 3.7776 - accuracy: 0.2184 - val_loss: 3.7344 - val_accuracy: 0.1607
Epoch 17/100
3/3 [==============================] - 0s 19ms/step - loss: 3.7244 - accuracy: 0.2200 - val_loss: 3.7299 - val_accuracy: 0.1607
Epoch 18/100
3/3 [==============================] - 0s 16ms/step - loss: 3.7819 - accuracy: 0.2085 - val_loss: 3.7253 - val_accuracy: 0.1639
Epoch 19/100
3/3 [==============================] - 0s 20ms/step - loss: 3.8210 - accuracy: 0.1724 - val_loss: 3.7207 - val_accuracy: 0.1639
Epoch 20/100
3/3 [==============================] - 0s 25ms/step - loss: 3.7357 - accuracy: 0.2118 - val_loss: 3.7162 - val_accuracy: 0.1672
Epoch 21/100
3/3 [==============================] - 0s 25ms/step - loss: 3.7256 - accuracy: 0.2135 - val_loss: 3.7117 - val_accuracy: 0.1672
Epoch 22/100
3/3 [==============================] - 0s 26ms/step - loss: 3.7686 - accuracy: 0.2069 - val_loss: 3.7072 - val_accuracy: 0.1705
Epoch 23/100
3/3 [==============================] - 0s 26ms/step - loss: 3.7339 - accuracy: 0.2167 - val_loss: 3.7027 - val_accuracy: 0.1738
Epoch 24/100
3/3 [==============================] - 0s 21ms/step - loss: 3.7678 - accuracy: 0.2118 - val_loss: 3.6982 - val_accuracy: 0.1738
Epoch 25/100
3/3 [==============================] - 0s 17ms/step - loss: 3.7581 - accuracy: 0.1987 - val_loss: 3.6938 - val_accuracy: 0.1738
Epoch 26/100
3/3 [==============================] - 0s 23ms/step - loss: 3.7323 - accuracy: 0.2069 - val_loss: 3.6893 - val_accuracy: 0.1770
Epoch 27/100
3/3 [==============================] - 0s 16ms/step - loss: 3.7002 - accuracy: 0.2053 - val_loss: 3.6849 - val_accuracy: 0.1770
Epoch 28/100
3/3 [==============================] - 0s 22ms/step - loss: 3.7162 - accuracy: 0.2365 - val_loss: 3.6805 - val_accuracy: 0.1836
Epoch 29/100
3/3 [==============================] - 0s 22ms/step - loss: 3.6994 - accuracy: 0.2447 - val_loss: 3.6761 - val_accuracy: 0.1836
Epoch 30/100
3/3 [==============================] - 0s 24ms/step - loss: 3.6826 - accuracy: 0.2069 - val_loss: 3.6718 - val_accuracy: 0.1836
Epoch 31/100
3/3 [==============================] - 0s 27ms/step - loss: 3.6859 - accuracy: 0.2233 - val_loss: 3.6674 - val_accuracy: 0.1836
Epoch 32/100
3/3 [==============================] - 0s 27ms/step - loss: 3.6890 - accuracy: 0.2463 - val_loss: 3.6630 - val_accuracy: 0.1836
Epoch 33/100
3/3 [==============================] - 0s 18ms/step - loss: 3.6719 - accuracy: 0.2151 - val_loss: 3.6587 - val_accuracy: 0.1836
Epoch 34/100
3/3 [==============================] - 0s 20ms/step - loss: 3.6967 - accuracy: 0.2184 - val_loss: 3.6544 - val_accuracy: 0.1836
Epoch 35/100
3/3 [==============================] - 0s 22ms/step - loss: 3.6792 - accuracy: 0.2250 - val_loss: 3.6500 - val_accuracy: 0.1902
Epoch 36/100
3/3 [==============================] - 0s 19ms/step - loss: 3.6391 - accuracy: 0.2414 - val_loss: 3.6457 - val_accuracy: 0.1902
Epoch 37/100
3/3 [==============================] - 0s 23ms/step - loss: 3.6413 - accuracy: 0.2562 - val_loss: 3.6415 - val_accuracy: 0.1902
Epoch 38/100
3/3 [==============================] - 0s 24ms/step - loss: 3.6612 - accuracy: 0.2053 - val_loss: 3.6373 - val_accuracy: 0.1967
Epoch 39/100
3/3 [==============================] - 0s 26ms/step - loss: 3.6596 - accuracy: 0.2479 - val_loss: 3.6330 - val_accuracy: 0.2000
Epoch 40/100
3/3 [==============================] - 0s 24ms/step - loss: 3.6190 - accuracy: 0.2677 - val_loss: 3.6288 - val_accuracy: 0.2033
Epoch 41/100
3/3 [==============================] - 0s 21ms/step - loss: 3.6653 - accuracy: 0.2315 - val_loss: 3.6246 - val_accuracy: 0.2033
Epoch 42/100
3/3 [==============================] - 0s 22ms/step - loss: 3.6278 - accuracy: 0.2348 - val_loss: 3.6204 - val_accuracy: 0.2033
Epoch 43/100
3/3 [==============================] - 0s 17ms/step - loss: 3.6477 - accuracy: 0.2233 - val_loss: 3.6162 - val_accuracy: 0.2066
Epoch 44/100
3/3 [==============================] - 0s 18ms/step - loss: 3.6375 - accuracy: 0.2430 - val_loss: 3.6119 - val_accuracy: 0.2066
Epoch 45/100
3/3 [==============================] - 0s 23ms/step - loss: 3.6094 - accuracy: 0.2726 - val_loss: 3.6077 - val_accuracy: 0.2033
Epoch 46/100
3/3 [==============================] - 0s 22ms/step - loss: 3.6412 - accuracy: 0.2479 - val_loss: 3.6036 - val_accuracy: 0.2066
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 3.6246 - accuracy: 0.2496 - val_loss: 3.5994 - val_accuracy: 0.2066
Epoch 48/100
3/3 [==============================] - 0s 17ms/step - loss: 3.6361 - accuracy: 0.2233 - val_loss: 3.5953 - val_accuracy: 0.2098
Epoch 49/100
3/3 [==============================] - 0s 17ms/step - loss: 3.6453 - accuracy: 0.2562 - val_loss: 3.5911 - val_accuracy: 0.2098
Epoch 50/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5837 - accuracy: 0.2545 - val_loss: 3.5870 - val_accuracy: 0.2098
Epoch 51/100
3/3 [==============================] - 0s 22ms/step - loss: 3.5931 - accuracy: 0.2791 - val_loss: 3.5828 - val_accuracy: 0.2098
Epoch 52/100
3/3 [==============================] - 0s 18ms/step - loss: 3.5745 - accuracy: 0.2594 - val_loss: 3.5787 - val_accuracy: 0.2098
Epoch 53/100
3/3 [==============================] - 0s 22ms/step - loss: 3.5816 - accuracy: 0.2693 - val_loss: 3.5746 - val_accuracy: 0.2131
Epoch 54/100
3/3 [==============================] - 0s 20ms/step - loss: 3.5824 - accuracy: 0.2775 - val_loss: 3.5705 - val_accuracy: 0.2164
Epoch 55/100
3/3 [==============================] - 0s 26ms/step - loss: 3.5710 - accuracy: 0.2644 - val_loss: 3.5664 - val_accuracy: 0.2230
Epoch 56/100
3/3 [==============================] - 0s 21ms/step - loss: 3.6105 - accuracy: 0.2233 - val_loss: 3.5623 - val_accuracy: 0.2230
Epoch 57/100
3/3 [==============================] - 0s 21ms/step - loss: 3.5796 - accuracy: 0.2594 - val_loss: 3.5582 - val_accuracy: 0.2262
Epoch 58/100
3/3 [==============================] - 0s 20ms/step - loss: 3.5698 - accuracy: 0.2742 - val_loss: 3.5541 - val_accuracy: 0.2262
Epoch 59/100
3/3 [==============================] - 0s 24ms/step - loss: 3.5777 - accuracy: 0.2381 - val_loss: 3.5501 - val_accuracy: 0.2328
Epoch 60/100
3/3 [==============================] - 0s 14ms/step - loss: 3.5911 - accuracy: 0.2414 - val_loss: 3.5461 - val_accuracy: 0.2361
Epoch 61/100
3/3 [==============================] - 0s 23ms/step - loss: 3.5601 - accuracy: 0.2693 - val_loss: 3.5420 - val_accuracy: 0.2361
Epoch 62/100
3/3 [==============================] - 0s 15ms/step - loss: 3.5631 - accuracy: 0.2693 - val_loss: 3.5380 - val_accuracy: 0.2361
Epoch 63/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5861 - accuracy: 0.2759 - val_loss: 3.5340 - val_accuracy: 0.2426
Epoch 64/100
3/3 [==============================] - 0s 23ms/step - loss: 3.5736 - accuracy: 0.2594 - val_loss: 3.5301 - val_accuracy: 0.2426
Epoch 65/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5833 - accuracy: 0.2677 - val_loss: 3.5261 - val_accuracy: 0.2459
Epoch 66/100
3/3 [==============================] - 0s 22ms/step - loss: 3.5584 - accuracy: 0.2874 - val_loss: 3.5221 - val_accuracy: 0.2459
Epoch 67/100
3/3 [==============================] - 0s 16ms/step - loss: 3.5221 - accuracy: 0.2709 - val_loss: 3.5181 - val_accuracy: 0.2459
Epoch 68/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4846 - accuracy: 0.3054 - val_loss: 3.5142 - val_accuracy: 0.2459
Epoch 69/100
3/3 [==============================] - 0s 16ms/step - loss: 3.5636 - accuracy: 0.2742 - val_loss: 3.5102 - val_accuracy: 0.2492
Epoch 70/100
3/3 [==============================] - 0s 18ms/step - loss: 3.5217 - accuracy: 0.2857 - val_loss: 3.5064 - val_accuracy: 0.2525
Epoch 71/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5191 - accuracy: 0.2956 - val_loss: 3.5025 - val_accuracy: 0.2557
Epoch 72/100
3/3 [==============================] - 0s 17ms/step - loss: 3.4939 - accuracy: 0.3235 - val_loss: 3.4986 - val_accuracy: 0.2557
Epoch 73/100
3/3 [==============================] - 0s 22ms/step - loss: 3.5305 - accuracy: 0.2824 - val_loss: 3.4947 - val_accuracy: 0.2557
Epoch 74/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5288 - accuracy: 0.2709 - val_loss: 3.4909 - val_accuracy: 0.2590
Epoch 75/100
3/3 [==============================] - 0s 18ms/step - loss: 3.5024 - accuracy: 0.3038 - val_loss: 3.4870 - val_accuracy: 0.2623
Epoch 76/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5003 - accuracy: 0.2956 - val_loss: 3.4831 - val_accuracy: 0.2623
Epoch 77/100
3/3 [==============================] - 0s 16ms/step - loss: 3.5235 - accuracy: 0.2726 - val_loss: 3.4793 - val_accuracy: 0.2623
Epoch 78/100
3/3 [==============================] - 0s 19ms/step - loss: 3.5098 - accuracy: 0.2989 - val_loss: 3.4755 - val_accuracy: 0.2623
Epoch 79/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4834 - accuracy: 0.2775 - val_loss: 3.4717 - val_accuracy: 0.2656
Epoch 80/100
3/3 [==============================] - 0s 19ms/step - loss: 3.4983 - accuracy: 0.3087 - val_loss: 3.4679 - val_accuracy: 0.2656
Epoch 81/100
3/3 [==============================] - 0s 25ms/step - loss: 3.5005 - accuracy: 0.3071 - val_loss: 3.4642 - val_accuracy: 0.2689
Epoch 82/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4785 - accuracy: 0.2989 - val_loss: 3.4605 - val_accuracy: 0.2721
Epoch 83/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4878 - accuracy: 0.2956 - val_loss: 3.4568 - val_accuracy: 0.2721
Epoch 84/100
3/3 [==============================] - 0s 23ms/step - loss: 3.4866 - accuracy: 0.2972 - val_loss: 3.4531 - val_accuracy: 0.2721
Epoch 85/100
3/3 [==============================] - 0s 24ms/step - loss: 3.4593 - accuracy: 0.3235 - val_loss: 3.4494 - val_accuracy: 0.2721
Epoch 86/100
3/3 [==============================] - 0s 24ms/step - loss: 3.4604 - accuracy: 0.3186 - val_loss: 3.4457 - val_accuracy: 0.2721
Epoch 87/100
3/3 [==============================] - 0s 19ms/step - loss: 3.4649 - accuracy: 0.2972 - val_loss: 3.4420 - val_accuracy: 0.2754
Epoch 88/100
3/3 [==============================] - 0s 19ms/step - loss: 3.4563 - accuracy: 0.3186 - val_loss: 3.4384 - val_accuracy: 0.2754
Epoch 89/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4303 - accuracy: 0.3235 - val_loss: 3.4348 - val_accuracy: 0.2820
Epoch 90/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4629 - accuracy: 0.3153 - val_loss: 3.4311 - val_accuracy: 0.2885
Epoch 91/100
3/3 [==============================] - 0s 25ms/step - loss: 3.4846 - accuracy: 0.2972 - val_loss: 3.4275 - val_accuracy: 0.2885
Epoch 92/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4224 - accuracy: 0.3350 - val_loss: 3.4238 - val_accuracy: 0.2918
Epoch 93/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4502 - accuracy: 0.3136 - val_loss: 3.4202 - val_accuracy: 0.2951
Epoch 94/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4150 - accuracy: 0.3333 - val_loss: 3.4166 - val_accuracy: 0.2951
Epoch 95/100
3/3 [==============================] - 0s 16ms/step - loss: 3.4292 - accuracy: 0.3021 - val_loss: 3.4130 - val_accuracy: 0.2951
Epoch 96/100
3/3 [==============================] - 0s 17ms/step - loss: 3.4395 - accuracy: 0.3284 - val_loss: 3.4095 - val_accuracy: 0.2984
Epoch 97/100
3/3 [==============================] - 0s 17ms/step - loss: 3.4387 - accuracy: 0.3235 - val_loss: 3.4059 - val_accuracy: 0.3016
Epoch 98/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4156 - accuracy: 0.3120 - val_loss: 3.4024 - val_accuracy: 0.3049
Epoch 99/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4481 - accuracy: 0.3169 - val_loss: 3.3988 - val_accuracy: 0.3049
Epoch 100/100
3/3 [==============================] - 0s 19ms/step - loss: 3.4071 - accuracy: 0.3350 - val_loss: 3.3953 - val_accuracy: 0.3082
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 32, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.8, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'he_uniform'}
Batch size: 256
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
3/3 [==============================] - 1s 111ms/step - loss: 3.2371 - accuracy: 0.5813 - val_loss: 3.1120 - val_accuracy: 0.7246
Epoch 2/100
3/3 [==============================] - 0s 22ms/step - loss: 3.2574 - accuracy: 0.5649 - val_loss: 3.1103 - val_accuracy: 0.7246
Epoch 3/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2502 - accuracy: 0.5846 - val_loss: 3.1081 - val_accuracy: 0.7279
Epoch 4/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2303 - accuracy: 0.5829 - val_loss: 3.1058 - val_accuracy: 0.7279
Epoch 5/100
3/3 [==============================] - 0s 15ms/step - loss: 3.2549 - accuracy: 0.5731 - val_loss: 3.1034 - val_accuracy: 0.7279
Epoch 6/100
3/3 [==============================] - 0s 21ms/step - loss: 3.2489 - accuracy: 0.6026 - val_loss: 3.1009 - val_accuracy: 0.7311
Epoch 7/100
3/3 [==============================] - 0s 16ms/step - loss: 3.2134 - accuracy: 0.6190 - val_loss: 3.0984 - val_accuracy: 0.7311
Epoch 8/100
3/3 [==============================] - 0s 21ms/step - loss: 3.2205 - accuracy: 0.6108 - val_loss: 3.0959 - val_accuracy: 0.7311
Epoch 9/100
3/3 [==============================] - 0s 18ms/step - loss: 3.2096 - accuracy: 0.6092 - val_loss: 3.0934 - val_accuracy: 0.7344
Epoch 10/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1917 - accuracy: 0.6256 - val_loss: 3.0909 - val_accuracy: 0.7344
Epoch 11/100
3/3 [==============================] - 0s 18ms/step - loss: 3.2392 - accuracy: 0.5649 - val_loss: 3.0883 - val_accuracy: 0.7344
Epoch 12/100
3/3 [==============================] - 0s 29ms/step - loss: 3.1795 - accuracy: 0.6322 - val_loss: 3.0859 - val_accuracy: 0.7344
Epoch 13/100
3/3 [==============================] - 0s 16ms/step - loss: 3.2307 - accuracy: 0.5961 - val_loss: 3.0834 - val_accuracy: 0.7410
Epoch 14/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1961 - accuracy: 0.6141 - val_loss: 3.0809 - val_accuracy: 0.7410
Epoch 15/100
3/3 [==============================] - 0s 22ms/step - loss: 3.2043 - accuracy: 0.5911 - val_loss: 3.0784 - val_accuracy: 0.7410
Epoch 16/100
3/3 [==============================] - 0s 30ms/step - loss: 3.2350 - accuracy: 0.5862 - val_loss: 3.0759 - val_accuracy: 0.7410
Epoch 17/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1973 - accuracy: 0.5977 - val_loss: 3.0734 - val_accuracy: 0.7443
Epoch 18/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1735 - accuracy: 0.6108 - val_loss: 3.0709 - val_accuracy: 0.7443
Epoch 19/100
3/3 [==============================] - 0s 17ms/step - loss: 3.1951 - accuracy: 0.6059 - val_loss: 3.0684 - val_accuracy: 0.7443
Epoch 20/100
3/3 [==============================] - 0s 18ms/step - loss: 3.1806 - accuracy: 0.6174 - val_loss: 3.0660 - val_accuracy: 0.7443
Epoch 21/100
3/3 [==============================] - 0s 17ms/step - loss: 3.1749 - accuracy: 0.6256 - val_loss: 3.0635 - val_accuracy: 0.7443
Epoch 22/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1979 - accuracy: 0.6108 - val_loss: 3.0610 - val_accuracy: 0.7443
Epoch 23/100
3/3 [==============================] - 0s 18ms/step - loss: 3.1911 - accuracy: 0.6190 - val_loss: 3.0586 - val_accuracy: 0.7475
Epoch 24/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1694 - accuracy: 0.5993 - val_loss: 3.0561 - val_accuracy: 0.7475
Epoch 25/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1552 - accuracy: 0.6388 - val_loss: 3.0537 - val_accuracy: 0.7475
Epoch 26/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1567 - accuracy: 0.6174 - val_loss: 3.0513 - val_accuracy: 0.7475
Epoch 27/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1986 - accuracy: 0.5829 - val_loss: 3.0488 - val_accuracy: 0.7475
Epoch 28/100
3/3 [==============================] - 0s 26ms/step - loss: 3.1591 - accuracy: 0.6108 - val_loss: 3.0464 - val_accuracy: 0.7508
Epoch 29/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1529 - accuracy: 0.6355 - val_loss: 3.0440 - val_accuracy: 0.7508
Epoch 30/100
3/3 [==============================] - 0s 18ms/step - loss: 3.1752 - accuracy: 0.5878 - val_loss: 3.0415 - val_accuracy: 0.7508
Epoch 31/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1620 - accuracy: 0.6158 - val_loss: 3.0391 - val_accuracy: 0.7508
Epoch 32/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1955 - accuracy: 0.6059 - val_loss: 3.0367 - val_accuracy: 0.7508
Epoch 33/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1780 - accuracy: 0.6026 - val_loss: 3.0342 - val_accuracy: 0.7508
Epoch 34/100
3/3 [==============================] - 0s 17ms/step - loss: 3.1820 - accuracy: 0.6043 - val_loss: 3.0318 - val_accuracy: 0.7508
Epoch 35/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1550 - accuracy: 0.6273 - val_loss: 3.0294 - val_accuracy: 0.7508
Epoch 36/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1781 - accuracy: 0.6289 - val_loss: 3.0271 - val_accuracy: 0.7508
Epoch 37/100
3/3 [==============================] - 0s 17ms/step - loss: 3.1264 - accuracy: 0.6388 - val_loss: 3.0247 - val_accuracy: 0.7508
Epoch 38/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1422 - accuracy: 0.6388 - val_loss: 3.0224 - val_accuracy: 0.7541
Epoch 39/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1754 - accuracy: 0.6108 - val_loss: 3.0200 - val_accuracy: 0.7574
Epoch 40/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1350 - accuracy: 0.6388 - val_loss: 3.0177 - val_accuracy: 0.7607
Epoch 41/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1458 - accuracy: 0.6273 - val_loss: 3.0153 - val_accuracy: 0.7639
Epoch 42/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1349 - accuracy: 0.6240 - val_loss: 3.0129 - val_accuracy: 0.7639
Epoch 43/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1049 - accuracy: 0.6486 - val_loss: 3.0106 - val_accuracy: 0.7672
Epoch 44/100
3/3 [==============================] - 0s 26ms/step - loss: 3.1440 - accuracy: 0.6125 - val_loss: 3.0082 - val_accuracy: 0.7672
Epoch 45/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1472 - accuracy: 0.5977 - val_loss: 3.0058 - val_accuracy: 0.7672
Epoch 46/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1296 - accuracy: 0.6141 - val_loss: 3.0035 - val_accuracy: 0.7705
Epoch 47/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1337 - accuracy: 0.6141 - val_loss: 3.0011 - val_accuracy: 0.7705
Epoch 48/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1275 - accuracy: 0.6158 - val_loss: 2.9988 - val_accuracy: 0.7705
Epoch 49/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1429 - accuracy: 0.6043 - val_loss: 2.9964 - val_accuracy: 0.7705
Epoch 50/100
3/3 [==============================] - 0s 18ms/step - loss: 3.0918 - accuracy: 0.6650 - val_loss: 2.9940 - val_accuracy: 0.7705
Epoch 51/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1360 - accuracy: 0.6207 - val_loss: 2.9917 - val_accuracy: 0.7705
Epoch 52/100
3/3 [==============================] - 0s 20ms/step - loss: 3.0885 - accuracy: 0.6305 - val_loss: 2.9894 - val_accuracy: 0.7705
Epoch 53/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1469 - accuracy: 0.6207 - val_loss: 2.9871 - val_accuracy: 0.7705
Epoch 54/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1359 - accuracy: 0.6519 - val_loss: 2.9848 - val_accuracy: 0.7705
Epoch 55/100
3/3 [==============================] - 0s 19ms/step - loss: 3.0917 - accuracy: 0.6667 - val_loss: 2.9825 - val_accuracy: 0.7705
Epoch 56/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1350 - accuracy: 0.5993 - val_loss: 2.9802 - val_accuracy: 0.7705
Epoch 57/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1223 - accuracy: 0.6207 - val_loss: 2.9779 - val_accuracy: 0.7738
Epoch 58/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1002 - accuracy: 0.6322 - val_loss: 2.9756 - val_accuracy: 0.7770
Epoch 59/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0809 - accuracy: 0.6617 - val_loss: 2.9733 - val_accuracy: 0.7770
Epoch 60/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1026 - accuracy: 0.6322 - val_loss: 2.9711 - val_accuracy: 0.7770
Epoch 61/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1083 - accuracy: 0.6273 - val_loss: 2.9688 - val_accuracy: 0.7770
Epoch 62/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0759 - accuracy: 0.6568 - val_loss: 2.9665 - val_accuracy: 0.7770
Epoch 63/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0882 - accuracy: 0.6568 - val_loss: 2.9643 - val_accuracy: 0.7770
Epoch 64/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0593 - accuracy: 0.6617 - val_loss: 2.9621 - val_accuracy: 0.7770
Epoch 65/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1107 - accuracy: 0.6420 - val_loss: 2.9599 - val_accuracy: 0.7770
Epoch 66/100
3/3 [==============================] - 0s 24ms/step - loss: 3.0724 - accuracy: 0.6453 - val_loss: 2.9576 - val_accuracy: 0.7770
Epoch 67/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0831 - accuracy: 0.6552 - val_loss: 2.9554 - val_accuracy: 0.7770
Epoch 68/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0868 - accuracy: 0.6355 - val_loss: 2.9532 - val_accuracy: 0.7770
Epoch 69/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0835 - accuracy: 0.6420 - val_loss: 2.9509 - val_accuracy: 0.7770
Epoch 70/100
3/3 [==============================] - 0s 27ms/step - loss: 3.0898 - accuracy: 0.6502 - val_loss: 2.9487 - val_accuracy: 0.7770
Epoch 71/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0806 - accuracy: 0.6289 - val_loss: 2.9464 - val_accuracy: 0.7770
Epoch 72/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0456 - accuracy: 0.6683 - val_loss: 2.9442 - val_accuracy: 0.7770
Epoch 73/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0416 - accuracy: 0.6437 - val_loss: 2.9420 - val_accuracy: 0.7770
Epoch 74/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0529 - accuracy: 0.6486 - val_loss: 2.9398 - val_accuracy: 0.7770
Epoch 75/100
3/3 [==============================] - 0s 20ms/step - loss: 3.0559 - accuracy: 0.6617 - val_loss: 2.9376 - val_accuracy: 0.7803
Epoch 76/100
3/3 [==============================] - 0s 24ms/step - loss: 3.0624 - accuracy: 0.6486 - val_loss: 2.9354 - val_accuracy: 0.7836
Epoch 77/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0624 - accuracy: 0.6585 - val_loss: 2.9332 - val_accuracy: 0.7836
Epoch 78/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0863 - accuracy: 0.6535 - val_loss: 2.9310 - val_accuracy: 0.7869
Epoch 79/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0433 - accuracy: 0.6486 - val_loss: 2.9288 - val_accuracy: 0.7869
Epoch 80/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0317 - accuracy: 0.6585 - val_loss: 2.9267 - val_accuracy: 0.7869
Epoch 81/100
3/3 [==============================] - 0s 20ms/step - loss: 3.0662 - accuracy: 0.6486 - val_loss: 2.9245 - val_accuracy: 0.7869
Epoch 82/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0261 - accuracy: 0.6814 - val_loss: 2.9223 - val_accuracy: 0.7869
Epoch 83/100
3/3 [==============================] - 0s 20ms/step - loss: 3.0304 - accuracy: 0.6732 - val_loss: 2.9202 - val_accuracy: 0.7869
Epoch 84/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0342 - accuracy: 0.6716 - val_loss: 2.9180 - val_accuracy: 0.7869
Epoch 85/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0722 - accuracy: 0.6289 - val_loss: 2.9159 - val_accuracy: 0.7869
Epoch 86/100
3/3 [==============================] - 0s 15ms/step - loss: 3.0298 - accuracy: 0.6749 - val_loss: 2.9137 - val_accuracy: 0.7869
Epoch 87/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0602 - accuracy: 0.6355 - val_loss: 2.9116 - val_accuracy: 0.7869
Epoch 88/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0560 - accuracy: 0.6388 - val_loss: 2.9094 - val_accuracy: 0.7869
Epoch 89/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0121 - accuracy: 0.6749 - val_loss: 2.9072 - val_accuracy: 0.7902
Epoch 90/100
3/3 [==============================] - 0s 20ms/step - loss: 3.0330 - accuracy: 0.6601 - val_loss: 2.9051 - val_accuracy: 0.7902
Epoch 91/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0254 - accuracy: 0.6420 - val_loss: 2.9029 - val_accuracy: 0.7902
Epoch 92/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0149 - accuracy: 0.6552 - val_loss: 2.9008 - val_accuracy: 0.7902
Epoch 93/100
3/3 [==============================] - 0s 20ms/step - loss: 3.0499 - accuracy: 0.6240 - val_loss: 2.8986 - val_accuracy: 0.7902
Epoch 94/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0323 - accuracy: 0.6240 - val_loss: 2.8965 - val_accuracy: 0.7902
Epoch 95/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0310 - accuracy: 0.6289 - val_loss: 2.8943 - val_accuracy: 0.7902
Epoch 96/100
3/3 [==============================] - 0s 45ms/step - loss: 3.0062 - accuracy: 0.6683 - val_loss: 2.8922 - val_accuracy: 0.7902
Epoch 97/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0090 - accuracy: 0.6782 - val_loss: 2.8901 - val_accuracy: 0.7902
Epoch 98/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0166 - accuracy: 0.6601 - val_loss: 2.8880 - val_accuracy: 0.7902
Epoch 99/100
3/3 [==============================] - 0s 22ms/step - loss: 2.9947 - accuracy: 0.6782 - val_loss: 2.8859 - val_accuracy: 0.7902
Epoch 100/100
3/3 [==============================] - 0s 18ms/step - loss: 2.9839 - accuracy: 0.6667 - val_loss: 2.8838 - val_accuracy: 0.7902
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 3, 'hidden_units': 32, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.8, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'he_uniform'}
Batch size: 256
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
3/3 [==============================] - 1s 118ms/step - loss: 3.4503 - accuracy: 0.3459 - val_loss: 3.3661 - val_accuracy: 0.3520
Epoch 2/100
3/3 [==============================] - 0s 19ms/step - loss: 3.4717 - accuracy: 0.3557 - val_loss: 3.3634 - val_accuracy: 0.3520
Epoch 3/100
3/3 [==============================] - 0s 22ms/step - loss: 3.4541 - accuracy: 0.3492 - val_loss: 3.3601 - val_accuracy: 0.3553
Epoch 4/100
3/3 [==============================] - 0s 23ms/step - loss: 3.4531 - accuracy: 0.3508 - val_loss: 3.3563 - val_accuracy: 0.3553
Epoch 5/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4401 - accuracy: 0.3557 - val_loss: 3.3524 - val_accuracy: 0.3553
Epoch 6/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4722 - accuracy: 0.3557 - val_loss: 3.3484 - val_accuracy: 0.3586
Epoch 7/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4511 - accuracy: 0.3656 - val_loss: 3.3444 - val_accuracy: 0.3618
Epoch 8/100
3/3 [==============================] - 0s 18ms/step - loss: 3.4419 - accuracy: 0.3623 - val_loss: 3.3404 - val_accuracy: 0.3586
Epoch 9/100
3/3 [==============================] - 0s 23ms/step - loss: 3.3972 - accuracy: 0.3607 - val_loss: 3.3364 - val_accuracy: 0.3618
Epoch 10/100
3/3 [==============================] - 0s 22ms/step - loss: 3.4251 - accuracy: 0.3656 - val_loss: 3.3325 - val_accuracy: 0.3651
Epoch 11/100
3/3 [==============================] - 0s 22ms/step - loss: 3.4182 - accuracy: 0.3705 - val_loss: 3.3286 - val_accuracy: 0.3651
Epoch 12/100
3/3 [==============================] - 0s 17ms/step - loss: 3.4296 - accuracy: 0.3475 - val_loss: 3.3246 - val_accuracy: 0.3684
Epoch 13/100
3/3 [==============================] - 0s 23ms/step - loss: 3.3970 - accuracy: 0.3918 - val_loss: 3.3206 - val_accuracy: 0.3684
Epoch 14/100
3/3 [==============================] - 0s 22ms/step - loss: 3.3999 - accuracy: 0.3803 - val_loss: 3.3167 - val_accuracy: 0.3684
Epoch 15/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4146 - accuracy: 0.3852 - val_loss: 3.3128 - val_accuracy: 0.3684
Epoch 16/100
3/3 [==============================] - 0s 21ms/step - loss: 3.3675 - accuracy: 0.3852 - val_loss: 3.3089 - val_accuracy: 0.3684
Epoch 17/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4110 - accuracy: 0.3770 - val_loss: 3.3050 - val_accuracy: 0.3783
Epoch 18/100
3/3 [==============================] - 0s 21ms/step - loss: 3.3738 - accuracy: 0.4033 - val_loss: 3.3012 - val_accuracy: 0.3816
Epoch 19/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4036 - accuracy: 0.3836 - val_loss: 3.2974 - val_accuracy: 0.3783
Epoch 20/100
3/3 [==============================] - 0s 18ms/step - loss: 3.4109 - accuracy: 0.3623 - val_loss: 3.2935 - val_accuracy: 0.3849
Epoch 21/100
3/3 [==============================] - 0s 17ms/step - loss: 3.3653 - accuracy: 0.3803 - val_loss: 3.2896 - val_accuracy: 0.3849
Epoch 22/100
3/3 [==============================] - 0s 18ms/step - loss: 3.3882 - accuracy: 0.3689 - val_loss: 3.2858 - val_accuracy: 0.3914
Epoch 23/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3799 - accuracy: 0.3689 - val_loss: 3.2820 - val_accuracy: 0.3980
Epoch 24/100
3/3 [==============================] - 0s 17ms/step - loss: 3.3584 - accuracy: 0.3803 - val_loss: 3.2782 - val_accuracy: 0.3980
Epoch 25/100
3/3 [==============================] - 0s 17ms/step - loss: 3.3957 - accuracy: 0.3705 - val_loss: 3.2744 - val_accuracy: 0.4079
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 3.3762 - accuracy: 0.3705 - val_loss: 3.2706 - val_accuracy: 0.4145
Epoch 27/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3921 - accuracy: 0.3787 - val_loss: 3.2668 - val_accuracy: 0.4145
Epoch 28/100
3/3 [==============================] - 0s 27ms/step - loss: 3.3203 - accuracy: 0.4213 - val_loss: 3.2631 - val_accuracy: 0.4211
Epoch 29/100
3/3 [==============================] - 0s 21ms/step - loss: 3.3537 - accuracy: 0.3902 - val_loss: 3.2594 - val_accuracy: 0.4243
Epoch 30/100
3/3 [==============================] - 0s 21ms/step - loss: 3.3630 - accuracy: 0.3836 - val_loss: 3.2556 - val_accuracy: 0.4276
Epoch 31/100
3/3 [==============================] - 0s 24ms/step - loss: 3.3482 - accuracy: 0.3951 - val_loss: 3.2519 - val_accuracy: 0.4276
Epoch 32/100
3/3 [==============================] - 0s 18ms/step - loss: 3.3198 - accuracy: 0.4098 - val_loss: 3.2482 - val_accuracy: 0.4309
Epoch 33/100
3/3 [==============================] - 0s 21ms/step - loss: 3.3357 - accuracy: 0.3967 - val_loss: 3.2445 - val_accuracy: 0.4309
Epoch 34/100
3/3 [==============================] - 0s 20ms/step - loss: 3.3662 - accuracy: 0.3754 - val_loss: 3.2407 - val_accuracy: 0.4276
Epoch 35/100
3/3 [==============================] - 0s 24ms/step - loss: 3.3448 - accuracy: 0.3967 - val_loss: 3.2369 - val_accuracy: 0.4309
Epoch 36/100
3/3 [==============================] - 0s 24ms/step - loss: 3.3478 - accuracy: 0.4049 - val_loss: 3.2332 - val_accuracy: 0.4342
Epoch 37/100
3/3 [==============================] - 0s 21ms/step - loss: 3.3244 - accuracy: 0.4033 - val_loss: 3.2295 - val_accuracy: 0.4375
Epoch 38/100
3/3 [==============================] - 0s 24ms/step - loss: 3.3354 - accuracy: 0.3836 - val_loss: 3.2258 - val_accuracy: 0.4474
Epoch 39/100
3/3 [==============================] - 0s 20ms/step - loss: 3.3129 - accuracy: 0.4246 - val_loss: 3.2221 - val_accuracy: 0.4441
Epoch 40/100
3/3 [==============================] - 0s 19ms/step - loss: 3.3050 - accuracy: 0.4410 - val_loss: 3.2185 - val_accuracy: 0.4474
Epoch 41/100
3/3 [==============================] - 0s 19ms/step - loss: 3.2939 - accuracy: 0.4148 - val_loss: 3.2149 - val_accuracy: 0.4539
Epoch 42/100
3/3 [==============================] - 0s 18ms/step - loss: 3.3234 - accuracy: 0.3918 - val_loss: 3.2114 - val_accuracy: 0.4539
Epoch 43/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2926 - accuracy: 0.4213 - val_loss: 3.2078 - val_accuracy: 0.4605
Epoch 44/100
3/3 [==============================] - 0s 21ms/step - loss: 3.2872 - accuracy: 0.4525 - val_loss: 3.2043 - val_accuracy: 0.4605
Epoch 45/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2797 - accuracy: 0.4492 - val_loss: 3.2008 - val_accuracy: 0.4605
Epoch 46/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2683 - accuracy: 0.4180 - val_loss: 3.1974 - val_accuracy: 0.4605
Epoch 47/100
3/3 [==============================] - 0s 19ms/step - loss: 3.2802 - accuracy: 0.4213 - val_loss: 3.1939 - val_accuracy: 0.4671
Epoch 48/100
3/3 [==============================] - 0s 22ms/step - loss: 3.3069 - accuracy: 0.4213 - val_loss: 3.1904 - val_accuracy: 0.4671
Epoch 49/100
3/3 [==============================] - 0s 18ms/step - loss: 3.2752 - accuracy: 0.4262 - val_loss: 3.1868 - val_accuracy: 0.4671
Epoch 50/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2655 - accuracy: 0.4475 - val_loss: 3.1834 - val_accuracy: 0.4704
Epoch 51/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2862 - accuracy: 0.4590 - val_loss: 3.1799 - val_accuracy: 0.4737
Epoch 52/100
3/3 [==============================] - 0s 18ms/step - loss: 3.2848 - accuracy: 0.4262 - val_loss: 3.1765 - val_accuracy: 0.4737
Epoch 53/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2791 - accuracy: 0.4262 - val_loss: 3.1731 - val_accuracy: 0.4737
Epoch 54/100
3/3 [==============================] - 0s 18ms/step - loss: 3.2749 - accuracy: 0.4262 - val_loss: 3.1696 - val_accuracy: 0.4770
Epoch 55/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2444 - accuracy: 0.4541 - val_loss: 3.1661 - val_accuracy: 0.4737
Epoch 56/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2716 - accuracy: 0.4377 - val_loss: 3.1626 - val_accuracy: 0.4770
Epoch 57/100
3/3 [==============================] - 0s 18ms/step - loss: 3.2439 - accuracy: 0.4410 - val_loss: 3.1592 - val_accuracy: 0.4770
Epoch 58/100
3/3 [==============================] - 0s 16ms/step - loss: 3.2387 - accuracy: 0.4475 - val_loss: 3.1558 - val_accuracy: 0.4770
Epoch 59/100
3/3 [==============================] - 0s 17ms/step - loss: 3.2620 - accuracy: 0.4213 - val_loss: 3.1525 - val_accuracy: 0.4770
Epoch 60/100
3/3 [==============================] - 0s 18ms/step - loss: 3.2439 - accuracy: 0.4426 - val_loss: 3.1491 - val_accuracy: 0.4803
Epoch 61/100
3/3 [==============================] - 0s 17ms/step - loss: 3.2576 - accuracy: 0.4262 - val_loss: 3.1456 - val_accuracy: 0.4803
Epoch 62/100
3/3 [==============================] - 0s 26ms/step - loss: 3.2320 - accuracy: 0.4738 - val_loss: 3.1423 - val_accuracy: 0.4836
Epoch 63/100
3/3 [==============================] - 0s 21ms/step - loss: 3.2219 - accuracy: 0.4705 - val_loss: 3.1389 - val_accuracy: 0.4836
Epoch 64/100
3/3 [==============================] - 0s 24ms/step - loss: 3.2285 - accuracy: 0.4279 - val_loss: 3.1355 - val_accuracy: 0.4836
Epoch 65/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2206 - accuracy: 0.4508 - val_loss: 3.1322 - val_accuracy: 0.4868
Epoch 66/100
3/3 [==============================] - 0s 22ms/step - loss: 3.2237 - accuracy: 0.4820 - val_loss: 3.1288 - val_accuracy: 0.4934
Epoch 67/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1989 - accuracy: 0.4934 - val_loss: 3.1255 - val_accuracy: 0.5000
Epoch 68/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1958 - accuracy: 0.4705 - val_loss: 3.1223 - val_accuracy: 0.5066
Epoch 69/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1749 - accuracy: 0.5016 - val_loss: 3.1191 - val_accuracy: 0.5197
Epoch 70/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2047 - accuracy: 0.4787 - val_loss: 3.1158 - val_accuracy: 0.5197
Epoch 71/100
3/3 [==============================] - 0s 21ms/step - loss: 3.2127 - accuracy: 0.4492 - val_loss: 3.1126 - val_accuracy: 0.5263
Epoch 72/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1814 - accuracy: 0.4852 - val_loss: 3.1093 - val_accuracy: 0.5230
Epoch 73/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1941 - accuracy: 0.4836 - val_loss: 3.1061 - val_accuracy: 0.5230
Epoch 74/100
3/3 [==============================] - 0s 21ms/step - loss: 3.2112 - accuracy: 0.4787 - val_loss: 3.1028 - val_accuracy: 0.5296
Epoch 75/100
3/3 [==============================] - 0s 15ms/step - loss: 3.1752 - accuracy: 0.4672 - val_loss: 3.0995 - val_accuracy: 0.5329
Epoch 76/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1948 - accuracy: 0.4607 - val_loss: 3.0963 - val_accuracy: 0.5362
Epoch 77/100
3/3 [==============================] - 0s 18ms/step - loss: 3.1604 - accuracy: 0.4803 - val_loss: 3.0931 - val_accuracy: 0.5362
Epoch 78/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1806 - accuracy: 0.4803 - val_loss: 3.0899 - val_accuracy: 0.5395
Epoch 79/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1757 - accuracy: 0.4852 - val_loss: 3.0867 - val_accuracy: 0.5461
Epoch 80/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1588 - accuracy: 0.4820 - val_loss: 3.0836 - val_accuracy: 0.5559
Epoch 81/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1254 - accuracy: 0.5016 - val_loss: 3.0805 - val_accuracy: 0.5559
Epoch 82/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1778 - accuracy: 0.4738 - val_loss: 3.0774 - val_accuracy: 0.5625
Epoch 83/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1509 - accuracy: 0.4885 - val_loss: 3.0743 - val_accuracy: 0.5625
Epoch 84/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1529 - accuracy: 0.4803 - val_loss: 3.0712 - val_accuracy: 0.5625
Epoch 85/100
3/3 [==============================] - 0s 17ms/step - loss: 3.1446 - accuracy: 0.4885 - val_loss: 3.0680 - val_accuracy: 0.5625
Epoch 86/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1614 - accuracy: 0.4836 - val_loss: 3.0649 - val_accuracy: 0.5691
Epoch 87/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1557 - accuracy: 0.4934 - val_loss: 3.0618 - val_accuracy: 0.5822
Epoch 88/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1484 - accuracy: 0.4918 - val_loss: 3.0588 - val_accuracy: 0.5921
Epoch 89/100
3/3 [==============================] - 0s 18ms/step - loss: 3.1479 - accuracy: 0.5148 - val_loss: 3.0557 - val_accuracy: 0.6020
Epoch 90/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1964 - accuracy: 0.4689 - val_loss: 3.0526 - val_accuracy: 0.6053
Epoch 91/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1421 - accuracy: 0.4951 - val_loss: 3.0495 - val_accuracy: 0.6053
Epoch 92/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1121 - accuracy: 0.5311 - val_loss: 3.0465 - val_accuracy: 0.6086
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1050 - accuracy: 0.5016 - val_loss: 3.0435 - val_accuracy: 0.6086
Epoch 94/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1522 - accuracy: 0.5049 - val_loss: 3.0405 - val_accuracy: 0.6086
Epoch 95/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1162 - accuracy: 0.5164 - val_loss: 3.0375 - val_accuracy: 0.6086
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1338 - accuracy: 0.4918 - val_loss: 3.0345 - val_accuracy: 0.6151
Epoch 97/100
3/3 [==============================] - 0s 16ms/step - loss: 3.1441 - accuracy: 0.4885 - val_loss: 3.0315 - val_accuracy: 0.6184
Epoch 98/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1635 - accuracy: 0.4869 - val_loss: 3.0285 - val_accuracy: 0.6184
Epoch 99/100
3/3 [==============================] - 0s 18ms/step - loss: 3.1180 - accuracy: 0.5000 - val_loss: 3.0254 - val_accuracy: 0.6217
Epoch 100/100
3/3 [==============================] - 0s 26ms/step - loss: 3.1168 - accuracy: 0.5131 - val_loss: 3.0224 - val_accuracy: 0.6217
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 4
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': False, 'initializers': 'he_uniform'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 57ms/step - loss: 1.5015 - accuracy: 0.6305 - val_loss: 1.4062 - val_accuracy: 0.6689
Epoch 2/100
5/5 [==============================] - 0s 13ms/step - loss: 1.4369 - accuracy: 0.6535 - val_loss: 1.3668 - val_accuracy: 0.6984
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 1.3523 - accuracy: 0.7077 - val_loss: 1.3304 - val_accuracy: 0.7148
Epoch 4/100
5/5 [==============================] - 0s 9ms/step - loss: 1.3476 - accuracy: 0.7225 - val_loss: 1.2955 - val_accuracy: 0.7443
Epoch 5/100
5/5 [==============================] - 0s 12ms/step - loss: 1.2861 - accuracy: 0.7241 - val_loss: 1.2619 - val_accuracy: 0.7541
Epoch 6/100
5/5 [==============================] - 0s 11ms/step - loss: 1.2718 - accuracy: 0.7504 - val_loss: 1.2306 - val_accuracy: 0.7836
Epoch 7/100
5/5 [==============================] - 0s 10ms/step - loss: 1.2665 - accuracy: 0.7455 - val_loss: 1.2013 - val_accuracy: 0.8000
Epoch 8/100
5/5 [==============================] - 0s 10ms/step - loss: 1.2063 - accuracy: 0.7701 - val_loss: 1.1742 - val_accuracy: 0.8131
Epoch 9/100
5/5 [==============================] - 0s 12ms/step - loss: 1.1986 - accuracy: 0.7816 - val_loss: 1.1487 - val_accuracy: 0.8164
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 1.1611 - accuracy: 0.7931 - val_loss: 1.1247 - val_accuracy: 0.8197
Epoch 11/100
5/5 [==============================] - 0s 11ms/step - loss: 1.1349 - accuracy: 0.7931 - val_loss: 1.1024 - val_accuracy: 0.8197
Epoch 12/100
5/5 [==============================] - 0s 13ms/step - loss: 1.1120 - accuracy: 0.8112 - val_loss: 1.0810 - val_accuracy: 0.8197
Epoch 13/100
5/5 [==============================] - 0s 13ms/step - loss: 1.1179 - accuracy: 0.8112 - val_loss: 1.0614 - val_accuracy: 0.8197
Epoch 14/100
5/5 [==============================] - 0s 12ms/step - loss: 1.0705 - accuracy: 0.8374 - val_loss: 1.0431 - val_accuracy: 0.8197
Epoch 15/100
5/5 [==============================] - 0s 12ms/step - loss: 1.0489 - accuracy: 0.8161 - val_loss: 1.0258 - val_accuracy: 0.8164
Epoch 16/100
5/5 [==============================] - 0s 11ms/step - loss: 1.0394 - accuracy: 0.8358 - val_loss: 1.0097 - val_accuracy: 0.8164
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 1.0070 - accuracy: 0.8358 - val_loss: 0.9942 - val_accuracy: 0.8197
Epoch 18/100
5/5 [==============================] - 0s 12ms/step - loss: 1.0144 - accuracy: 0.8374 - val_loss: 0.9794 - val_accuracy: 0.8197
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9850 - accuracy: 0.8473 - val_loss: 0.9653 - val_accuracy: 0.8197
Epoch 20/100
5/5 [==============================] - 0s 10ms/step - loss: 0.9704 - accuracy: 0.8473 - val_loss: 0.9520 - val_accuracy: 0.8164
Epoch 21/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9576 - accuracy: 0.8506 - val_loss: 0.9392 - val_accuracy: 0.8164
Epoch 22/100
5/5 [==============================] - 0s 9ms/step - loss: 0.9448 - accuracy: 0.8424 - val_loss: 0.9269 - val_accuracy: 0.8164
Epoch 23/100
5/5 [==============================] - 0s 8ms/step - loss: 0.9281 - accuracy: 0.8391 - val_loss: 0.9149 - val_accuracy: 0.8164
Epoch 24/100
5/5 [==============================] - 0s 10ms/step - loss: 0.9102 - accuracy: 0.8506 - val_loss: 0.9032 - val_accuracy: 0.8164
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9303 - accuracy: 0.8424 - val_loss: 0.8918 - val_accuracy: 0.8164
Epoch 26/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9002 - accuracy: 0.8407 - val_loss: 0.8811 - val_accuracy: 0.8164
Epoch 27/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8798 - accuracy: 0.8555 - val_loss: 0.8704 - val_accuracy: 0.8131
Epoch 28/100
5/5 [==============================] - 0s 9ms/step - loss: 0.8811 - accuracy: 0.8588 - val_loss: 0.8599 - val_accuracy: 0.8131
Epoch 29/100
5/5 [==============================] - 0s 10ms/step - loss: 0.8940 - accuracy: 0.8555 - val_loss: 0.8499 - val_accuracy: 0.8131
Epoch 30/100
5/5 [==============================] - 0s 9ms/step - loss: 0.8498 - accuracy: 0.8637 - val_loss: 0.8403 - val_accuracy: 0.8131
Epoch 31/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8501 - accuracy: 0.8555 - val_loss: 0.8311 - val_accuracy: 0.8131
Epoch 32/100
5/5 [==============================] - 0s 8ms/step - loss: 0.8296 - accuracy: 0.8637 - val_loss: 0.8221 - val_accuracy: 0.8131
Epoch 33/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8299 - accuracy: 0.8588 - val_loss: 0.8136 - val_accuracy: 0.8131
Epoch 34/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7967 - accuracy: 0.8604 - val_loss: 0.8053 - val_accuracy: 0.8098
Epoch 35/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8083 - accuracy: 0.8686 - val_loss: 0.7973 - val_accuracy: 0.8131
Epoch 36/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7877 - accuracy: 0.8670 - val_loss: 0.7895 - val_accuracy: 0.8131
Epoch 37/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7775 - accuracy: 0.8555 - val_loss: 0.7821 - val_accuracy: 0.8131
Epoch 38/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7493 - accuracy: 0.8686 - val_loss: 0.7750 - val_accuracy: 0.8131
Epoch 39/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7631 - accuracy: 0.8686 - val_loss: 0.7680 - val_accuracy: 0.8164
Epoch 40/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7604 - accuracy: 0.8588 - val_loss: 0.7609 - val_accuracy: 0.8164
Epoch 41/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7454 - accuracy: 0.8539 - val_loss: 0.7538 - val_accuracy: 0.8164
Epoch 42/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7543 - accuracy: 0.8539 - val_loss: 0.7468 - val_accuracy: 0.8164
Epoch 43/100
5/5 [==============================] - 0s 8ms/step - loss: 0.7268 - accuracy: 0.8670 - val_loss: 0.7401 - val_accuracy: 0.8164
Epoch 44/100
5/5 [==============================] - 0s 8ms/step - loss: 0.7291 - accuracy: 0.8670 - val_loss: 0.7334 - val_accuracy: 0.8164
Epoch 45/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7118 - accuracy: 0.8588 - val_loss: 0.7265 - val_accuracy: 0.8164
Epoch 46/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7183 - accuracy: 0.8670 - val_loss: 0.7198 - val_accuracy: 0.8164
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6944 - accuracy: 0.8654 - val_loss: 0.7132 - val_accuracy: 0.8164
Epoch 48/100
5/5 [==============================] - 0s 10ms/step - loss: 0.6846 - accuracy: 0.8654 - val_loss: 0.7065 - val_accuracy: 0.8164
Epoch 49/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7009 - accuracy: 0.8670 - val_loss: 0.6998 - val_accuracy: 0.8164
Epoch 50/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6803 - accuracy: 0.8637 - val_loss: 0.6932 - val_accuracy: 0.8164
Epoch 51/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6702 - accuracy: 0.8637 - val_loss: 0.6868 - val_accuracy: 0.8164
Epoch 52/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6813 - accuracy: 0.8604 - val_loss: 0.6805 - val_accuracy: 0.8164
Epoch 53/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6679 - accuracy: 0.8621 - val_loss: 0.6745 - val_accuracy: 0.8164
Epoch 54/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6734 - accuracy: 0.8621 - val_loss: 0.6686 - val_accuracy: 0.8164
Epoch 55/100
5/5 [==============================] - 0s 9ms/step - loss: 0.6259 - accuracy: 0.8686 - val_loss: 0.6626 - val_accuracy: 0.8164
Epoch 56/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6385 - accuracy: 0.8703 - val_loss: 0.6568 - val_accuracy: 0.8164
Epoch 57/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6307 - accuracy: 0.8719 - val_loss: 0.6510 - val_accuracy: 0.8164
Epoch 58/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6268 - accuracy: 0.8703 - val_loss: 0.6453 - val_accuracy: 0.8164
Epoch 59/100
5/5 [==============================] - 0s 10ms/step - loss: 0.6354 - accuracy: 0.8621 - val_loss: 0.6399 - val_accuracy: 0.8164
Epoch 60/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6232 - accuracy: 0.8670 - val_loss: 0.6343 - val_accuracy: 0.8164
Epoch 61/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6105 - accuracy: 0.8686 - val_loss: 0.6289 - val_accuracy: 0.8164
Epoch 62/100
5/5 [==============================] - 0s 10ms/step - loss: 0.6083 - accuracy: 0.8654 - val_loss: 0.6236 - val_accuracy: 0.8164
Epoch 63/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5993 - accuracy: 0.8670 - val_loss: 0.6183 - val_accuracy: 0.8164
Epoch 64/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5853 - accuracy: 0.8703 - val_loss: 0.6131 - val_accuracy: 0.8164
Epoch 65/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5782 - accuracy: 0.8670 - val_loss: 0.6079 - val_accuracy: 0.8164
Epoch 66/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5775 - accuracy: 0.8637 - val_loss: 0.6028 - val_accuracy: 0.8164
Epoch 67/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5759 - accuracy: 0.8637 - val_loss: 0.5978 - val_accuracy: 0.8164
Epoch 68/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5845 - accuracy: 0.8621 - val_loss: 0.5928 - val_accuracy: 0.8164
Epoch 69/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5640 - accuracy: 0.8670 - val_loss: 0.5878 - val_accuracy: 0.8164
Epoch 70/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5485 - accuracy: 0.8654 - val_loss: 0.5828 - val_accuracy: 0.8164
Epoch 71/100
5/5 [==============================] - 0s 10ms/step - loss: 0.5467 - accuracy: 0.8670 - val_loss: 0.5781 - val_accuracy: 0.8164
Epoch 72/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5406 - accuracy: 0.8670 - val_loss: 0.5733 - val_accuracy: 0.8164
Epoch 73/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5394 - accuracy: 0.8686 - val_loss: 0.5683 - val_accuracy: 0.8164
Epoch 74/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5518 - accuracy: 0.8670 - val_loss: 0.5636 - val_accuracy: 0.8164
Epoch 75/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5147 - accuracy: 0.8670 - val_loss: 0.5587 - val_accuracy: 0.8164
Epoch 76/100
5/5 [==============================] - 0s 10ms/step - loss: 0.5265 - accuracy: 0.8637 - val_loss: 0.5539 - val_accuracy: 0.8164
Epoch 77/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5224 - accuracy: 0.8670 - val_loss: 0.5490 - val_accuracy: 0.8164
Epoch 78/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5414 - accuracy: 0.8670 - val_loss: 0.5443 - val_accuracy: 0.8164
Epoch 79/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5278 - accuracy: 0.8654 - val_loss: 0.5399 - val_accuracy: 0.8164
Epoch 80/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5109 - accuracy: 0.8686 - val_loss: 0.5352 - val_accuracy: 0.8164
Epoch 81/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4976 - accuracy: 0.8686 - val_loss: 0.5306 - val_accuracy: 0.8164
Epoch 82/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5008 - accuracy: 0.8670 - val_loss: 0.5262 - val_accuracy: 0.8164
Epoch 83/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4913 - accuracy: 0.8670 - val_loss: 0.5220 - val_accuracy: 0.8164
Epoch 84/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4837 - accuracy: 0.8654 - val_loss: 0.5180 - val_accuracy: 0.8164
Epoch 85/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4883 - accuracy: 0.8670 - val_loss: 0.5141 - val_accuracy: 0.8164
Epoch 86/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4835 - accuracy: 0.8670 - val_loss: 0.5105 - val_accuracy: 0.8164
Epoch 87/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4733 - accuracy: 0.8654 - val_loss: 0.5069 - val_accuracy: 0.8164
Epoch 88/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4680 - accuracy: 0.8654 - val_loss: 0.5036 - val_accuracy: 0.8164
Epoch 89/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4652 - accuracy: 0.8654 - val_loss: 0.5006 - val_accuracy: 0.8164
Epoch 90/100
5/5 [==============================] - 0s 9ms/step - loss: 0.4682 - accuracy: 0.8686 - val_loss: 0.4972 - val_accuracy: 0.8164
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4677 - accuracy: 0.8670 - val_loss: 0.4942 - val_accuracy: 0.8164
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4579 - accuracy: 0.8670 - val_loss: 0.4916 - val_accuracy: 0.8164
Epoch 93/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4547 - accuracy: 0.8670 - val_loss: 0.4888 - val_accuracy: 0.8164
Epoch 94/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4627 - accuracy: 0.8654 - val_loss: 0.4864 - val_accuracy: 0.8164
Epoch 95/100
5/5 [==============================] - 0s 16ms/step - loss: 0.4571 - accuracy: 0.8670 - val_loss: 0.4839 - val_accuracy: 0.8164
Epoch 96/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4509 - accuracy: 0.8670 - val_loss: 0.4814 - val_accuracy: 0.8164
Epoch 97/100
5/5 [==============================] - 0s 13ms/step - loss: 0.4351 - accuracy: 0.8654 - val_loss: 0.4790 - val_accuracy: 0.8164
Epoch 98/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4379 - accuracy: 0.8670 - val_loss: 0.4767 - val_accuracy: 0.8164
Epoch 99/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4390 - accuracy: 0.8670 - val_loss: 0.4753 - val_accuracy: 0.8164
Epoch 100/100
5/5 [==============================] - 0s 8ms/step - loss: 0.4266 - accuracy: 0.8670 - val_loss: 0.4734 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': False, 'initializers': 'he_uniform'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 59ms/step - loss: 2.1799 - accuracy: 0.1675 - val_loss: 2.0308 - val_accuracy: 0.1508
Epoch 2/100
5/5 [==============================] - 0s 10ms/step - loss: 2.1138 - accuracy: 0.1839 - val_loss: 1.9647 - val_accuracy: 0.1607
Epoch 3/100
5/5 [==============================] - 0s 9ms/step - loss: 1.9940 - accuracy: 0.1921 - val_loss: 1.9015 - val_accuracy: 0.1934
Epoch 4/100
5/5 [==============================] - 0s 11ms/step - loss: 1.9606 - accuracy: 0.2151 - val_loss: 1.8415 - val_accuracy: 0.2328
Epoch 5/100
5/5 [==============================] - 0s 9ms/step - loss: 1.8960 - accuracy: 0.2578 - val_loss: 1.7839 - val_accuracy: 0.2590
Epoch 6/100
5/5 [==============================] - 0s 9ms/step - loss: 1.8180 - accuracy: 0.2890 - val_loss: 1.7294 - val_accuracy: 0.2787
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 1.7679 - accuracy: 0.3136 - val_loss: 1.6779 - val_accuracy: 0.2984
Epoch 8/100
5/5 [==============================] - 0s 10ms/step - loss: 1.7524 - accuracy: 0.3465 - val_loss: 1.6289 - val_accuracy: 0.3443
Epoch 9/100
5/5 [==============================] - 0s 11ms/step - loss: 1.6939 - accuracy: 0.3744 - val_loss: 1.5826 - val_accuracy: 0.3836
Epoch 10/100
5/5 [==============================] - 0s 9ms/step - loss: 1.6605 - accuracy: 0.3990 - val_loss: 1.5383 - val_accuracy: 0.4066
Epoch 11/100
5/5 [==============================] - 0s 8ms/step - loss: 1.5822 - accuracy: 0.4138 - val_loss: 1.4966 - val_accuracy: 0.4590
Epoch 12/100
5/5 [==============================] - 0s 12ms/step - loss: 1.5351 - accuracy: 0.4450 - val_loss: 1.4568 - val_accuracy: 0.4984
Epoch 13/100
5/5 [==============================] - 0s 12ms/step - loss: 1.5281 - accuracy: 0.4614 - val_loss: 1.4189 - val_accuracy: 0.5377
Epoch 14/100
5/5 [==============================] - 0s 13ms/step - loss: 1.4613 - accuracy: 0.4762 - val_loss: 1.3830 - val_accuracy: 0.5869
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 1.4420 - accuracy: 0.5665 - val_loss: 1.3491 - val_accuracy: 0.6197
Epoch 16/100
5/5 [==============================] - 0s 8ms/step - loss: 1.4108 - accuracy: 0.5304 - val_loss: 1.3171 - val_accuracy: 0.6754
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 1.3545 - accuracy: 0.5977 - val_loss: 1.2868 - val_accuracy: 0.7016
Epoch 18/100
5/5 [==============================] - 0s 12ms/step - loss: 1.3771 - accuracy: 0.5829 - val_loss: 1.2582 - val_accuracy: 0.7311
Epoch 19/100
5/5 [==============================] - 0s 15ms/step - loss: 1.3164 - accuracy: 0.6256 - val_loss: 1.2306 - val_accuracy: 0.7574
Epoch 20/100
5/5 [==============================] - 0s 10ms/step - loss: 1.2909 - accuracy: 0.6305 - val_loss: 1.2044 - val_accuracy: 0.7672
Epoch 21/100
5/5 [==============================] - 0s 12ms/step - loss: 1.2621 - accuracy: 0.6601 - val_loss: 1.1795 - val_accuracy: 0.7803
Epoch 22/100
5/5 [==============================] - 0s 12ms/step - loss: 1.2422 - accuracy: 0.6667 - val_loss: 1.1555 - val_accuracy: 0.7934
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 1.2096 - accuracy: 0.6979 - val_loss: 1.1329 - val_accuracy: 0.8066
Epoch 24/100
5/5 [==============================] - 0s 15ms/step - loss: 1.1918 - accuracy: 0.7389 - val_loss: 1.1112 - val_accuracy: 0.8164
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 1.2086 - accuracy: 0.7126 - val_loss: 1.0903 - val_accuracy: 0.8328
Epoch 26/100
5/5 [==============================] - 0s 12ms/step - loss: 1.1823 - accuracy: 0.7110 - val_loss: 1.0702 - val_accuracy: 0.8361
Epoch 27/100
5/5 [==============================] - 0s 10ms/step - loss: 1.1560 - accuracy: 0.7340 - val_loss: 1.0510 - val_accuracy: 0.8459
Epoch 28/100
5/5 [==============================] - 0s 13ms/step - loss: 1.1134 - accuracy: 0.7570 - val_loss: 1.0323 - val_accuracy: 0.8557
Epoch 29/100
5/5 [==============================] - 0s 13ms/step - loss: 1.1114 - accuracy: 0.7586 - val_loss: 1.0144 - val_accuracy: 0.8656
Epoch 30/100
5/5 [==============================] - 0s 9ms/step - loss: 1.1029 - accuracy: 0.7488 - val_loss: 0.9973 - val_accuracy: 0.8656
Epoch 31/100
5/5 [==============================] - 0s 9ms/step - loss: 1.0780 - accuracy: 0.7865 - val_loss: 0.9810 - val_accuracy: 0.8754
Epoch 32/100
5/5 [==============================] - 0s 9ms/step - loss: 1.0621 - accuracy: 0.7865 - val_loss: 0.9656 - val_accuracy: 0.8754
Epoch 33/100
5/5 [==============================] - 0s 12ms/step - loss: 1.0545 - accuracy: 0.7898 - val_loss: 0.9505 - val_accuracy: 0.8754
Epoch 34/100
5/5 [==============================] - 0s 11ms/step - loss: 1.0356 - accuracy: 0.7783 - val_loss: 0.9356 - val_accuracy: 0.8754
Epoch 35/100
5/5 [==============================] - 0s 13ms/step - loss: 1.0291 - accuracy: 0.7964 - val_loss: 0.9213 - val_accuracy: 0.8754
Epoch 36/100
5/5 [==============================] - 0s 9ms/step - loss: 0.9940 - accuracy: 0.8095 - val_loss: 0.9073 - val_accuracy: 0.8754
Epoch 37/100
5/5 [==============================] - 0s 9ms/step - loss: 1.0047 - accuracy: 0.8112 - val_loss: 0.8939 - val_accuracy: 0.8754
Epoch 38/100
5/5 [==============================] - 0s 8ms/step - loss: 0.9679 - accuracy: 0.8177 - val_loss: 0.8812 - val_accuracy: 0.8754
Epoch 39/100
5/5 [==============================] - 0s 9ms/step - loss: 0.9734 - accuracy: 0.8177 - val_loss: 0.8687 - val_accuracy: 0.8754
Epoch 40/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9568 - accuracy: 0.8144 - val_loss: 0.8569 - val_accuracy: 0.8754
Epoch 41/100
5/5 [==============================] - 0s 14ms/step - loss: 0.9394 - accuracy: 0.8309 - val_loss: 0.8453 - val_accuracy: 0.8754
Epoch 42/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9410 - accuracy: 0.8374 - val_loss: 0.8342 - val_accuracy: 0.8754
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9052 - accuracy: 0.8325 - val_loss: 0.8236 - val_accuracy: 0.8754
Epoch 44/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8905 - accuracy: 0.8374 - val_loss: 0.8129 - val_accuracy: 0.8754
Epoch 45/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8914 - accuracy: 0.8325 - val_loss: 0.8023 - val_accuracy: 0.8754
Epoch 46/100
5/5 [==============================] - 0s 14ms/step - loss: 0.8910 - accuracy: 0.8161 - val_loss: 0.7921 - val_accuracy: 0.8754
Epoch 47/100
5/5 [==============================] - 0s 9ms/step - loss: 0.8623 - accuracy: 0.8292 - val_loss: 0.7821 - val_accuracy: 0.8754
Epoch 48/100
5/5 [==============================] - 0s 8ms/step - loss: 0.8639 - accuracy: 0.8325 - val_loss: 0.7724 - val_accuracy: 0.8754
Epoch 49/100
5/5 [==============================] - 0s 9ms/step - loss: 0.8737 - accuracy: 0.8243 - val_loss: 0.7632 - val_accuracy: 0.8754
Epoch 50/100
5/5 [==============================] - 0s 10ms/step - loss: 0.8481 - accuracy: 0.8325 - val_loss: 0.7541 - val_accuracy: 0.8754
Epoch 51/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8523 - accuracy: 0.8391 - val_loss: 0.7451 - val_accuracy: 0.8754
Epoch 52/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8330 - accuracy: 0.8358 - val_loss: 0.7365 - val_accuracy: 0.8754
Epoch 53/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8233 - accuracy: 0.8358 - val_loss: 0.7279 - val_accuracy: 0.8754
Epoch 54/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8237 - accuracy: 0.8342 - val_loss: 0.7196 - val_accuracy: 0.8754
Epoch 55/100
5/5 [==============================] - 0s 13ms/step - loss: 0.8119 - accuracy: 0.8309 - val_loss: 0.7113 - val_accuracy: 0.8787
Epoch 56/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7883 - accuracy: 0.8440 - val_loss: 0.7033 - val_accuracy: 0.8787
Epoch 57/100
5/5 [==============================] - 0s 28ms/step - loss: 0.7919 - accuracy: 0.8374 - val_loss: 0.6954 - val_accuracy: 0.8787
Epoch 58/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7781 - accuracy: 0.8342 - val_loss: 0.6876 - val_accuracy: 0.8787
Epoch 59/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7703 - accuracy: 0.8276 - val_loss: 0.6801 - val_accuracy: 0.8787
Epoch 60/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7813 - accuracy: 0.8358 - val_loss: 0.6727 - val_accuracy: 0.8787
Epoch 61/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7564 - accuracy: 0.8456 - val_loss: 0.6654 - val_accuracy: 0.8787
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7560 - accuracy: 0.8473 - val_loss: 0.6584 - val_accuracy: 0.8787
Epoch 63/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7517 - accuracy: 0.8391 - val_loss: 0.6514 - val_accuracy: 0.8787
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7334 - accuracy: 0.8292 - val_loss: 0.6447 - val_accuracy: 0.8787
Epoch 65/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7410 - accuracy: 0.8342 - val_loss: 0.6380 - val_accuracy: 0.8787
Epoch 66/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7207 - accuracy: 0.8407 - val_loss: 0.6316 - val_accuracy: 0.8787
Epoch 67/100
5/5 [==============================] - 0s 9ms/step - loss: 0.7292 - accuracy: 0.8342 - val_loss: 0.6252 - val_accuracy: 0.8787
Epoch 68/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7043 - accuracy: 0.8325 - val_loss: 0.6189 - val_accuracy: 0.8787
Epoch 69/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6924 - accuracy: 0.8276 - val_loss: 0.6127 - val_accuracy: 0.8787
Epoch 70/100
5/5 [==============================] - 0s 16ms/step - loss: 0.7063 - accuracy: 0.8407 - val_loss: 0.6067 - val_accuracy: 0.8787
Epoch 71/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6891 - accuracy: 0.8391 - val_loss: 0.6006 - val_accuracy: 0.8787
Epoch 72/100
5/5 [==============================] - 0s 10ms/step - loss: 0.6884 - accuracy: 0.8325 - val_loss: 0.5947 - val_accuracy: 0.8787
Epoch 73/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6775 - accuracy: 0.8440 - val_loss: 0.5888 - val_accuracy: 0.8787
Epoch 74/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6690 - accuracy: 0.8555 - val_loss: 0.5832 - val_accuracy: 0.8787
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6778 - accuracy: 0.8424 - val_loss: 0.5774 - val_accuracy: 0.8754
Epoch 76/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6669 - accuracy: 0.8489 - val_loss: 0.5720 - val_accuracy: 0.8754
Epoch 77/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6521 - accuracy: 0.8424 - val_loss: 0.5666 - val_accuracy: 0.8754
Epoch 78/100
5/5 [==============================] - 0s 9ms/step - loss: 0.6475 - accuracy: 0.8342 - val_loss: 0.5613 - val_accuracy: 0.8754
Epoch 79/100
5/5 [==============================] - 0s 10ms/step - loss: 0.6521 - accuracy: 0.8489 - val_loss: 0.5559 - val_accuracy: 0.8754
Epoch 80/100
5/5 [==============================] - 0s 10ms/step - loss: 0.6419 - accuracy: 0.8391 - val_loss: 0.5507 - val_accuracy: 0.8754
Epoch 81/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6543 - accuracy: 0.8424 - val_loss: 0.5455 - val_accuracy: 0.8754
Epoch 82/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6328 - accuracy: 0.8440 - val_loss: 0.5405 - val_accuracy: 0.8754
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6488 - accuracy: 0.8473 - val_loss: 0.5355 - val_accuracy: 0.8754
Epoch 84/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6271 - accuracy: 0.8342 - val_loss: 0.5307 - val_accuracy: 0.8754
Epoch 85/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6195 - accuracy: 0.8424 - val_loss: 0.5260 - val_accuracy: 0.8754
Epoch 86/100
5/5 [==============================] - 0s 9ms/step - loss: 0.6339 - accuracy: 0.8358 - val_loss: 0.5212 - val_accuracy: 0.8754
Epoch 87/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6138 - accuracy: 0.8424 - val_loss: 0.5164 - val_accuracy: 0.8754
Epoch 88/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6026 - accuracy: 0.8440 - val_loss: 0.5116 - val_accuracy: 0.8754
Epoch 89/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6122 - accuracy: 0.8407 - val_loss: 0.5068 - val_accuracy: 0.8754
Epoch 90/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5843 - accuracy: 0.8489 - val_loss: 0.5021 - val_accuracy: 0.8754
Epoch 91/100
5/5 [==============================] - 0s 10ms/step - loss: 0.5920 - accuracy: 0.8407 - val_loss: 0.4974 - val_accuracy: 0.8754
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5817 - accuracy: 0.8407 - val_loss: 0.4930 - val_accuracy: 0.8754
Epoch 93/100
5/5 [==============================] - 0s 8ms/step - loss: 0.6018 - accuracy: 0.8407 - val_loss: 0.4885 - val_accuracy: 0.8754
Epoch 94/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5740 - accuracy: 0.8407 - val_loss: 0.4841 - val_accuracy: 0.8754
Epoch 95/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5763 - accuracy: 0.8440 - val_loss: 0.4798 - val_accuracy: 0.8754
Epoch 96/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5868 - accuracy: 0.8407 - val_loss: 0.4755 - val_accuracy: 0.8754
Epoch 97/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5630 - accuracy: 0.8440 - val_loss: 0.4713 - val_accuracy: 0.8754
Epoch 98/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5683 - accuracy: 0.8440 - val_loss: 0.4674 - val_accuracy: 0.8754
Epoch 99/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5675 - accuracy: 0.8440 - val_loss: 0.4635 - val_accuracy: 0.8754
Epoch 100/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5449 - accuracy: 0.8440 - val_loss: 0.4596 - val_accuracy: 0.8754
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.001, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'Adam', 'l1': 0.01, 'l2': 0.01, 'dropout_rate': 0.4, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': False, 'initializers': 'he_uniform'}
Batch size: 128
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
5/5 [==============================] - 1s 61ms/step - loss: 1.5234 - accuracy: 0.5984 - val_loss: 1.4057 - val_accuracy: 0.6513
Epoch 2/100
5/5 [==============================] - 0s 14ms/step - loss: 1.4478 - accuracy: 0.6033 - val_loss: 1.3680 - val_accuracy: 0.6941
Epoch 3/100
5/5 [==============================] - 0s 12ms/step - loss: 1.4517 - accuracy: 0.6295 - val_loss: 1.3321 - val_accuracy: 0.7138
Epoch 4/100
5/5 [==============================] - 0s 12ms/step - loss: 1.3829 - accuracy: 0.6213 - val_loss: 1.2981 - val_accuracy: 0.7204
Epoch 5/100
5/5 [==============================] - 0s 13ms/step - loss: 1.3314 - accuracy: 0.6951 - val_loss: 1.2660 - val_accuracy: 0.7434
Epoch 6/100
5/5 [==============================] - 0s 11ms/step - loss: 1.3129 - accuracy: 0.6885 - val_loss: 1.2358 - val_accuracy: 0.7664
Epoch 7/100
5/5 [==============================] - 0s 15ms/step - loss: 1.3190 - accuracy: 0.7082 - val_loss: 1.2078 - val_accuracy: 0.7697
Epoch 8/100
5/5 [==============================] - 0s 13ms/step - loss: 1.2717 - accuracy: 0.7344 - val_loss: 1.1810 - val_accuracy: 0.7796
Epoch 9/100
5/5 [==============================] - 0s 14ms/step - loss: 1.2454 - accuracy: 0.7393 - val_loss: 1.1564 - val_accuracy: 0.7928
Epoch 10/100
5/5 [==============================] - 0s 10ms/step - loss: 1.1871 - accuracy: 0.7377 - val_loss: 1.1331 - val_accuracy: 0.7993
Epoch 11/100
5/5 [==============================] - 0s 14ms/step - loss: 1.1465 - accuracy: 0.7787 - val_loss: 1.1112 - val_accuracy: 0.8059
Epoch 12/100
5/5 [==============================] - 0s 12ms/step - loss: 1.1623 - accuracy: 0.7721 - val_loss: 1.0913 - val_accuracy: 0.8092
Epoch 13/100
5/5 [==============================] - 0s 12ms/step - loss: 1.1300 - accuracy: 0.7885 - val_loss: 1.0726 - val_accuracy: 0.8092
Epoch 14/100
5/5 [==============================] - 0s 11ms/step - loss: 1.0946 - accuracy: 0.8000 - val_loss: 1.0549 - val_accuracy: 0.8158
Epoch 15/100
5/5 [==============================] - 0s 10ms/step - loss: 1.1156 - accuracy: 0.7918 - val_loss: 1.0380 - val_accuracy: 0.8191
Epoch 16/100
5/5 [==============================] - 0s 12ms/step - loss: 1.1039 - accuracy: 0.8016 - val_loss: 1.0220 - val_accuracy: 0.8191
Epoch 17/100
5/5 [==============================] - 0s 13ms/step - loss: 1.0358 - accuracy: 0.8361 - val_loss: 1.0066 - val_accuracy: 0.8257
Epoch 18/100
5/5 [==============================] - 0s 11ms/step - loss: 1.0325 - accuracy: 0.8279 - val_loss: 0.9918 - val_accuracy: 0.8289
Epoch 19/100
5/5 [==============================] - 0s 11ms/step - loss: 1.0428 - accuracy: 0.8082 - val_loss: 0.9777 - val_accuracy: 0.8289
Epoch 20/100
5/5 [==============================] - 0s 12ms/step - loss: 1.0332 - accuracy: 0.8115 - val_loss: 0.9640 - val_accuracy: 0.8388
Epoch 21/100
5/5 [==============================] - 0s 10ms/step - loss: 0.9942 - accuracy: 0.8213 - val_loss: 0.9509 - val_accuracy: 0.8388
Epoch 22/100
5/5 [==============================] - 0s 13ms/step - loss: 0.9948 - accuracy: 0.8361 - val_loss: 0.9383 - val_accuracy: 0.8421
Epoch 23/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9919 - accuracy: 0.8213 - val_loss: 0.9261 - val_accuracy: 0.8454
Epoch 24/100
5/5 [==============================] - 0s 15ms/step - loss: 0.9615 - accuracy: 0.8344 - val_loss: 0.9141 - val_accuracy: 0.8487
Epoch 25/100
5/5 [==============================] - 0s 10ms/step - loss: 0.9495 - accuracy: 0.8377 - val_loss: 0.9026 - val_accuracy: 0.8520
Epoch 26/100
5/5 [==============================] - 0s 9ms/step - loss: 0.9374 - accuracy: 0.8295 - val_loss: 0.8914 - val_accuracy: 0.8520
Epoch 27/100
5/5 [==============================] - 0s 12ms/step - loss: 0.9337 - accuracy: 0.8295 - val_loss: 0.8805 - val_accuracy: 0.8553
Epoch 28/100
5/5 [==============================] - 0s 13ms/step - loss: 0.9105 - accuracy: 0.8279 - val_loss: 0.8703 - val_accuracy: 0.8586
Epoch 29/100
5/5 [==============================] - 0s 13ms/step - loss: 0.9028 - accuracy: 0.8262 - val_loss: 0.8602 - val_accuracy: 0.8586
Epoch 30/100
5/5 [==============================] - 0s 14ms/step - loss: 0.8822 - accuracy: 0.8492 - val_loss: 0.8506 - val_accuracy: 0.8586
Epoch 31/100
5/5 [==============================] - 0s 10ms/step - loss: 0.8594 - accuracy: 0.8590 - val_loss: 0.8412 - val_accuracy: 0.8586
Epoch 32/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8426 - accuracy: 0.8590 - val_loss: 0.8320 - val_accuracy: 0.8586
Epoch 33/100
5/5 [==============================] - 0s 8ms/step - loss: 0.8642 - accuracy: 0.8393 - val_loss: 0.8231 - val_accuracy: 0.8586
Epoch 34/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8615 - accuracy: 0.8443 - val_loss: 0.8143 - val_accuracy: 0.8553
Epoch 35/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8558 - accuracy: 0.8393 - val_loss: 0.8056 - val_accuracy: 0.8553
Epoch 36/100
5/5 [==============================] - 0s 12ms/step - loss: 0.8106 - accuracy: 0.8508 - val_loss: 0.7971 - val_accuracy: 0.8586
Epoch 37/100
5/5 [==============================] - 0s 10ms/step - loss: 0.8047 - accuracy: 0.8623 - val_loss: 0.7887 - val_accuracy: 0.8586
Epoch 38/100
5/5 [==============================] - 0s 11ms/step - loss: 0.8034 - accuracy: 0.8443 - val_loss: 0.7806 - val_accuracy: 0.8586
Epoch 39/100
5/5 [==============================] - 0s 9ms/step - loss: 0.7927 - accuracy: 0.8525 - val_loss: 0.7726 - val_accuracy: 0.8586
Epoch 40/100
5/5 [==============================] - 0s 10ms/step - loss: 0.7747 - accuracy: 0.8689 - val_loss: 0.7648 - val_accuracy: 0.8586
Epoch 41/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7876 - accuracy: 0.8443 - val_loss: 0.7569 - val_accuracy: 0.8586
Epoch 42/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7582 - accuracy: 0.8607 - val_loss: 0.7491 - val_accuracy: 0.8586
Epoch 43/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7755 - accuracy: 0.8541 - val_loss: 0.7415 - val_accuracy: 0.8618
Epoch 44/100
5/5 [==============================] - 0s 13ms/step - loss: 0.7756 - accuracy: 0.8426 - val_loss: 0.7338 - val_accuracy: 0.8618
Epoch 45/100
5/5 [==============================] - 0s 9ms/step - loss: 0.7525 - accuracy: 0.8508 - val_loss: 0.7264 - val_accuracy: 0.8618
Epoch 46/100
5/5 [==============================] - 0s 9ms/step - loss: 0.7482 - accuracy: 0.8525 - val_loss: 0.7191 - val_accuracy: 0.8553
Epoch 47/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7273 - accuracy: 0.8574 - val_loss: 0.7121 - val_accuracy: 0.8553
Epoch 48/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6921 - accuracy: 0.8590 - val_loss: 0.7053 - val_accuracy: 0.8553
Epoch 49/100
5/5 [==============================] - 0s 10ms/step - loss: 0.7241 - accuracy: 0.8623 - val_loss: 0.6985 - val_accuracy: 0.8553
Epoch 50/100
5/5 [==============================] - 0s 10ms/step - loss: 0.7059 - accuracy: 0.8672 - val_loss: 0.6917 - val_accuracy: 0.8553
Epoch 51/100
5/5 [==============================] - 0s 12ms/step - loss: 0.7035 - accuracy: 0.8508 - val_loss: 0.6850 - val_accuracy: 0.8553
Epoch 52/100
5/5 [==============================] - 0s 11ms/step - loss: 0.7184 - accuracy: 0.8574 - val_loss: 0.6784 - val_accuracy: 0.8553
Epoch 53/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6698 - accuracy: 0.8557 - val_loss: 0.6718 - val_accuracy: 0.8553
Epoch 54/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6738 - accuracy: 0.8672 - val_loss: 0.6652 - val_accuracy: 0.8586
Epoch 55/100
5/5 [==============================] - 0s 10ms/step - loss: 0.6680 - accuracy: 0.8590 - val_loss: 0.6586 - val_accuracy: 0.8586
Epoch 56/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6661 - accuracy: 0.8377 - val_loss: 0.6521 - val_accuracy: 0.8586
Epoch 57/100
5/5 [==============================] - 0s 13ms/step - loss: 0.6444 - accuracy: 0.8525 - val_loss: 0.6455 - val_accuracy: 0.8586
Epoch 58/100
5/5 [==============================] - 0s 10ms/step - loss: 0.6537 - accuracy: 0.8525 - val_loss: 0.6391 - val_accuracy: 0.8586
Epoch 59/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6311 - accuracy: 0.8459 - val_loss: 0.6331 - val_accuracy: 0.8586
Epoch 60/100
5/5 [==============================] - 0s 9ms/step - loss: 0.6239 - accuracy: 0.8623 - val_loss: 0.6273 - val_accuracy: 0.8586
Epoch 61/100
5/5 [==============================] - 0s 9ms/step - loss: 0.6153 - accuracy: 0.8656 - val_loss: 0.6217 - val_accuracy: 0.8586
Epoch 62/100
5/5 [==============================] - 0s 12ms/step - loss: 0.6185 - accuracy: 0.8590 - val_loss: 0.6160 - val_accuracy: 0.8586
Epoch 63/100
5/5 [==============================] - 0s 11ms/step - loss: 0.6022 - accuracy: 0.8574 - val_loss: 0.6103 - val_accuracy: 0.8618
Epoch 64/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5904 - accuracy: 0.8738 - val_loss: 0.6047 - val_accuracy: 0.8618
Epoch 65/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5903 - accuracy: 0.8672 - val_loss: 0.5993 - val_accuracy: 0.8618
Epoch 66/100
5/5 [==============================] - 0s 13ms/step - loss: 0.5908 - accuracy: 0.8639 - val_loss: 0.5938 - val_accuracy: 0.8618
Epoch 67/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5781 - accuracy: 0.8459 - val_loss: 0.5884 - val_accuracy: 0.8618
Epoch 68/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5944 - accuracy: 0.8590 - val_loss: 0.5830 - val_accuracy: 0.8618
Epoch 69/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5664 - accuracy: 0.8623 - val_loss: 0.5778 - val_accuracy: 0.8618
Epoch 70/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5799 - accuracy: 0.8590 - val_loss: 0.5725 - val_accuracy: 0.8618
Epoch 71/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5687 - accuracy: 0.8541 - val_loss: 0.5671 - val_accuracy: 0.8618
Epoch 72/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5535 - accuracy: 0.8574 - val_loss: 0.5621 - val_accuracy: 0.8618
Epoch 73/100
5/5 [==============================] - 0s 8ms/step - loss: 0.5265 - accuracy: 0.8541 - val_loss: 0.5571 - val_accuracy: 0.8618
Epoch 74/100
5/5 [==============================] - 0s 8ms/step - loss: 0.5231 - accuracy: 0.8557 - val_loss: 0.5523 - val_accuracy: 0.8618
Epoch 75/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5484 - accuracy: 0.8623 - val_loss: 0.5475 - val_accuracy: 0.8618
Epoch 76/100
5/5 [==============================] - 0s 14ms/step - loss: 0.5390 - accuracy: 0.8541 - val_loss: 0.5429 - val_accuracy: 0.8618
Epoch 77/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5255 - accuracy: 0.8525 - val_loss: 0.5384 - val_accuracy: 0.8618
Epoch 78/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5289 - accuracy: 0.8590 - val_loss: 0.5338 - val_accuracy: 0.8618
Epoch 79/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5238 - accuracy: 0.8590 - val_loss: 0.5293 - val_accuracy: 0.8618
Epoch 80/100
5/5 [==============================] - 0s 15ms/step - loss: 0.5205 - accuracy: 0.8492 - val_loss: 0.5250 - val_accuracy: 0.8618
Epoch 81/100
5/5 [==============================] - 0s 9ms/step - loss: 0.5014 - accuracy: 0.8656 - val_loss: 0.5212 - val_accuracy: 0.8618
Epoch 82/100
5/5 [==============================] - 0s 16ms/step - loss: 0.5063 - accuracy: 0.8525 - val_loss: 0.5176 - val_accuracy: 0.8618
Epoch 83/100
5/5 [==============================] - 0s 12ms/step - loss: 0.5097 - accuracy: 0.8689 - val_loss: 0.5138 - val_accuracy: 0.8618
Epoch 84/100
5/5 [==============================] - 0s 11ms/step - loss: 0.5032 - accuracy: 0.8607 - val_loss: 0.5102 - val_accuracy: 0.8618
Epoch 85/100
5/5 [==============================] - 0s 14ms/step - loss: 0.4817 - accuracy: 0.8656 - val_loss: 0.5068 - val_accuracy: 0.8618
Epoch 86/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4895 - accuracy: 0.8590 - val_loss: 0.5035 - val_accuracy: 0.8651
Epoch 87/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4918 - accuracy: 0.8557 - val_loss: 0.5002 - val_accuracy: 0.8651
Epoch 88/100
5/5 [==============================] - 0s 10ms/step - loss: 0.4818 - accuracy: 0.8541 - val_loss: 0.4969 - val_accuracy: 0.8651
Epoch 89/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4645 - accuracy: 0.8754 - val_loss: 0.4936 - val_accuracy: 0.8651
Epoch 90/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4643 - accuracy: 0.8541 - val_loss: 0.4905 - val_accuracy: 0.8651
Epoch 91/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4763 - accuracy: 0.8525 - val_loss: 0.4874 - val_accuracy: 0.8651
Epoch 92/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4744 - accuracy: 0.8705 - val_loss: 0.4843 - val_accuracy: 0.8651
Epoch 93/100
5/5 [==============================] - 0s 9ms/step - loss: 0.4493 - accuracy: 0.8705 - val_loss: 0.4817 - val_accuracy: 0.8651
Epoch 94/100
5/5 [==============================] - 0s 12ms/step - loss: 0.4572 - accuracy: 0.8557 - val_loss: 0.4793 - val_accuracy: 0.8651
Epoch 95/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4547 - accuracy: 0.8705 - val_loss: 0.4769 - val_accuracy: 0.8651
Epoch 96/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4449 - accuracy: 0.8574 - val_loss: 0.4744 - val_accuracy: 0.8651
Epoch 97/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4515 - accuracy: 0.8705 - val_loss: 0.4721 - val_accuracy: 0.8618
Epoch 98/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4465 - accuracy: 0.8557 - val_loss: 0.4699 - val_accuracy: 0.8651
Epoch 99/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4314 - accuracy: 0.8623 - val_loss: 0.4676 - val_accuracy: 0.8651
Epoch 100/100
5/5 [==============================] - 0s 11ms/step - loss: 0.4399 - accuracy: 0.8672 - val_loss: 0.4653 - val_accuracy: 0.8586
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 3ms/step
Experiment number: 5
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 254ms/step - loss: 2.0636 - accuracy: 0.2923 - val_loss: 1.4263 - val_accuracy: 0.3279
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0939 - accuracy: 0.3071 - val_loss: 1.4296 - val_accuracy: 0.3279
Epoch 3/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1102 - accuracy: 0.2627 - val_loss: 1.4344 - val_accuracy: 0.3279
Epoch 4/100
2/2 [==============================] - 0s 30ms/step - loss: 2.0886 - accuracy: 0.2677 - val_loss: 1.4386 - val_accuracy: 0.3279
Epoch 5/100
2/2 [==============================] - 0s 36ms/step - loss: 2.0787 - accuracy: 0.2660 - val_loss: 1.4422 - val_accuracy: 0.3246
Epoch 6/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1174 - accuracy: 0.2759 - val_loss: 1.4457 - val_accuracy: 0.3213
Epoch 7/100
2/2 [==============================] - 0s 47ms/step - loss: 2.0030 - accuracy: 0.3333 - val_loss: 1.4497 - val_accuracy: 0.3180
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0832 - accuracy: 0.2611 - val_loss: 1.4534 - val_accuracy: 0.3180
Epoch 9/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1485 - accuracy: 0.2759 - val_loss: 1.4576 - val_accuracy: 0.3148
Epoch 10/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0717 - accuracy: 0.3038 - val_loss: 1.4614 - val_accuracy: 0.3180
Epoch 11/100
1/2 [==============>...............] - ETA: 0s - loss: 2.0665 - accuracy: 0.2930Restoring model weights from the end of the best epoch: 1.
2/2 [==============================] - 0s 36ms/step - loss: 2.0665 - accuracy: 0.2841 - val_loss: 1.4653 - val_accuracy: 0.3180
Epoch 11: early stopping
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 242ms/step - loss: 2.2476 - accuracy: 0.3859 - val_loss: 2.1307 - val_accuracy: 0.0721
Epoch 2/100
2/2 [==============================] - 0s 53ms/step - loss: 2.1248 - accuracy: 0.4269 - val_loss: 2.1219 - val_accuracy: 0.0721
Epoch 3/100
2/2 [==============================] - 0s 37ms/step - loss: 2.2018 - accuracy: 0.4039 - val_loss: 2.1123 - val_accuracy: 0.0721
Epoch 4/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0901 - accuracy: 0.3875 - val_loss: 2.1034 - val_accuracy: 0.0754
Epoch 5/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1632 - accuracy: 0.4023 - val_loss: 2.0939 - val_accuracy: 0.0820
Epoch 6/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1226 - accuracy: 0.4072 - val_loss: 2.0827 - val_accuracy: 0.0852
Epoch 7/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1790 - accuracy: 0.3908 - val_loss: 2.0745 - val_accuracy: 0.0852
Epoch 8/100
2/2 [==============================] - 0s 34ms/step - loss: 2.1883 - accuracy: 0.3826 - val_loss: 2.0659 - val_accuracy: 0.0918
Epoch 9/100
2/2 [==============================] - 0s 48ms/step - loss: 2.2325 - accuracy: 0.3826 - val_loss: 2.0576 - val_accuracy: 0.0951
Epoch 10/100
2/2 [==============================] - 0s 52ms/step - loss: 2.2499 - accuracy: 0.3793 - val_loss: 2.0481 - val_accuracy: 0.1016
Epoch 11/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1204 - accuracy: 0.3875 - val_loss: 2.0392 - val_accuracy: 0.1016
Epoch 12/100
2/2 [==============================] - 0s 34ms/step - loss: 2.2106 - accuracy: 0.4154 - val_loss: 2.0289 - val_accuracy: 0.1049
Epoch 13/100
2/2 [==============================] - 0s 35ms/step - loss: 2.1204 - accuracy: 0.4269 - val_loss: 2.0198 - val_accuracy: 0.1082
Epoch 14/100
2/2 [==============================] - 0s 34ms/step - loss: 2.1692 - accuracy: 0.3612 - val_loss: 2.0112 - val_accuracy: 0.1115
Epoch 15/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0857 - accuracy: 0.4039 - val_loss: 2.0019 - val_accuracy: 0.1148
Epoch 16/100
2/2 [==============================] - 0s 50ms/step - loss: 2.0943 - accuracy: 0.3924 - val_loss: 1.9938 - val_accuracy: 0.1148
Epoch 17/100
2/2 [==============================] - 0s 41ms/step - loss: 2.1698 - accuracy: 0.3859 - val_loss: 1.9851 - val_accuracy: 0.1148
Epoch 18/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1743 - accuracy: 0.3875 - val_loss: 1.9778 - val_accuracy: 0.1180
Epoch 19/100
2/2 [==============================] - 0s 34ms/step - loss: 2.1720 - accuracy: 0.4023 - val_loss: 1.9704 - val_accuracy: 0.1180
Epoch 20/100
2/2 [==============================] - 0s 31ms/step - loss: 2.1703 - accuracy: 0.3859 - val_loss: 1.9629 - val_accuracy: 0.1213
Epoch 21/100
2/2 [==============================] - 0s 42ms/step - loss: 2.1260 - accuracy: 0.3892 - val_loss: 1.9550 - val_accuracy: 0.1279
Epoch 22/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1972 - accuracy: 0.3875 - val_loss: 1.9485 - val_accuracy: 0.1344
Epoch 23/100
2/2 [==============================] - 0s 45ms/step - loss: 2.1259 - accuracy: 0.3957 - val_loss: 1.9400 - val_accuracy: 0.1377
Epoch 24/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1167 - accuracy: 0.3908 - val_loss: 1.9338 - val_accuracy: 0.1443
Epoch 25/100
2/2 [==============================] - 0s 50ms/step - loss: 2.1111 - accuracy: 0.3875 - val_loss: 1.9280 - val_accuracy: 0.1508
Epoch 26/100
2/2 [==============================] - 0s 49ms/step - loss: 2.1311 - accuracy: 0.3941 - val_loss: 1.9210 - val_accuracy: 0.1574
Epoch 27/100
2/2 [==============================] - 0s 48ms/step - loss: 2.1576 - accuracy: 0.3859 - val_loss: 1.9129 - val_accuracy: 0.1574
Epoch 28/100
2/2 [==============================] - 0s 28ms/step - loss: 2.1077 - accuracy: 0.4039 - val_loss: 1.9050 - val_accuracy: 0.1574
Epoch 29/100
2/2 [==============================] - 0s 30ms/step - loss: 2.2171 - accuracy: 0.3941 - val_loss: 1.8985 - val_accuracy: 0.1607
Epoch 30/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1298 - accuracy: 0.4105 - val_loss: 1.8920 - val_accuracy: 0.1639
Epoch 31/100
2/2 [==============================] - 0s 33ms/step - loss: 2.1943 - accuracy: 0.3957 - val_loss: 1.8851 - val_accuracy: 0.1639
Epoch 32/100
2/2 [==============================] - 0s 39ms/step - loss: 2.1350 - accuracy: 0.3875 - val_loss: 1.8779 - val_accuracy: 0.1672
Epoch 33/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1331 - accuracy: 0.3826 - val_loss: 1.8709 - val_accuracy: 0.1672
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1584 - accuracy: 0.4056 - val_loss: 1.8651 - val_accuracy: 0.1738
Epoch 35/100
2/2 [==============================] - 0s 44ms/step - loss: 2.1168 - accuracy: 0.4187 - val_loss: 1.8598 - val_accuracy: 0.1738
Epoch 36/100
2/2 [==============================] - 0s 49ms/step - loss: 2.1559 - accuracy: 0.4072 - val_loss: 1.8535 - val_accuracy: 0.1770
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0422 - accuracy: 0.4105 - val_loss: 1.8485 - val_accuracy: 0.1770
Epoch 38/100
2/2 [==============================] - 0s 48ms/step - loss: 2.1719 - accuracy: 0.3941 - val_loss: 1.8445 - val_accuracy: 0.1836
Epoch 39/100
2/2 [==============================] - 0s 29ms/step - loss: 2.0618 - accuracy: 0.4154 - val_loss: 1.8389 - val_accuracy: 0.1902
Epoch 40/100
2/2 [==============================] - 0s 32ms/step - loss: 2.1425 - accuracy: 0.3908 - val_loss: 1.8338 - val_accuracy: 0.1934
Epoch 41/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1087 - accuracy: 0.3859 - val_loss: 1.8292 - val_accuracy: 0.2000
Epoch 42/100
2/2 [==============================] - 0s 67ms/step - loss: 2.1145 - accuracy: 0.3990 - val_loss: 1.8244 - val_accuracy: 0.2098
Epoch 43/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1591 - accuracy: 0.3793 - val_loss: 1.8191 - val_accuracy: 0.2197
Epoch 44/100
2/2 [==============================] - 0s 31ms/step - loss: 2.1223 - accuracy: 0.4072 - val_loss: 1.8157 - val_accuracy: 0.2197
Epoch 45/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0537 - accuracy: 0.3957 - val_loss: 1.8096 - val_accuracy: 0.2262
Epoch 46/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0361 - accuracy: 0.4532 - val_loss: 1.8053 - val_accuracy: 0.2295
Epoch 47/100
2/2 [==============================] - 0s 47ms/step - loss: 2.2182 - accuracy: 0.3760 - val_loss: 1.7991 - val_accuracy: 0.2328
Epoch 48/100
2/2 [==============================] - 0s 43ms/step - loss: 2.1853 - accuracy: 0.3892 - val_loss: 1.7942 - val_accuracy: 0.2328
Epoch 49/100
2/2 [==============================] - 0s 35ms/step - loss: 2.2075 - accuracy: 0.3859 - val_loss: 1.7881 - val_accuracy: 0.2361
Epoch 50/100
2/2 [==============================] - 0s 34ms/step - loss: 2.1360 - accuracy: 0.4039 - val_loss: 1.7850 - val_accuracy: 0.2361
Epoch 51/100
2/2 [==============================] - 0s 35ms/step - loss: 2.1007 - accuracy: 0.3974 - val_loss: 1.7811 - val_accuracy: 0.2361
Epoch 52/100
2/2 [==============================] - 0s 50ms/step - loss: 2.0815 - accuracy: 0.3875 - val_loss: 1.7763 - val_accuracy: 0.2361
Epoch 53/100
2/2 [==============================] - 0s 48ms/step - loss: 2.1759 - accuracy: 0.4056 - val_loss: 1.7718 - val_accuracy: 0.2393
Epoch 54/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0860 - accuracy: 0.4007 - val_loss: 1.7686 - val_accuracy: 0.2393
Epoch 55/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0784 - accuracy: 0.4023 - val_loss: 1.7644 - val_accuracy: 0.2426
Epoch 56/100
2/2 [==============================] - 0s 32ms/step - loss: 2.0837 - accuracy: 0.3859 - val_loss: 1.7596 - val_accuracy: 0.2459
Epoch 57/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0861 - accuracy: 0.4138 - val_loss: 1.7561 - val_accuracy: 0.2459
Epoch 58/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0864 - accuracy: 0.4138 - val_loss: 1.7538 - val_accuracy: 0.2492
Epoch 59/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0326 - accuracy: 0.4039 - val_loss: 1.7506 - val_accuracy: 0.2492
Epoch 60/100
2/2 [==============================] - 0s 43ms/step - loss: 1.9559 - accuracy: 0.4351 - val_loss: 1.7473 - val_accuracy: 0.2557
Epoch 61/100
2/2 [==============================] - 0s 48ms/step - loss: 2.1460 - accuracy: 0.3777 - val_loss: 1.7424 - val_accuracy: 0.2590
Epoch 62/100
2/2 [==============================] - 0s 41ms/step - loss: 2.2493 - accuracy: 0.3810 - val_loss: 1.7399 - val_accuracy: 0.2623
Epoch 63/100
2/2 [==============================] - 0s 44ms/step - loss: 2.0250 - accuracy: 0.4039 - val_loss: 1.7359 - val_accuracy: 0.2623
Epoch 64/100
2/2 [==============================] - 0s 46ms/step - loss: 2.2158 - accuracy: 0.4154 - val_loss: 1.7317 - val_accuracy: 0.2754
Epoch 65/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0437 - accuracy: 0.4171 - val_loss: 1.7289 - val_accuracy: 0.2754
Epoch 66/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1400 - accuracy: 0.3908 - val_loss: 1.7263 - val_accuracy: 0.2787
Epoch 67/100
2/2 [==============================] - 0s 35ms/step - loss: 2.0740 - accuracy: 0.3859 - val_loss: 1.7230 - val_accuracy: 0.2820
Epoch 68/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1539 - accuracy: 0.4007 - val_loss: 1.7203 - val_accuracy: 0.2918
Epoch 69/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0904 - accuracy: 0.4154 - val_loss: 1.7176 - val_accuracy: 0.2951
Epoch 70/100
2/2 [==============================] - 0s 37ms/step - loss: 2.1222 - accuracy: 0.3908 - val_loss: 1.7144 - val_accuracy: 0.2984
Epoch 71/100
2/2 [==============================] - 0s 49ms/step - loss: 2.1905 - accuracy: 0.4056 - val_loss: 1.7105 - val_accuracy: 0.2984
Epoch 72/100
2/2 [==============================] - 0s 50ms/step - loss: 2.1437 - accuracy: 0.4253 - val_loss: 1.7087 - val_accuracy: 0.3016
Epoch 73/100
2/2 [==============================] - 0s 42ms/step - loss: 2.0766 - accuracy: 0.4171 - val_loss: 1.7061 - val_accuracy: 0.3049
Epoch 74/100
2/2 [==============================] - 0s 45ms/step - loss: 2.1811 - accuracy: 0.4023 - val_loss: 1.7025 - val_accuracy: 0.3049
Epoch 75/100
2/2 [==============================] - 0s 46ms/step - loss: 2.1047 - accuracy: 0.4056 - val_loss: 1.7004 - val_accuracy: 0.3115
Epoch 76/100
2/2 [==============================] - 0s 34ms/step - loss: 1.9861 - accuracy: 0.4401 - val_loss: 1.6983 - val_accuracy: 0.3246
Epoch 77/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1271 - accuracy: 0.4122 - val_loss: 1.6959 - val_accuracy: 0.3279
Epoch 78/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1190 - accuracy: 0.3957 - val_loss: 1.6921 - val_accuracy: 0.3311
Epoch 79/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0366 - accuracy: 0.4122 - val_loss: 1.6902 - val_accuracy: 0.3311
Epoch 80/100
2/2 [==============================] - 0s 51ms/step - loss: 2.0889 - accuracy: 0.4154 - val_loss: 1.6889 - val_accuracy: 0.3311
Epoch 81/100
2/2 [==============================] - 0s 48ms/step - loss: 2.0589 - accuracy: 0.4269 - val_loss: 1.6870 - val_accuracy: 0.3410
Epoch 82/100
2/2 [==============================] - 0s 34ms/step - loss: 2.1267 - accuracy: 0.4138 - val_loss: 1.6845 - val_accuracy: 0.3443
Epoch 83/100
2/2 [==============================] - 0s 34ms/step - loss: 2.2834 - accuracy: 0.3924 - val_loss: 1.6835 - val_accuracy: 0.3443
Epoch 84/100
2/2 [==============================] - 0s 38ms/step - loss: 2.0849 - accuracy: 0.4220 - val_loss: 1.6798 - val_accuracy: 0.3475
Epoch 85/100
2/2 [==============================] - 0s 45ms/step - loss: 2.1101 - accuracy: 0.3908 - val_loss: 1.6769 - val_accuracy: 0.3475
Epoch 86/100
2/2 [==============================] - 0s 40ms/step - loss: 2.0617 - accuracy: 0.4171 - val_loss: 1.6739 - val_accuracy: 0.3475
Epoch 87/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0798 - accuracy: 0.4089 - val_loss: 1.6721 - val_accuracy: 0.3607
Epoch 88/100
2/2 [==============================] - 0s 42ms/step - loss: 2.0823 - accuracy: 0.4236 - val_loss: 1.6705 - val_accuracy: 0.3672
Epoch 89/100
2/2 [==============================] - 0s 47ms/step - loss: 2.1255 - accuracy: 0.3777 - val_loss: 1.6692 - val_accuracy: 0.3738
Epoch 90/100
2/2 [==============================] - 0s 50ms/step - loss: 2.0906 - accuracy: 0.4007 - val_loss: 1.6657 - val_accuracy: 0.3770
Epoch 91/100
2/2 [==============================] - 0s 42ms/step - loss: 2.0803 - accuracy: 0.4220 - val_loss: 1.6623 - val_accuracy: 0.3770
Epoch 92/100
2/2 [==============================] - 0s 41ms/step - loss: 2.0654 - accuracy: 0.4105 - val_loss: 1.6614 - val_accuracy: 0.3770
Epoch 93/100
2/2 [==============================] - 0s 47ms/step - loss: 1.9954 - accuracy: 0.4138 - val_loss: 1.6589 - val_accuracy: 0.3770
Epoch 94/100
2/2 [==============================] - 0s 45ms/step - loss: 2.0903 - accuracy: 0.4023 - val_loss: 1.6566 - val_accuracy: 0.3738
Epoch 95/100
2/2 [==============================] - 0s 39ms/step - loss: 2.2208 - accuracy: 0.3957 - val_loss: 1.6545 - val_accuracy: 0.3770
Epoch 96/100
2/2 [==============================] - 0s 36ms/step - loss: 2.1106 - accuracy: 0.3924 - val_loss: 1.6526 - val_accuracy: 0.3770
Epoch 97/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1591 - accuracy: 0.4072 - val_loss: 1.6521 - val_accuracy: 0.3770
Epoch 98/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0497 - accuracy: 0.4204 - val_loss: 1.6498 - val_accuracy: 0.3770
Epoch 99/100
2/2 [==============================] - 0s 49ms/step - loss: 2.0034 - accuracy: 0.4122 - val_loss: 1.6490 - val_accuracy: 0.3770
Epoch 100/100
2/2 [==============================] - 0s 49ms/step - loss: 2.1024 - accuracy: 0.4187 - val_loss: 1.6462 - val_accuracy: 0.3803
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Model parameters: {'learning_rate': 1e-05, 'hidden_layers': 3, 'hidden_units': 16, 'learning_rate_decay': 0.0001, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.01, 'dropout_rate': 0.3, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': True, 'initializers': 'he_normal'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 247ms/step - loss: 2.1366 - accuracy: 0.2361 - val_loss: 1.3825 - val_accuracy: 0.3191
Epoch 2/100
2/2 [==============================] - 0s 39ms/step - loss: 2.0646 - accuracy: 0.2459 - val_loss: 1.3861 - val_accuracy: 0.3191
Epoch 3/100
2/2 [==============================] - 0s 41ms/step - loss: 2.1321 - accuracy: 0.2475 - val_loss: 1.3888 - val_accuracy: 0.3191
Epoch 4/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0813 - accuracy: 0.2574 - val_loss: 1.3923 - val_accuracy: 0.3158
Epoch 5/100
2/2 [==============================] - 0s 36ms/step - loss: 2.0580 - accuracy: 0.2541 - val_loss: 1.3961 - val_accuracy: 0.3158
Epoch 6/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0771 - accuracy: 0.2607 - val_loss: 1.3987 - val_accuracy: 0.3158
Epoch 7/100
2/2 [==============================] - 0s 33ms/step - loss: 2.0561 - accuracy: 0.2689 - val_loss: 1.4017 - val_accuracy: 0.3158
Epoch 8/100
2/2 [==============================] - 0s 37ms/step - loss: 2.0636 - accuracy: 0.2623 - val_loss: 1.4043 - val_accuracy: 0.3158
Epoch 9/100
2/2 [==============================] - 0s 38ms/step - loss: 2.1386 - accuracy: 0.2574 - val_loss: 1.4072 - val_accuracy: 0.3158
Epoch 10/100
2/2 [==============================] - 0s 34ms/step - loss: 2.0348 - accuracy: 0.2607 - val_loss: 1.4107 - val_accuracy: 0.3125
Epoch 11/100
1/2 [==============>...............] - ETA: 0s - loss: 2.1143 - accuracy: 0.2637Restoring model weights from the end of the best epoch: 1.
2/2 [==============================] - 0s 51ms/step - loss: 2.0957 - accuracy: 0.2721 - val_loss: 1.4140 - val_accuracy: 0.3125
Epoch 11: early stopping
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 504us/step
Experiment number: 6
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 1, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': True, 'initializers': 'glorot_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 67ms/step - loss: 16.6942 - accuracy: 0.5008 - val_loss: 8.1739 - val_accuracy: 0.8164
Epoch 2/100
5/5 [==============================] - 0s 15ms/step - loss: 6.4341 - accuracy: 0.6831 - val_loss: 3.4627 - val_accuracy: 0.8164
Epoch 3/100
5/5 [==============================] - 0s 10ms/step - loss: 2.7272 - accuracy: 0.8013 - val_loss: 2.2567 - val_accuracy: 0.8164
Epoch 4/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8835 - accuracy: 0.8670 - val_loss: 1.9476 - val_accuracy: 0.8164
Epoch 5/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8041 - accuracy: 0.8621 - val_loss: 2.0173 - val_accuracy: 0.8164
Epoch 6/100
5/5 [==============================] - 0s 13ms/step - loss: 1.7728 - accuracy: 0.8654 - val_loss: 1.9190 - val_accuracy: 0.8164
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8529 - accuracy: 0.8539 - val_loss: 2.0189 - val_accuracy: 0.8164
Epoch 8/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8124 - accuracy: 0.8654 - val_loss: 2.0140 - val_accuracy: 0.8164
Epoch 9/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8023 - accuracy: 0.8571 - val_loss: 1.9833 - val_accuracy: 0.8164
Epoch 10/100
5/5 [==============================] - 0s 11ms/step - loss: 1.8290 - accuracy: 0.8637 - val_loss: 1.9586 - val_accuracy: 0.8164
Epoch 11/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8088 - accuracy: 0.8604 - val_loss: 1.9989 - val_accuracy: 0.8164
Epoch 12/100
5/5 [==============================] - 0s 10ms/step - loss: 1.8035 - accuracy: 0.8555 - val_loss: 2.0385 - val_accuracy: 0.8164
Epoch 13/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8153 - accuracy: 0.8539 - val_loss: 1.9609 - val_accuracy: 0.8164
Epoch 14/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8408 - accuracy: 0.8489 - val_loss: 2.0036 - val_accuracy: 0.8164
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8073 - accuracy: 0.8604 - val_loss: 2.0086 - val_accuracy: 0.8164
Epoch 16/100
1/5 [=====>........................] - ETA: 0s - loss: 1.7784 - accuracy: 0.8594Restoring model weights from the end of the best epoch: 6.
5/5 [==============================] - 0s 14ms/step - loss: 1.7965 - accuracy: 0.8621 - val_loss: 2.0334 - val_accuracy: 0.8164
Epoch 16: early stopping
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 1, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': True, 'initializers': 'glorot_normal'}
Batch size: 128
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
5/5 [==============================] - 1s 65ms/step - loss: 16.3605 - accuracy: 0.5090 - val_loss: 7.8345 - val_accuracy: 0.8721
Epoch 2/100
5/5 [==============================] - 0s 14ms/step - loss: 6.3912 - accuracy: 0.6667 - val_loss: 3.2080 - val_accuracy: 0.8721
Epoch 3/100
5/5 [==============================] - 0s 16ms/step - loss: 2.8838 - accuracy: 0.8030 - val_loss: 2.0162 - val_accuracy: 0.8721
Epoch 4/100
5/5 [==============================] - 0s 16ms/step - loss: 2.0834 - accuracy: 0.8079 - val_loss: 1.8422 - val_accuracy: 0.8721
Epoch 5/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8203 - accuracy: 0.8374 - val_loss: 1.8582 - val_accuracy: 0.8721
Epoch 6/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8526 - accuracy: 0.8309 - val_loss: 1.8401 - val_accuracy: 0.8721
Epoch 7/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8289 - accuracy: 0.8358 - val_loss: 1.8644 - val_accuracy: 0.8721
Epoch 8/100
5/5 [==============================] - 0s 9ms/step - loss: 1.8563 - accuracy: 0.8276 - val_loss: 1.9681 - val_accuracy: 0.8721
Epoch 9/100
5/5 [==============================] - 0s 13ms/step - loss: 1.9036 - accuracy: 0.8424 - val_loss: 1.8333 - val_accuracy: 0.8721
Epoch 10/100
5/5 [==============================] - 0s 16ms/step - loss: 1.8706 - accuracy: 0.8227 - val_loss: 1.8240 - val_accuracy: 0.8721
Epoch 11/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8796 - accuracy: 0.8292 - val_loss: 1.8585 - val_accuracy: 0.8721
Epoch 12/100
5/5 [==============================] - 0s 16ms/step - loss: 1.8377 - accuracy: 0.8391 - val_loss: 1.8060 - val_accuracy: 0.8721
Epoch 13/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8856 - accuracy: 0.8292 - val_loss: 1.8233 - val_accuracy: 0.8721
Epoch 14/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8419 - accuracy: 0.8407 - val_loss: 1.8316 - val_accuracy: 0.8721
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8611 - accuracy: 0.8259 - val_loss: 1.8694 - val_accuracy: 0.8721
Epoch 16/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8517 - accuracy: 0.8391 - val_loss: 1.8918 - val_accuracy: 0.8721
Epoch 17/100
5/5 [==============================] - 0s 15ms/step - loss: 1.8655 - accuracy: 0.8424 - val_loss: 1.8498 - val_accuracy: 0.8721
Epoch 18/100
5/5 [==============================] - 0s 11ms/step - loss: 1.8904 - accuracy: 0.8227 - val_loss: 1.7969 - val_accuracy: 0.8721
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8782 - accuracy: 0.8342 - val_loss: 1.8349 - val_accuracy: 0.8721
Epoch 20/100
5/5 [==============================] - 0s 11ms/step - loss: 1.8281 - accuracy: 0.8407 - val_loss: 1.8812 - val_accuracy: 0.8721
Epoch 21/100
5/5 [==============================] - 0s 11ms/step - loss: 1.8558 - accuracy: 0.8243 - val_loss: 1.8500 - val_accuracy: 0.8721
Epoch 22/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8499 - accuracy: 0.8358 - val_loss: 1.8502 - val_accuracy: 0.8721
Epoch 23/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8265 - accuracy: 0.8489 - val_loss: 1.8169 - val_accuracy: 0.8721
Epoch 24/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8464 - accuracy: 0.8227 - val_loss: 1.8484 - val_accuracy: 0.8721
Epoch 25/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8462 - accuracy: 0.8325 - val_loss: 1.8255 - val_accuracy: 0.8721
Epoch 26/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8357 - accuracy: 0.8571 - val_loss: 1.8073 - val_accuracy: 0.8721
Epoch 27/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8541 - accuracy: 0.8456 - val_loss: 1.8392 - val_accuracy: 0.8721
Epoch 28/100
1/5 [=====>........................] - ETA: 0s - loss: 1.8263 - accuracy: 0.8594Restoring model weights from the end of the best epoch: 18.
5/5 [==============================] - 0s 14ms/step - loss: 1.8322 - accuracy: 0.8407 - val_loss: 1.8126 - val_accuracy: 0.8721
Epoch 28: early stopping
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 1, 'hidden_units': 256, 'learning_rate_decay': 1e-06, 'optimizer': 'RMSprop', 'l1': 0.1, 'l2': 0.1, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': 0.8, 'batch_norm': True, 'initializers': 'glorot_normal'}
Batch size: 128
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
5/5 [==============================] - 1s 65ms/step - loss: 16.7367 - accuracy: 0.5180 - val_loss: 8.2470 - val_accuracy: 0.8618
Epoch 2/100
5/5 [==============================] - 0s 12ms/step - loss: 6.5231 - accuracy: 0.6852 - val_loss: 3.4640 - val_accuracy: 0.8618
Epoch 3/100
5/5 [==============================] - 0s 13ms/step - loss: 2.7340 - accuracy: 0.8328 - val_loss: 2.2269 - val_accuracy: 0.8618
Epoch 4/100
5/5 [==============================] - 0s 9ms/step - loss: 1.9410 - accuracy: 0.8607 - val_loss: 1.8899 - val_accuracy: 0.8618
Epoch 5/100
5/5 [==============================] - 0s 13ms/step - loss: 1.7869 - accuracy: 0.8574 - val_loss: 1.9018 - val_accuracy: 0.8618
Epoch 6/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8185 - accuracy: 0.8525 - val_loss: 1.8654 - val_accuracy: 0.8618
Epoch 7/100
5/5 [==============================] - 0s 11ms/step - loss: 1.7892 - accuracy: 0.8623 - val_loss: 1.9010 - val_accuracy: 0.8618
Epoch 8/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8183 - accuracy: 0.8656 - val_loss: 1.8757 - val_accuracy: 0.8618
Epoch 9/100
5/5 [==============================] - 0s 16ms/step - loss: 1.8389 - accuracy: 0.8557 - val_loss: 1.8950 - val_accuracy: 0.8618
Epoch 10/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8323 - accuracy: 0.8328 - val_loss: 1.8944 - val_accuracy: 0.8618
Epoch 11/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8612 - accuracy: 0.8475 - val_loss: 1.9896 - val_accuracy: 0.8618
Epoch 12/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8066 - accuracy: 0.8623 - val_loss: 1.9038 - val_accuracy: 0.8618
Epoch 13/100
5/5 [==============================] - 0s 13ms/step - loss: 1.7847 - accuracy: 0.8607 - val_loss: 1.9527 - val_accuracy: 0.8618
Epoch 14/100
5/5 [==============================] - 0s 16ms/step - loss: 1.8323 - accuracy: 0.8508 - val_loss: 1.8628 - val_accuracy: 0.8618
Epoch 15/100
5/5 [==============================] - 0s 13ms/step - loss: 1.7726 - accuracy: 0.8721 - val_loss: 1.8749 - val_accuracy: 0.8618
Epoch 16/100
5/5 [==============================] - 0s 9ms/step - loss: 1.8061 - accuracy: 0.8492 - val_loss: 1.9398 - val_accuracy: 0.8618
Epoch 17/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8048 - accuracy: 0.8672 - val_loss: 1.9262 - val_accuracy: 0.8618
Epoch 18/100
5/5 [==============================] - 0s 13ms/step - loss: 1.7923 - accuracy: 0.8590 - val_loss: 1.8868 - val_accuracy: 0.8618
Epoch 19/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8123 - accuracy: 0.8557 - val_loss: 1.8973 - val_accuracy: 0.8618
Epoch 20/100
5/5 [==============================] - 0s 12ms/step - loss: 1.7979 - accuracy: 0.8639 - val_loss: 1.8939 - val_accuracy: 0.8618
Epoch 21/100
5/5 [==============================] - 0s 12ms/step - loss: 1.8073 - accuracy: 0.8443 - val_loss: 1.8969 - val_accuracy: 0.8618
Epoch 22/100
5/5 [==============================] - 0s 13ms/step - loss: 1.8230 - accuracy: 0.8459 - val_loss: 1.9254 - val_accuracy: 0.8618
Epoch 23/100
5/5 [==============================] - 0s 14ms/step - loss: 1.8062 - accuracy: 0.8541 - val_loss: 1.9045 - val_accuracy: 0.8618
Epoch 24/100
1/5 [=====>........................] - ETA: 0s - loss: 1.7999 - accuracy: 0.8438Restoring model weights from the end of the best epoch: 14.
5/5 [==============================] - 0s 12ms/step - loss: 1.8178 - accuracy: 0.8410 - val_loss: 1.8730 - val_accuracy: 0.8618
Epoch 24: early stopping
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 7
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': False, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 220ms/step - loss: 1.0937 - accuracy: 0.6749 - val_loss: 0.9444 - val_accuracy: 0.8164
Epoch 2/100
2/2 [==============================] - 0s 37ms/step - loss: 0.9107 - accuracy: 0.8670 - val_loss: 0.8191 - val_accuracy: 0.8164
Epoch 3/100
2/2 [==============================] - 0s 50ms/step - loss: 0.7654 - accuracy: 0.8670 - val_loss: 0.7278 - val_accuracy: 0.8164
Epoch 4/100
2/2 [==============================] - 0s 41ms/step - loss: 0.6655 - accuracy: 0.8670 - val_loss: 0.6652 - val_accuracy: 0.8164
Epoch 5/100
2/2 [==============================] - 0s 33ms/step - loss: 0.5896 - accuracy: 0.8670 - val_loss: 0.6232 - val_accuracy: 0.8164
Epoch 6/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5405 - accuracy: 0.8670 - val_loss: 0.5925 - val_accuracy: 0.8164
Epoch 7/100
2/2 [==============================] - 0s 32ms/step - loss: 0.5061 - accuracy: 0.8670 - val_loss: 0.5686 - val_accuracy: 0.8164
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 0.4865 - accuracy: 0.8670 - val_loss: 0.5474 - val_accuracy: 0.8164
Epoch 9/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4544 - accuracy: 0.8670 - val_loss: 0.5288 - val_accuracy: 0.8164
Epoch 10/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4509 - accuracy: 0.8670 - val_loss: 0.5127 - val_accuracy: 0.8164
Epoch 11/100
2/2 [==============================] - 0s 40ms/step - loss: 0.4337 - accuracy: 0.8670 - val_loss: 0.5003 - val_accuracy: 0.8164
Epoch 12/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4379 - accuracy: 0.8686 - val_loss: 0.4912 - val_accuracy: 0.8459
Epoch 13/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4180 - accuracy: 0.8752 - val_loss: 0.4839 - val_accuracy: 0.8557
Epoch 14/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4161 - accuracy: 0.8785 - val_loss: 0.4784 - val_accuracy: 0.8492
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4173 - accuracy: 0.8785 - val_loss: 0.4747 - val_accuracy: 0.8426
Epoch 16/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4063 - accuracy: 0.8752 - val_loss: 0.4726 - val_accuracy: 0.8426
Epoch 17/100
2/2 [==============================] - 0s 41ms/step - loss: 0.3950 - accuracy: 0.8818 - val_loss: 0.4716 - val_accuracy: 0.8492
Epoch 18/100
2/2 [==============================] - 0s 35ms/step - loss: 0.3932 - accuracy: 0.8637 - val_loss: 0.4704 - val_accuracy: 0.8557
Epoch 19/100
2/2 [==============================] - 0s 35ms/step - loss: 0.3895 - accuracy: 0.8736 - val_loss: 0.4681 - val_accuracy: 0.8525
Epoch 20/100
2/2 [==============================] - 0s 36ms/step - loss: 0.3908 - accuracy: 0.8768 - val_loss: 0.4673 - val_accuracy: 0.8426
Epoch 21/100
2/2 [==============================] - 0s 36ms/step - loss: 0.3784 - accuracy: 0.8703 - val_loss: 0.4685 - val_accuracy: 0.8361
Epoch 22/100
2/2 [==============================] - 0s 38ms/step - loss: 0.3856 - accuracy: 0.8703 - val_loss: 0.4684 - val_accuracy: 0.8361
Epoch 23/100
2/2 [==============================] - 0s 34ms/step - loss: 0.3780 - accuracy: 0.8736 - val_loss: 0.4665 - val_accuracy: 0.8361
Epoch 24/100
2/2 [==============================] - 0s 50ms/step - loss: 0.3723 - accuracy: 0.8703 - val_loss: 0.4623 - val_accuracy: 0.8361
Epoch 25/100
2/2 [==============================] - 0s 47ms/step - loss: 0.3696 - accuracy: 0.8752 - val_loss: 0.4566 - val_accuracy: 0.8393
Epoch 26/100
2/2 [==============================] - 0s 33ms/step - loss: 0.3594 - accuracy: 0.8801 - val_loss: 0.4493 - val_accuracy: 0.8492
Epoch 27/100
2/2 [==============================] - 0s 41ms/step - loss: 0.3684 - accuracy: 0.8785 - val_loss: 0.4448 - val_accuracy: 0.8492
Epoch 28/100
2/2 [==============================] - 0s 32ms/step - loss: 0.3564 - accuracy: 0.8752 - val_loss: 0.4427 - val_accuracy: 0.8525
Epoch 29/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3556 - accuracy: 0.8637 - val_loss: 0.4421 - val_accuracy: 0.8525
Epoch 30/100
2/2 [==============================] - 0s 40ms/step - loss: 0.3583 - accuracy: 0.8736 - val_loss: 0.4430 - val_accuracy: 0.8492
Epoch 31/100
2/2 [==============================] - 0s 28ms/step - loss: 0.3510 - accuracy: 0.8752 - val_loss: 0.4437 - val_accuracy: 0.8426
Epoch 32/100
2/2 [==============================] - 0s 33ms/step - loss: 0.3414 - accuracy: 0.8768 - val_loss: 0.4430 - val_accuracy: 0.8459
Epoch 33/100
2/2 [==============================] - 0s 35ms/step - loss: 0.3400 - accuracy: 0.8785 - val_loss: 0.4383 - val_accuracy: 0.8459
Epoch 34/100
2/2 [==============================] - 0s 35ms/step - loss: 0.3453 - accuracy: 0.8834 - val_loss: 0.4330 - val_accuracy: 0.8459
Epoch 35/100
2/2 [==============================] - 0s 41ms/step - loss: 0.3479 - accuracy: 0.8834 - val_loss: 0.4296 - val_accuracy: 0.8557
Epoch 36/100
2/2 [==============================] - 0s 47ms/step - loss: 0.3372 - accuracy: 0.8916 - val_loss: 0.4265 - val_accuracy: 0.8590
Epoch 37/100
2/2 [==============================] - 0s 40ms/step - loss: 0.3359 - accuracy: 0.8834 - val_loss: 0.4248 - val_accuracy: 0.8689
Epoch 38/100
2/2 [==============================] - 0s 28ms/step - loss: 0.3321 - accuracy: 0.8867 - val_loss: 0.4254 - val_accuracy: 0.8721
Epoch 39/100
2/2 [==============================] - 0s 32ms/step - loss: 0.3380 - accuracy: 0.8818 - val_loss: 0.4262 - val_accuracy: 0.8623
Epoch 40/100
2/2 [==============================] - 0s 33ms/step - loss: 0.3397 - accuracy: 0.8900 - val_loss: 0.4283 - val_accuracy: 0.8590
Epoch 41/100
2/2 [==============================] - 0s 32ms/step - loss: 0.3236 - accuracy: 0.8834 - val_loss: 0.4299 - val_accuracy: 0.8590
Epoch 42/100
2/2 [==============================] - 0s 40ms/step - loss: 0.3266 - accuracy: 0.8867 - val_loss: 0.4286 - val_accuracy: 0.8557
Epoch 43/100
2/2 [==============================] - 0s 47ms/step - loss: 0.3230 - accuracy: 0.8818 - val_loss: 0.4262 - val_accuracy: 0.8557
Epoch 44/100
2/2 [==============================] - 0s 43ms/step - loss: 0.3206 - accuracy: 0.8916 - val_loss: 0.4192 - val_accuracy: 0.8590
Epoch 45/100
2/2 [==============================] - 0s 48ms/step - loss: 0.3164 - accuracy: 0.8900 - val_loss: 0.4136 - val_accuracy: 0.8590
Epoch 46/100
2/2 [==============================] - 0s 30ms/step - loss: 0.3194 - accuracy: 0.8933 - val_loss: 0.4112 - val_accuracy: 0.8525
Epoch 47/100
2/2 [==============================] - 0s 31ms/step - loss: 0.3171 - accuracy: 0.8900 - val_loss: 0.4101 - val_accuracy: 0.8525
Epoch 48/100
2/2 [==============================] - 0s 38ms/step - loss: 0.3264 - accuracy: 0.8916 - val_loss: 0.4113 - val_accuracy: 0.8525
Epoch 49/100
2/2 [==============================] - 0s 36ms/step - loss: 0.3176 - accuracy: 0.8818 - val_loss: 0.4166 - val_accuracy: 0.8426
Epoch 50/100
2/2 [==============================] - 0s 49ms/step - loss: 0.3228 - accuracy: 0.8752 - val_loss: 0.4253 - val_accuracy: 0.8361
Epoch 51/100
2/2 [==============================] - 0s 32ms/step - loss: 0.3255 - accuracy: 0.8818 - val_loss: 0.4272 - val_accuracy: 0.8361
Epoch 52/100
2/2 [==============================] - 0s 32ms/step - loss: 0.3170 - accuracy: 0.8851 - val_loss: 0.4214 - val_accuracy: 0.8393
Epoch 53/100
2/2 [==============================] - 0s 49ms/step - loss: 0.3166 - accuracy: 0.8900 - val_loss: 0.4160 - val_accuracy: 0.8426
Epoch 54/100
2/2 [==============================] - 0s 26ms/step - loss: 0.3131 - accuracy: 0.8949 - val_loss: 0.4138 - val_accuracy: 0.8459
Epoch 55/100
2/2 [==============================] - 0s 31ms/step - loss: 0.3123 - accuracy: 0.8851 - val_loss: 0.4150 - val_accuracy: 0.8459
Epoch 56/100
2/2 [==============================] - 0s 34ms/step - loss: 0.3119 - accuracy: 0.8883 - val_loss: 0.4180 - val_accuracy: 0.8426
Epoch 57/100
1/2 [==============>...............] - ETA: 0s - loss: 0.3107 - accuracy: 0.8945Restoring model weights from the end of the best epoch: 47.
2/2 [==============================] - 0s 53ms/step - loss: 0.3049 - accuracy: 0.8949 - val_loss: 0.4194 - val_accuracy: 0.8426
Epoch 57: early stopping
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No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': False, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 227ms/step - loss: 1.2025 - accuracy: 0.2545 - val_loss: 1.0216 - val_accuracy: 0.8721
Epoch 2/100
2/2 [==============================] - 0s 28ms/step - loss: 1.0156 - accuracy: 0.8161 - val_loss: 0.8688 - val_accuracy: 0.8721
Epoch 3/100
2/2 [==============================] - 0s 32ms/step - loss: 0.8771 - accuracy: 0.8391 - val_loss: 0.7455 - val_accuracy: 0.8721
Epoch 4/100
2/2 [==============================] - 1s 567ms/step - loss: 0.7744 - accuracy: 0.8391 - val_loss: 0.6486 - val_accuracy: 0.8721
Epoch 5/100
2/2 [==============================] - 0s 30ms/step - loss: 0.6912 - accuracy: 0.8391 - val_loss: 0.5761 - val_accuracy: 0.8721
Epoch 6/100
2/2 [==============================] - 0s 34ms/step - loss: 0.6265 - accuracy: 0.8391 - val_loss: 0.5251 - val_accuracy: 0.8721
Epoch 7/100
2/2 [==============================] - 0s 42ms/step - loss: 0.5852 - accuracy: 0.8391 - val_loss: 0.4895 - val_accuracy: 0.8721
Epoch 8/100
2/2 [==============================] - 0s 44ms/step - loss: 0.5530 - accuracy: 0.8391 - val_loss: 0.4645 - val_accuracy: 0.8721
Epoch 9/100
2/2 [==============================] - 0s 39ms/step - loss: 0.5261 - accuracy: 0.8391 - val_loss: 0.4450 - val_accuracy: 0.8721
Epoch 10/100
2/2 [==============================] - 0s 35ms/step - loss: 0.5139 - accuracy: 0.8391 - val_loss: 0.4284 - val_accuracy: 0.8721
Epoch 11/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4918 - accuracy: 0.8391 - val_loss: 0.4145 - val_accuracy: 0.8754
Epoch 12/100
2/2 [==============================] - 0s 38ms/step - loss: 0.4840 - accuracy: 0.8424 - val_loss: 0.4048 - val_accuracy: 0.8984
Epoch 13/100
2/2 [==============================] - 0s 41ms/step - loss: 0.4680 - accuracy: 0.8489 - val_loss: 0.3991 - val_accuracy: 0.9016
Epoch 14/100
2/2 [==============================] - 0s 48ms/step - loss: 0.4636 - accuracy: 0.8522 - val_loss: 0.3953 - val_accuracy: 0.8852
Epoch 15/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4638 - accuracy: 0.8391 - val_loss: 0.3908 - val_accuracy: 0.8820
Epoch 16/100
2/2 [==============================] - 0s 34ms/step - loss: 0.4550 - accuracy: 0.8358 - val_loss: 0.3840 - val_accuracy: 0.8885
Epoch 17/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4452 - accuracy: 0.8440 - val_loss: 0.3755 - val_accuracy: 0.8885
Epoch 18/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4459 - accuracy: 0.8456 - val_loss: 0.3672 - val_accuracy: 0.8918
Epoch 19/100
2/2 [==============================] - 0s 49ms/step - loss: 0.4264 - accuracy: 0.8686 - val_loss: 0.3612 - val_accuracy: 0.9016
Epoch 20/100
2/2 [==============================] - 0s 48ms/step - loss: 0.4269 - accuracy: 0.8522 - val_loss: 0.3570 - val_accuracy: 0.8852
Epoch 21/100
2/2 [==============================] - 0s 43ms/step - loss: 0.4060 - accuracy: 0.8555 - val_loss: 0.3533 - val_accuracy: 0.8885
Epoch 22/100
2/2 [==============================] - 0s 48ms/step - loss: 0.4112 - accuracy: 0.8604 - val_loss: 0.3500 - val_accuracy: 0.8885
Epoch 23/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4068 - accuracy: 0.8654 - val_loss: 0.3471 - val_accuracy: 0.8951
Epoch 24/100
2/2 [==============================] - 0s 35ms/step - loss: 0.4007 - accuracy: 0.8686 - val_loss: 0.3451 - val_accuracy: 0.8984
Epoch 25/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4006 - accuracy: 0.8588 - val_loss: 0.3440 - val_accuracy: 0.9016
Epoch 26/100
2/2 [==============================] - 0s 51ms/step - loss: 0.4032 - accuracy: 0.8604 - val_loss: 0.3430 - val_accuracy: 0.8951
Epoch 27/100
2/2 [==============================] - 0s 39ms/step - loss: 0.3948 - accuracy: 0.8539 - val_loss: 0.3417 - val_accuracy: 0.8984
Epoch 28/100
2/2 [==============================] - 0s 39ms/step - loss: 0.3959 - accuracy: 0.8637 - val_loss: 0.3393 - val_accuracy: 0.8984
Epoch 29/100
2/2 [==============================] - 0s 36ms/step - loss: 0.3823 - accuracy: 0.8654 - val_loss: 0.3362 - val_accuracy: 0.9016
Epoch 30/100
2/2 [==============================] - 0s 36ms/step - loss: 0.3841 - accuracy: 0.8719 - val_loss: 0.3326 - val_accuracy: 0.9016
Epoch 31/100
2/2 [==============================] - 0s 29ms/step - loss: 0.3775 - accuracy: 0.8686 - val_loss: 0.3292 - val_accuracy: 0.8984
Epoch 32/100
2/2 [==============================] - 0s 35ms/step - loss: 0.3760 - accuracy: 0.8752 - val_loss: 0.3264 - val_accuracy: 0.8951
Epoch 33/100
2/2 [==============================] - 0s 40ms/step - loss: 0.3754 - accuracy: 0.8604 - val_loss: 0.3241 - val_accuracy: 0.8951
Epoch 34/100
2/2 [==============================] - 0s 38ms/step - loss: 0.3718 - accuracy: 0.8621 - val_loss: 0.3216 - val_accuracy: 0.8984
Epoch 35/100
2/2 [==============================] - 0s 39ms/step - loss: 0.3710 - accuracy: 0.8670 - val_loss: 0.3199 - val_accuracy: 0.8984
Epoch 36/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3738 - accuracy: 0.8571 - val_loss: 0.3188 - val_accuracy: 0.8951
Epoch 37/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3692 - accuracy: 0.8637 - val_loss: 0.3172 - val_accuracy: 0.8951
Epoch 38/100
2/2 [==============================] - 0s 39ms/step - loss: 0.3710 - accuracy: 0.8637 - val_loss: 0.3150 - val_accuracy: 0.9016
Epoch 39/100
2/2 [==============================] - 0s 41ms/step - loss: 0.3656 - accuracy: 0.8654 - val_loss: 0.3131 - val_accuracy: 0.9016
Epoch 40/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3682 - accuracy: 0.8670 - val_loss: 0.3120 - val_accuracy: 0.9049
Epoch 41/100
2/2 [==============================] - 0s 49ms/step - loss: 0.3654 - accuracy: 0.8768 - val_loss: 0.3117 - val_accuracy: 0.9082
Epoch 42/100
2/2 [==============================] - 0s 39ms/step - loss: 0.3590 - accuracy: 0.8670 - val_loss: 0.3111 - val_accuracy: 0.9049
Epoch 43/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3580 - accuracy: 0.8703 - val_loss: 0.3098 - val_accuracy: 0.9049
Epoch 44/100
2/2 [==============================] - 0s 36ms/step - loss: 0.3562 - accuracy: 0.8703 - val_loss: 0.3087 - val_accuracy: 0.9016
Epoch 45/100
2/2 [==============================] - 0s 35ms/step - loss: 0.3611 - accuracy: 0.8621 - val_loss: 0.3080 - val_accuracy: 0.8951
Epoch 46/100
2/2 [==============================] - 0s 48ms/step - loss: 0.3583 - accuracy: 0.8752 - val_loss: 0.3072 - val_accuracy: 0.8885
Epoch 47/100
2/2 [==============================] - 0s 39ms/step - loss: 0.3637 - accuracy: 0.8588 - val_loss: 0.3069 - val_accuracy: 0.8918
Epoch 48/100
2/2 [==============================] - 0s 34ms/step - loss: 0.3530 - accuracy: 0.8637 - val_loss: 0.3068 - val_accuracy: 0.8951
Epoch 49/100
2/2 [==============================] - 0s 35ms/step - loss: 0.3515 - accuracy: 0.8719 - val_loss: 0.3072 - val_accuracy: 0.8984
Epoch 50/100
2/2 [==============================] - 0s 47ms/step - loss: 0.3568 - accuracy: 0.8637 - val_loss: 0.3078 - val_accuracy: 0.8984
Epoch 51/100
2/2 [==============================] - 0s 38ms/step - loss: 0.3495 - accuracy: 0.8736 - val_loss: 0.3077 - val_accuracy: 0.8984
Epoch 52/100
2/2 [==============================] - 0s 35ms/step - loss: 0.3523 - accuracy: 0.8621 - val_loss: 0.3068 - val_accuracy: 0.8984
Epoch 53/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3548 - accuracy: 0.8522 - val_loss: 0.3077 - val_accuracy: 0.9049
Epoch 54/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3544 - accuracy: 0.8604 - val_loss: 0.3092 - val_accuracy: 0.8984
Epoch 55/100
2/2 [==============================] - 0s 34ms/step - loss: 0.3538 - accuracy: 0.8637 - val_loss: 0.3092 - val_accuracy: 0.9049
Epoch 56/100
2/2 [==============================] - 0s 27ms/step - loss: 0.3429 - accuracy: 0.8654 - val_loss: 0.3082 - val_accuracy: 0.8984
Epoch 57/100
2/2 [==============================] - 0s 42ms/step - loss: 0.3471 - accuracy: 0.8637 - val_loss: 0.3058 - val_accuracy: 0.8984
Epoch 58/100
2/2 [==============================] - 0s 32ms/step - loss: 0.3407 - accuracy: 0.8785 - val_loss: 0.3035 - val_accuracy: 0.9016
Epoch 59/100
2/2 [==============================] - 0s 40ms/step - loss: 0.3328 - accuracy: 0.8768 - val_loss: 0.3017 - val_accuracy: 0.9049
Epoch 60/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3393 - accuracy: 0.8785 - val_loss: 0.3006 - val_accuracy: 0.9016
Epoch 61/100
2/2 [==============================] - 0s 44ms/step - loss: 0.3435 - accuracy: 0.8621 - val_loss: 0.3002 - val_accuracy: 0.9016
Epoch 62/100
2/2 [==============================] - 0s 36ms/step - loss: 0.3318 - accuracy: 0.8801 - val_loss: 0.2999 - val_accuracy: 0.8984
Epoch 63/100
2/2 [==============================] - 0s 34ms/step - loss: 0.3449 - accuracy: 0.8736 - val_loss: 0.2994 - val_accuracy: 0.9016
Epoch 64/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3368 - accuracy: 0.8801 - val_loss: 0.3004 - val_accuracy: 0.9016
Epoch 65/100
2/2 [==============================] - 0s 34ms/step - loss: 0.3425 - accuracy: 0.8785 - val_loss: 0.3015 - val_accuracy: 0.9016
Epoch 66/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3399 - accuracy: 0.8686 - val_loss: 0.3016 - val_accuracy: 0.8951
Epoch 67/100
2/2 [==============================] - 0s 38ms/step - loss: 0.3391 - accuracy: 0.8752 - val_loss: 0.3030 - val_accuracy: 0.8951
Epoch 68/100
2/2 [==============================] - 0s 32ms/step - loss: 0.3292 - accuracy: 0.8752 - val_loss: 0.3046 - val_accuracy: 0.8918
Epoch 69/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3357 - accuracy: 0.8670 - val_loss: 0.3060 - val_accuracy: 0.8918
Epoch 70/100
2/2 [==============================] - 0s 36ms/step - loss: 0.3353 - accuracy: 0.8736 - val_loss: 0.3042 - val_accuracy: 0.8885
Epoch 71/100
2/2 [==============================] - 0s 39ms/step - loss: 0.3438 - accuracy: 0.8621 - val_loss: 0.3024 - val_accuracy: 0.8951
Epoch 72/100
2/2 [==============================] - 0s 37ms/step - loss: 0.3262 - accuracy: 0.8654 - val_loss: 0.3017 - val_accuracy: 0.8951
Epoch 73/100
1/2 [==============>...............] - ETA: 0s - loss: 0.3200 - accuracy: 0.8926Restoring model weights from the end of the best epoch: 63.
2/2 [==============================] - 0s 37ms/step - loss: 0.3374 - accuracy: 0.8785 - val_loss: 0.3020 - val_accuracy: 0.8951
Epoch 73: early stopping
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No description has been provided for this image 
10/10 [==============================] - 0s 3ms/step
Model parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 32, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'momentum': None, 'adam_beta_1': 0.9, 'adam_beta_2': 0.999, 'rho': None, 'batch_norm': False, 'initializers': 'random_normal'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 218ms/step - loss: 1.1603 - accuracy: 0.3951 - val_loss: 0.9750 - val_accuracy: 0.8553
Epoch 2/100
2/2 [==============================] - 0s 36ms/step - loss: 0.9786 - accuracy: 0.8344 - val_loss: 0.8203 - val_accuracy: 0.8618
Epoch 3/100
2/2 [==============================] - 0s 44ms/step - loss: 0.8358 - accuracy: 0.8443 - val_loss: 0.7001 - val_accuracy: 0.8618
Epoch 4/100
2/2 [==============================] - 0s 34ms/step - loss: 0.7176 - accuracy: 0.8443 - val_loss: 0.6125 - val_accuracy: 0.8618
Epoch 5/100
2/2 [==============================] - 0s 52ms/step - loss: 0.6313 - accuracy: 0.8443 - val_loss: 0.5543 - val_accuracy: 0.8618
Epoch 6/100
2/2 [==============================] - 0s 37ms/step - loss: 0.5620 - accuracy: 0.8443 - val_loss: 0.5198 - val_accuracy: 0.8618
Epoch 7/100
2/2 [==============================] - 0s 34ms/step - loss: 0.5231 - accuracy: 0.8443 - val_loss: 0.5001 - val_accuracy: 0.8618
Epoch 8/100
2/2 [==============================] - 0s 44ms/step - loss: 0.4864 - accuracy: 0.8459 - val_loss: 0.4892 - val_accuracy: 0.8651
Epoch 9/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4681 - accuracy: 0.8459 - val_loss: 0.4831 - val_accuracy: 0.8651
Epoch 10/100
2/2 [==============================] - 0s 39ms/step - loss: 0.4462 - accuracy: 0.8639 - val_loss: 0.4805 - val_accuracy: 0.8586
Epoch 11/100
2/2 [==============================] - 0s 50ms/step - loss: 0.4332 - accuracy: 0.8754 - val_loss: 0.4805 - val_accuracy: 0.8520
Epoch 12/100
2/2 [==============================] - 0s 44ms/step - loss: 0.4274 - accuracy: 0.8754 - val_loss: 0.4837 - val_accuracy: 0.8355
Epoch 13/100
2/2 [==============================] - 0s 31ms/step - loss: 0.4178 - accuracy: 0.8705 - val_loss: 0.4878 - val_accuracy: 0.8322
Epoch 14/100
2/2 [==============================] - 0s 33ms/step - loss: 0.4129 - accuracy: 0.8705 - val_loss: 0.4893 - val_accuracy: 0.8322
Epoch 15/100
2/2 [==============================] - 0s 37ms/step - loss: 0.4011 - accuracy: 0.8672 - val_loss: 0.4888 - val_accuracy: 0.8322
Epoch 16/100
2/2 [==============================] - 0s 42ms/step - loss: 0.4049 - accuracy: 0.8820 - val_loss: 0.4876 - val_accuracy: 0.8388
Epoch 17/100
2/2 [==============================] - 0s 44ms/step - loss: 0.3966 - accuracy: 0.8787 - val_loss: 0.4864 - val_accuracy: 0.8388
Epoch 18/100
2/2 [==============================] - 0s 43ms/step - loss: 0.3881 - accuracy: 0.8803 - val_loss: 0.4849 - val_accuracy: 0.8421
Epoch 19/100
2/2 [==============================] - 0s 34ms/step - loss: 0.3853 - accuracy: 0.8721 - val_loss: 0.4837 - val_accuracy: 0.8454
Epoch 20/100
1/2 [==============>...............] - ETA: 0s - loss: 0.3856 - accuracy: 0.8691Restoring model weights from the end of the best epoch: 10.
2/2 [==============================] - 0s 32ms/step - loss: 0.3783 - accuracy: 0.8705 - val_loss: 0.4816 - val_accuracy: 0.8454
Epoch 20: early stopping
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No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 8
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 222ms/step - loss: 3.7834 - accuracy: 0.5238 - val_loss: 3.2629 - val_accuracy: 0.8098
Epoch 2/100
2/2 [==============================] - 0s 38ms/step - loss: 3.1419 - accuracy: 0.7997 - val_loss: 2.3975 - val_accuracy: 0.8164
Epoch 3/100
2/2 [==============================] - 0s 38ms/step - loss: 2.2361 - accuracy: 0.8670 - val_loss: 1.5207 - val_accuracy: 0.8164
Epoch 4/100
2/2 [==============================] - 0s 40ms/step - loss: 1.3640 - accuracy: 0.8670 - val_loss: 0.8739 - val_accuracy: 0.8164
Epoch 5/100
2/2 [==============================] - 0s 24ms/step - loss: 0.7794 - accuracy: 0.8670 - val_loss: 0.9126 - val_accuracy: 0.8164
Epoch 6/100
2/2 [==============================] - 0s 33ms/step - loss: 0.8676 - accuracy: 0.8670 - val_loss: 1.7115 - val_accuracy: 0.8164
Epoch 7/100
2/2 [==============================] - 0s 33ms/step - loss: 1.6138 - accuracy: 0.8670 - val_loss: 2.6618 - val_accuracy: 0.8164
Epoch 8/100
2/2 [==============================] - 0s 32ms/step - loss: 2.4895 - accuracy: 0.8670 - val_loss: 3.2997 - val_accuracy: 0.8164
Epoch 9/100
2/2 [==============================] - 0s 37ms/step - loss: 3.0857 - accuracy: 0.8670 - val_loss: 3.4463 - val_accuracy: 0.8164
Epoch 10/100
2/2 [==============================] - 0s 50ms/step - loss: 3.2183 - accuracy: 0.8670 - val_loss: 3.1312 - val_accuracy: 0.8164
Epoch 11/100
2/2 [==============================] - 0s 42ms/step - loss: 2.9442 - accuracy: 0.8637 - val_loss: 2.5147 - val_accuracy: 0.8459
Epoch 12/100
2/2 [==============================] - 0s 46ms/step - loss: 2.4147 - accuracy: 0.8489 - val_loss: 1.8559 - val_accuracy: 0.8393
Epoch 13/100
2/2 [==============================] - 0s 35ms/step - loss: 1.8566 - accuracy: 0.7635 - val_loss: 1.3013 - val_accuracy: 0.8328
Epoch 14/100
1/2 [==============>...............] - ETA: 0s - loss: 1.2787 - accuracy: 0.7949Restoring model weights from the end of the best epoch: 4.
2/2 [==============================] - 0s 53ms/step - loss: 1.2399 - accuracy: 0.8030 - val_loss: 1.1847 - val_accuracy: 0.8164
Epoch 14: early stopping
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No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
2/2 [==============================] - 1s 228ms/step - loss: 3.8932 - accuracy: 0.3153 - val_loss: 3.1413 - val_accuracy: 0.8098
Epoch 2/100
2/2 [==============================] - 0s 34ms/step - loss: 3.1123 - accuracy: 0.7340 - val_loss: 2.1650 - val_accuracy: 0.8721
Epoch 3/100
2/2 [==============================] - 0s 50ms/step - loss: 2.1523 - accuracy: 0.8391 - val_loss: 1.3339 - val_accuracy: 0.8721
Epoch 4/100
2/2 [==============================] - 0s 48ms/step - loss: 1.3555 - accuracy: 0.8391 - val_loss: 0.7390 - val_accuracy: 0.8721
Epoch 5/100
2/2 [==============================] - 0s 42ms/step - loss: 0.8116 - accuracy: 0.8391 - val_loss: 0.7856 - val_accuracy: 0.8721
Epoch 6/100
2/2 [==============================] - 0s 35ms/step - loss: 0.9624 - accuracy: 0.8391 - val_loss: 1.5070 - val_accuracy: 0.8721
Epoch 7/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7450 - accuracy: 0.8391 - val_loss: 2.3029 - val_accuracy: 0.8721
Epoch 8/100
2/2 [==============================] - 0s 47ms/step - loss: 2.5260 - accuracy: 0.8391 - val_loss: 2.7945 - val_accuracy: 0.8721
Epoch 9/100
2/2 [==============================] - 0s 48ms/step - loss: 2.9953 - accuracy: 0.8391 - val_loss: 2.8746 - val_accuracy: 0.8721
Epoch 10/100
2/2 [==============================] - 0s 54ms/step - loss: 3.0174 - accuracy: 0.8391 - val_loss: 2.5921 - val_accuracy: 0.8721
Epoch 11/100
2/2 [==============================] - 0s 41ms/step - loss: 2.7174 - accuracy: 0.8440 - val_loss: 2.1061 - val_accuracy: 0.8984
Epoch 12/100
2/2 [==============================] - 0s 31ms/step - loss: 2.2703 - accuracy: 0.8128 - val_loss: 1.6099 - val_accuracy: 0.8557
Epoch 13/100
2/2 [==============================] - 0s 43ms/step - loss: 1.7254 - accuracy: 0.7767 - val_loss: 1.1848 - val_accuracy: 0.8689
Epoch 14/100
1/2 [==============>...............] - ETA: 0s - loss: 1.3559 - accuracy: 0.7637Restoring model weights from the end of the best epoch: 4.
2/2 [==============================] - 0s 29ms/step - loss: 1.3357 - accuracy: 0.7685 - val_loss: 1.0574 - val_accuracy: 0.8557
Epoch 14: early stopping
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No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.1, 'hidden_layers': 3, 'hidden_units': 64, 'learning_rate_decay': 0.001, 'optimizer': 'momentum', 'l1': 0.01, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.999, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 512
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
2/2 [==============================] - 1s 215ms/step - loss: 4.0263 - accuracy: 0.2164 - val_loss: 3.1470 - val_accuracy: 0.8421
Epoch 2/100
2/2 [==============================] - 0s 33ms/step - loss: 3.1351 - accuracy: 0.7246 - val_loss: 2.1474 - val_accuracy: 0.8618
Epoch 3/100
2/2 [==============================] - 0s 40ms/step - loss: 2.1351 - accuracy: 0.8443 - val_loss: 1.3807 - val_accuracy: 0.8618
Epoch 4/100
2/2 [==============================] - 0s 42ms/step - loss: 1.3340 - accuracy: 0.8443 - val_loss: 0.8672 - val_accuracy: 0.8618
Epoch 5/100
2/2 [==============================] - 0s 49ms/step - loss: 0.8592 - accuracy: 0.8443 - val_loss: 1.0006 - val_accuracy: 0.8618
Epoch 6/100
2/2 [==============================] - 0s 25ms/step - loss: 1.0337 - accuracy: 0.8443 - val_loss: 1.7459 - val_accuracy: 0.8618
Epoch 7/100
2/2 [==============================] - 0s 33ms/step - loss: 1.8376 - accuracy: 0.8443 - val_loss: 2.5699 - val_accuracy: 0.8618
Epoch 8/100
2/2 [==============================] - 0s 36ms/step - loss: 2.6380 - accuracy: 0.8443 - val_loss: 3.1060 - val_accuracy: 0.8618
Epoch 9/100
2/2 [==============================] - 0s 46ms/step - loss: 3.1408 - accuracy: 0.8443 - val_loss: 3.2225 - val_accuracy: 0.8618
Epoch 10/100
2/2 [==============================] - 0s 28ms/step - loss: 3.1483 - accuracy: 0.8426 - val_loss: 2.9554 - val_accuracy: 0.8355
Epoch 11/100
2/2 [==============================] - 0s 33ms/step - loss: 2.8294 - accuracy: 0.8607 - val_loss: 2.4664 - val_accuracy: 0.8026
Epoch 12/100
2/2 [==============================] - 0s 30ms/step - loss: 2.3327 - accuracy: 0.8262 - val_loss: 1.8589 - val_accuracy: 0.7632
Epoch 13/100
2/2 [==============================] - 0s 37ms/step - loss: 1.7770 - accuracy: 0.7984 - val_loss: 1.3191 - val_accuracy: 0.7993
Epoch 14/100
1/2 [==============>...............] - ETA: 0s - loss: 1.3991 - accuracy: 0.7695Restoring model weights from the end of the best epoch: 4.
2/2 [==============================] - 0s 49ms/step - loss: 1.3671 - accuracy: 0.7770 - val_loss: 1.2359 - val_accuracy: 0.8487
Epoch 14: early stopping
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No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 9
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'he_normal'}
Batch size: 256
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
3/3 [==============================] - 1s 108ms/step - loss: 5.5924 - accuracy: 0.1888 - val_loss: 5.5781 - val_accuracy: 0.1770
Epoch 2/100
3/3 [==============================] - 0s 22ms/step - loss: 5.6184 - accuracy: 0.1560 - val_loss: 5.5731 - val_accuracy: 0.1803
Epoch 3/100
3/3 [==============================] - 0s 23ms/step - loss: 5.5790 - accuracy: 0.1888 - val_loss: 5.5653 - val_accuracy: 0.1803
Epoch 4/100
3/3 [==============================] - 0s 14ms/step - loss: 5.5934 - accuracy: 0.1905 - val_loss: 5.5547 - val_accuracy: 0.1902
Epoch 5/100
3/3 [==============================] - 0s 25ms/step - loss: 5.5874 - accuracy: 0.1675 - val_loss: 5.5415 - val_accuracy: 0.1967
Epoch 6/100
3/3 [==============================] - 0s 25ms/step - loss: 5.5517 - accuracy: 0.1872 - val_loss: 5.5258 - val_accuracy: 0.2033
Epoch 7/100
3/3 [==============================] - 0s 26ms/step - loss: 5.5348 - accuracy: 0.1954 - val_loss: 5.5076 - val_accuracy: 0.2033
Epoch 8/100
3/3 [==============================] - 0s 23ms/step - loss: 5.4883 - accuracy: 0.2282 - val_loss: 5.4872 - val_accuracy: 0.2098
Epoch 9/100
3/3 [==============================] - 0s 26ms/step - loss: 5.4924 - accuracy: 0.2233 - val_loss: 5.4646 - val_accuracy: 0.2098
Epoch 10/100
3/3 [==============================] - 0s 25ms/step - loss: 5.4628 - accuracy: 0.2167 - val_loss: 5.4399 - val_accuracy: 0.2131
Epoch 11/100
3/3 [==============================] - 0s 25ms/step - loss: 5.4407 - accuracy: 0.2365 - val_loss: 5.4134 - val_accuracy: 0.2262
Epoch 12/100
3/3 [==============================] - 0s 25ms/step - loss: 5.4126 - accuracy: 0.2250 - val_loss: 5.3850 - val_accuracy: 0.2393
Epoch 13/100
3/3 [==============================] - 0s 24ms/step - loss: 5.3966 - accuracy: 0.2250 - val_loss: 5.3550 - val_accuracy: 0.2557
Epoch 14/100
3/3 [==============================] - 0s 22ms/step - loss: 5.3547 - accuracy: 0.2726 - val_loss: 5.3234 - val_accuracy: 0.2656
Epoch 15/100
3/3 [==============================] - 0s 25ms/step - loss: 5.3082 - accuracy: 0.2496 - val_loss: 5.2903 - val_accuracy: 0.2787
Epoch 16/100
3/3 [==============================] - 0s 21ms/step - loss: 5.2898 - accuracy: 0.2693 - val_loss: 5.2558 - val_accuracy: 0.2984
Epoch 17/100
3/3 [==============================] - 0s 25ms/step - loss: 5.2572 - accuracy: 0.2989 - val_loss: 5.2199 - val_accuracy: 0.3311
Epoch 18/100
3/3 [==============================] - 0s 24ms/step - loss: 5.1942 - accuracy: 0.3366 - val_loss: 5.1827 - val_accuracy: 0.3443
Epoch 19/100
3/3 [==============================] - 0s 25ms/step - loss: 5.1914 - accuracy: 0.3186 - val_loss: 5.1442 - val_accuracy: 0.3639
Epoch 20/100
3/3 [==============================] - 0s 25ms/step - loss: 5.1296 - accuracy: 0.3432 - val_loss: 5.1046 - val_accuracy: 0.3836
Epoch 21/100
3/3 [==============================] - 0s 27ms/step - loss: 5.1071 - accuracy: 0.3498 - val_loss: 5.0640 - val_accuracy: 0.4295
Epoch 22/100
3/3 [==============================] - 0s 23ms/step - loss: 5.0377 - accuracy: 0.4056 - val_loss: 5.0227 - val_accuracy: 0.4557
Epoch 23/100
3/3 [==============================] - 0s 18ms/step - loss: 5.0049 - accuracy: 0.4286 - val_loss: 4.9805 - val_accuracy: 0.4721
Epoch 24/100
3/3 [==============================] - 0s 16ms/step - loss: 4.9718 - accuracy: 0.4335 - val_loss: 4.9376 - val_accuracy: 0.5049
Epoch 25/100
3/3 [==============================] - 0s 21ms/step - loss: 4.9225 - accuracy: 0.4548 - val_loss: 4.8944 - val_accuracy: 0.5311
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 4.8695 - accuracy: 0.4926 - val_loss: 4.8509 - val_accuracy: 0.5377
Epoch 27/100
3/3 [==============================] - 0s 21ms/step - loss: 4.8418 - accuracy: 0.4844 - val_loss: 4.8069 - val_accuracy: 0.5738
Epoch 28/100
3/3 [==============================] - 0s 16ms/step - loss: 4.8007 - accuracy: 0.5057 - val_loss: 4.7624 - val_accuracy: 0.5967
Epoch 29/100
3/3 [==============================] - 0s 16ms/step - loss: 4.7466 - accuracy: 0.5649 - val_loss: 4.7178 - val_accuracy: 0.6262
Epoch 30/100
3/3 [==============================] - 0s 16ms/step - loss: 4.6805 - accuracy: 0.5632 - val_loss: 4.6733 - val_accuracy: 0.6295
Epoch 31/100
3/3 [==============================] - 0s 17ms/step - loss: 4.6493 - accuracy: 0.5829 - val_loss: 4.6283 - val_accuracy: 0.6557
Epoch 32/100
3/3 [==============================] - 0s 17ms/step - loss: 4.6072 - accuracy: 0.6108 - val_loss: 4.5828 - val_accuracy: 0.6590
Epoch 33/100
3/3 [==============================] - 0s 21ms/step - loss: 4.5539 - accuracy: 0.6240 - val_loss: 4.5369 - val_accuracy: 0.6689
Epoch 34/100
3/3 [==============================] - 0s 26ms/step - loss: 4.5034 - accuracy: 0.6700 - val_loss: 4.4909 - val_accuracy: 0.6787
Epoch 35/100
3/3 [==============================] - 0s 21ms/step - loss: 4.4591 - accuracy: 0.6667 - val_loss: 4.4449 - val_accuracy: 0.6885
Epoch 36/100
3/3 [==============================] - 0s 22ms/step - loss: 4.4033 - accuracy: 0.6929 - val_loss: 4.3990 - val_accuracy: 0.7082
Epoch 37/100
3/3 [==============================] - 0s 15ms/step - loss: 4.3647 - accuracy: 0.6749 - val_loss: 4.3535 - val_accuracy: 0.7213
Epoch 38/100
3/3 [==============================] - 0s 15ms/step - loss: 4.3260 - accuracy: 0.7061 - val_loss: 4.3083 - val_accuracy: 0.7279
Epoch 39/100
3/3 [==============================] - 0s 24ms/step - loss: 4.2770 - accuracy: 0.7176 - val_loss: 4.2627 - val_accuracy: 0.7344
Epoch 40/100
3/3 [==============================] - 0s 18ms/step - loss: 4.2051 - accuracy: 0.7603 - val_loss: 4.2170 - val_accuracy: 0.7377
Epoch 41/100
3/3 [==============================] - 0s 25ms/step - loss: 4.1743 - accuracy: 0.7586 - val_loss: 4.1710 - val_accuracy: 0.7443
Epoch 42/100
3/3 [==============================] - 0s 24ms/step - loss: 4.1193 - accuracy: 0.7718 - val_loss: 4.1251 - val_accuracy: 0.7508
Epoch 43/100
3/3 [==============================] - 0s 26ms/step - loss: 4.0729 - accuracy: 0.7915 - val_loss: 4.0792 - val_accuracy: 0.7508
Epoch 44/100
3/3 [==============================] - 0s 18ms/step - loss: 4.0455 - accuracy: 0.7701 - val_loss: 4.0331 - val_accuracy: 0.7574
Epoch 45/100
3/3 [==============================] - 0s 25ms/step - loss: 3.9845 - accuracy: 0.7964 - val_loss: 3.9874 - val_accuracy: 0.7672
Epoch 46/100
3/3 [==============================] - 0s 16ms/step - loss: 3.9277 - accuracy: 0.8128 - val_loss: 3.9422 - val_accuracy: 0.7705
Epoch 47/100
3/3 [==============================] - 0s 16ms/step - loss: 3.8803 - accuracy: 0.8259 - val_loss: 3.8971 - val_accuracy: 0.7639
Epoch 48/100
3/3 [==============================] - 0s 24ms/step - loss: 3.8406 - accuracy: 0.8227 - val_loss: 3.8527 - val_accuracy: 0.7705
Epoch 49/100
3/3 [==============================] - 0s 24ms/step - loss: 3.8056 - accuracy: 0.8243 - val_loss: 3.8093 - val_accuracy: 0.7705
Epoch 50/100
3/3 [==============================] - 0s 15ms/step - loss: 3.7491 - accuracy: 0.8358 - val_loss: 3.7661 - val_accuracy: 0.7803
Epoch 51/100
3/3 [==============================] - 0s 17ms/step - loss: 3.7227 - accuracy: 0.8374 - val_loss: 3.7230 - val_accuracy: 0.7902
Epoch 52/100
3/3 [==============================] - 0s 16ms/step - loss: 3.6567 - accuracy: 0.8456 - val_loss: 3.6799 - val_accuracy: 0.8131
Epoch 53/100
3/3 [==============================] - 0s 16ms/step - loss: 3.6183 - accuracy: 0.8374 - val_loss: 3.6368 - val_accuracy: 0.8131
Epoch 54/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5829 - accuracy: 0.8407 - val_loss: 3.5936 - val_accuracy: 0.8164
Epoch 55/100
3/3 [==============================] - 0s 20ms/step - loss: 3.5271 - accuracy: 0.8555 - val_loss: 3.5513 - val_accuracy: 0.8164
Epoch 56/100
3/3 [==============================] - 0s 15ms/step - loss: 3.4790 - accuracy: 0.8539 - val_loss: 3.5095 - val_accuracy: 0.8230
Epoch 57/100
3/3 [==============================] - 0s 17ms/step - loss: 3.4357 - accuracy: 0.8621 - val_loss: 3.4677 - val_accuracy: 0.8197
Epoch 58/100
3/3 [==============================] - 0s 18ms/step - loss: 3.4002 - accuracy: 0.8473 - val_loss: 3.4262 - val_accuracy: 0.8164
Epoch 59/100
3/3 [==============================] - 0s 17ms/step - loss: 3.3565 - accuracy: 0.8654 - val_loss: 3.3848 - val_accuracy: 0.8164
Epoch 60/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3097 - accuracy: 0.8654 - val_loss: 3.3443 - val_accuracy: 0.8164
Epoch 61/100
3/3 [==============================] - 0s 25ms/step - loss: 3.2572 - accuracy: 0.8621 - val_loss: 3.3042 - val_accuracy: 0.8164
Epoch 62/100
3/3 [==============================] - 0s 25ms/step - loss: 3.2431 - accuracy: 0.8654 - val_loss: 3.2644 - val_accuracy: 0.8164
Epoch 63/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1891 - accuracy: 0.8670 - val_loss: 3.2245 - val_accuracy: 0.8164
Epoch 64/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1601 - accuracy: 0.8654 - val_loss: 3.1846 - val_accuracy: 0.8164
Epoch 65/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1036 - accuracy: 0.8654 - val_loss: 3.1455 - val_accuracy: 0.8164
Epoch 66/100
3/3 [==============================] - 0s 26ms/step - loss: 3.0663 - accuracy: 0.8670 - val_loss: 3.1065 - val_accuracy: 0.8164
Epoch 67/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0261 - accuracy: 0.8670 - val_loss: 3.0673 - val_accuracy: 0.8164
Epoch 68/100
3/3 [==============================] - 0s 26ms/step - loss: 2.9878 - accuracy: 0.8670 - val_loss: 3.0287 - val_accuracy: 0.8164
Epoch 69/100
3/3 [==============================] - 0s 18ms/step - loss: 2.9489 - accuracy: 0.8670 - val_loss: 2.9908 - val_accuracy: 0.8164
Epoch 70/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9136 - accuracy: 0.8670 - val_loss: 2.9535 - val_accuracy: 0.8164
Epoch 71/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8724 - accuracy: 0.8670 - val_loss: 2.9171 - val_accuracy: 0.8164
Epoch 72/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8320 - accuracy: 0.8670 - val_loss: 2.8810 - val_accuracy: 0.8164
Epoch 73/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8037 - accuracy: 0.8670 - val_loss: 2.8448 - val_accuracy: 0.8164
Epoch 74/100
3/3 [==============================] - 0s 17ms/step - loss: 2.7732 - accuracy: 0.8670 - val_loss: 2.8088 - val_accuracy: 0.8164
Epoch 75/100
3/3 [==============================] - 0s 26ms/step - loss: 2.7383 - accuracy: 0.8654 - val_loss: 2.7730 - val_accuracy: 0.8164
Epoch 76/100
3/3 [==============================] - 0s 24ms/step - loss: 2.6948 - accuracy: 0.8670 - val_loss: 2.7367 - val_accuracy: 0.8164
Epoch 77/100
3/3 [==============================] - 0s 17ms/step - loss: 2.6467 - accuracy: 0.8670 - val_loss: 2.7001 - val_accuracy: 0.8164
Epoch 78/100
3/3 [==============================] - 0s 25ms/step - loss: 2.6092 - accuracy: 0.8670 - val_loss: 2.6639 - val_accuracy: 0.8164
Epoch 79/100
3/3 [==============================] - 0s 23ms/step - loss: 2.5659 - accuracy: 0.8670 - val_loss: 2.6283 - val_accuracy: 0.8164
Epoch 80/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5392 - accuracy: 0.8670 - val_loss: 2.5928 - val_accuracy: 0.8164
Epoch 81/100
3/3 [==============================] - 0s 20ms/step - loss: 2.5119 - accuracy: 0.8670 - val_loss: 2.5576 - val_accuracy: 0.8164
Epoch 82/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4652 - accuracy: 0.8670 - val_loss: 2.5224 - val_accuracy: 0.8164
Epoch 83/100
3/3 [==============================] - 0s 19ms/step - loss: 2.4273 - accuracy: 0.8670 - val_loss: 2.4867 - val_accuracy: 0.8164
Epoch 84/100
3/3 [==============================] - 0s 20ms/step - loss: 2.4016 - accuracy: 0.8670 - val_loss: 2.4516 - val_accuracy: 0.8164
Epoch 85/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3620 - accuracy: 0.8670 - val_loss: 2.4166 - val_accuracy: 0.8164
Epoch 86/100
3/3 [==============================] - 0s 22ms/step - loss: 2.3348 - accuracy: 0.8670 - val_loss: 2.3830 - val_accuracy: 0.8164
Epoch 87/100
3/3 [==============================] - 0s 22ms/step - loss: 2.2987 - accuracy: 0.8670 - val_loss: 2.3502 - val_accuracy: 0.8164
Epoch 88/100
3/3 [==============================] - 0s 18ms/step - loss: 2.2587 - accuracy: 0.8670 - val_loss: 2.3179 - val_accuracy: 0.8164
Epoch 89/100
3/3 [==============================] - 0s 21ms/step - loss: 2.2330 - accuracy: 0.8670 - val_loss: 2.2852 - val_accuracy: 0.8164
Epoch 90/100
3/3 [==============================] - 0s 18ms/step - loss: 2.1948 - accuracy: 0.8670 - val_loss: 2.2522 - val_accuracy: 0.8164
Epoch 91/100
3/3 [==============================] - 0s 21ms/step - loss: 2.1597 - accuracy: 0.8670 - val_loss: 2.2200 - val_accuracy: 0.8164
Epoch 92/100
3/3 [==============================] - 0s 20ms/step - loss: 2.1260 - accuracy: 0.8670 - val_loss: 2.1885 - val_accuracy: 0.8164
Epoch 93/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0968 - accuracy: 0.8670 - val_loss: 2.1581 - val_accuracy: 0.8164
Epoch 94/100
3/3 [==============================] - 0s 22ms/step - loss: 2.0729 - accuracy: 0.8670 - val_loss: 2.1277 - val_accuracy: 0.8164
Epoch 95/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0417 - accuracy: 0.8670 - val_loss: 2.0976 - val_accuracy: 0.8164
Epoch 96/100
3/3 [==============================] - 0s 20ms/step - loss: 2.0158 - accuracy: 0.8670 - val_loss: 2.0671 - val_accuracy: 0.8164
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9825 - accuracy: 0.8670 - val_loss: 2.0364 - val_accuracy: 0.8164
Epoch 98/100
3/3 [==============================] - 0s 18ms/step - loss: 1.9472 - accuracy: 0.8670 - val_loss: 2.0056 - val_accuracy: 0.8164
Epoch 99/100
3/3 [==============================] - 0s 21ms/step - loss: 1.9137 - accuracy: 0.8670 - val_loss: 1.9749 - val_accuracy: 0.8164
Epoch 100/100
3/3 [==============================] - 0s 20ms/step - loss: 1.8832 - accuracy: 0.8670 - val_loss: 1.9448 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'he_normal'}
Batch size: 256
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
3/3 [==============================] - 1s 117ms/step - loss: 6.0112 - accuracy: 0.2299 - val_loss: 5.8791 - val_accuracy: 0.2623
Epoch 2/100
3/3 [==============================] - 0s 26ms/step - loss: 6.0593 - accuracy: 0.2562 - val_loss: 5.8719 - val_accuracy: 0.2623
Epoch 3/100
3/3 [==============================] - 0s 26ms/step - loss: 6.0118 - accuracy: 0.2693 - val_loss: 5.8605 - val_accuracy: 0.2656
Epoch 4/100
3/3 [==============================] - 0s 16ms/step - loss: 6.0296 - accuracy: 0.2594 - val_loss: 5.8449 - val_accuracy: 0.2689
Epoch 5/100
3/3 [==============================] - 0s 17ms/step - loss: 5.9923 - accuracy: 0.2479 - val_loss: 5.8255 - val_accuracy: 0.2721
Epoch 6/100
3/3 [==============================] - 0s 17ms/step - loss: 5.9512 - accuracy: 0.2627 - val_loss: 5.8025 - val_accuracy: 0.2754
Epoch 7/100
3/3 [==============================] - 0s 16ms/step - loss: 5.9487 - accuracy: 0.2923 - val_loss: 5.7759 - val_accuracy: 0.2787
Epoch 8/100
3/3 [==============================] - 0s 16ms/step - loss: 5.9239 - accuracy: 0.2759 - val_loss: 5.7462 - val_accuracy: 0.2820
Epoch 9/100
3/3 [==============================] - 0s 23ms/step - loss: 5.8632 - accuracy: 0.2956 - val_loss: 5.7133 - val_accuracy: 0.2852
Epoch 10/100
3/3 [==============================] - 0s 21ms/step - loss: 5.8837 - accuracy: 0.2726 - val_loss: 5.6775 - val_accuracy: 0.2951
Epoch 11/100
3/3 [==============================] - 0s 20ms/step - loss: 5.8302 - accuracy: 0.2824 - val_loss: 5.6389 - val_accuracy: 0.3016
Epoch 12/100
3/3 [==============================] - 0s 16ms/step - loss: 5.7694 - accuracy: 0.2972 - val_loss: 5.5978 - val_accuracy: 0.3115
Epoch 13/100
3/3 [==============================] - 0s 22ms/step - loss: 5.7780 - accuracy: 0.2939 - val_loss: 5.5545 - val_accuracy: 0.3180
Epoch 14/100
3/3 [==============================] - 0s 22ms/step - loss: 5.6996 - accuracy: 0.3103 - val_loss: 5.5093 - val_accuracy: 0.3377
Epoch 15/100
3/3 [==============================] - 0s 23ms/step - loss: 5.6266 - accuracy: 0.3235 - val_loss: 5.4622 - val_accuracy: 0.3574
Epoch 16/100
3/3 [==============================] - 0s 25ms/step - loss: 5.6169 - accuracy: 0.3317 - val_loss: 5.4133 - val_accuracy: 0.3803
Epoch 17/100
3/3 [==============================] - 0s 21ms/step - loss: 5.5146 - accuracy: 0.3563 - val_loss: 5.3628 - val_accuracy: 0.3967
Epoch 18/100
3/3 [==============================] - 0s 22ms/step - loss: 5.4988 - accuracy: 0.4039 - val_loss: 5.3107 - val_accuracy: 0.4131
Epoch 19/100
3/3 [==============================] - 0s 23ms/step - loss: 5.4450 - accuracy: 0.3941 - val_loss: 5.2574 - val_accuracy: 0.4230
Epoch 20/100
3/3 [==============================] - 0s 22ms/step - loss: 5.3718 - accuracy: 0.4007 - val_loss: 5.2033 - val_accuracy: 0.4393
Epoch 21/100
3/3 [==============================] - 0s 24ms/step - loss: 5.3135 - accuracy: 0.4286 - val_loss: 5.1486 - val_accuracy: 0.4721
Epoch 22/100
3/3 [==============================] - 0s 25ms/step - loss: 5.2279 - accuracy: 0.4236 - val_loss: 5.0933 - val_accuracy: 0.4852
Epoch 23/100
3/3 [==============================] - 0s 22ms/step - loss: 5.2291 - accuracy: 0.4253 - val_loss: 5.0373 - val_accuracy: 0.5148
Epoch 24/100
3/3 [==============================] - 0s 19ms/step - loss: 5.1561 - accuracy: 0.4450 - val_loss: 4.9807 - val_accuracy: 0.5311
Epoch 25/100
3/3 [==============================] - 0s 27ms/step - loss: 5.0791 - accuracy: 0.4713 - val_loss: 4.9238 - val_accuracy: 0.5574
Epoch 26/100
3/3 [==============================] - 0s 19ms/step - loss: 5.0334 - accuracy: 0.5123 - val_loss: 4.8666 - val_accuracy: 0.5836
Epoch 27/100
3/3 [==============================] - 0s 28ms/step - loss: 4.9698 - accuracy: 0.5205 - val_loss: 4.8092 - val_accuracy: 0.6197
Epoch 28/100
3/3 [==============================] - 0s 23ms/step - loss: 4.9166 - accuracy: 0.5484 - val_loss: 4.7518 - val_accuracy: 0.6525
Epoch 29/100
3/3 [==============================] - 0s 25ms/step - loss: 4.8882 - accuracy: 0.5649 - val_loss: 4.6943 - val_accuracy: 0.6951
Epoch 30/100
3/3 [==============================] - 0s 28ms/step - loss: 4.8152 - accuracy: 0.5846 - val_loss: 4.6374 - val_accuracy: 0.7016
Epoch 31/100
3/3 [==============================] - 0s 18ms/step - loss: 4.7342 - accuracy: 0.5977 - val_loss: 4.5813 - val_accuracy: 0.7246
Epoch 32/100
3/3 [==============================] - 0s 24ms/step - loss: 4.6836 - accuracy: 0.6256 - val_loss: 4.5255 - val_accuracy: 0.7311
Epoch 33/100
3/3 [==============================] - 0s 26ms/step - loss: 4.6390 - accuracy: 0.6174 - val_loss: 4.4708 - val_accuracy: 0.7541
Epoch 34/100
3/3 [==============================] - 0s 25ms/step - loss: 4.5672 - accuracy: 0.6420 - val_loss: 4.4165 - val_accuracy: 0.7738
Epoch 35/100
3/3 [==============================] - 0s 27ms/step - loss: 4.4862 - accuracy: 0.6831 - val_loss: 4.3636 - val_accuracy: 0.7803
Epoch 36/100
3/3 [==============================] - 0s 23ms/step - loss: 4.4887 - accuracy: 0.6585 - val_loss: 4.3115 - val_accuracy: 0.7967
Epoch 37/100
3/3 [==============================] - 0s 25ms/step - loss: 4.3947 - accuracy: 0.7028 - val_loss: 4.2600 - val_accuracy: 0.8131
Epoch 38/100
3/3 [==============================] - 0s 25ms/step - loss: 4.3298 - accuracy: 0.7143 - val_loss: 4.2093 - val_accuracy: 0.8230
Epoch 39/100
3/3 [==============================] - 0s 25ms/step - loss: 4.2987 - accuracy: 0.7241 - val_loss: 4.1593 - val_accuracy: 0.8361
Epoch 40/100
3/3 [==============================] - 0s 26ms/step - loss: 4.2379 - accuracy: 0.7422 - val_loss: 4.1096 - val_accuracy: 0.8426
Epoch 41/100
3/3 [==============================] - 0s 23ms/step - loss: 4.1864 - accuracy: 0.7570 - val_loss: 4.0613 - val_accuracy: 0.8492
Epoch 42/100
3/3 [==============================] - 0s 17ms/step - loss: 4.1666 - accuracy: 0.7734 - val_loss: 4.0145 - val_accuracy: 0.8623
Epoch 43/100
3/3 [==============================] - 0s 17ms/step - loss: 4.0949 - accuracy: 0.7668 - val_loss: 3.9687 - val_accuracy: 0.8623
Epoch 44/100
3/3 [==============================] - 0s 17ms/step - loss: 4.0556 - accuracy: 0.7635 - val_loss: 3.9240 - val_accuracy: 0.8623
Epoch 45/100
3/3 [==============================] - 0s 19ms/step - loss: 4.0114 - accuracy: 0.7997 - val_loss: 3.8798 - val_accuracy: 0.8623
Epoch 46/100
3/3 [==============================] - 0s 15ms/step - loss: 3.9548 - accuracy: 0.7915 - val_loss: 3.8360 - val_accuracy: 0.8656
Epoch 47/100
3/3 [==============================] - 0s 18ms/step - loss: 3.9333 - accuracy: 0.7849 - val_loss: 3.7922 - val_accuracy: 0.8656
Epoch 48/100
3/3 [==============================] - 0s 22ms/step - loss: 3.8912 - accuracy: 0.7947 - val_loss: 3.7485 - val_accuracy: 0.8656
Epoch 49/100
3/3 [==============================] - 0s 16ms/step - loss: 3.8384 - accuracy: 0.8161 - val_loss: 3.7049 - val_accuracy: 0.8656
Epoch 50/100
3/3 [==============================] - 0s 18ms/step - loss: 3.7960 - accuracy: 0.8210 - val_loss: 3.6622 - val_accuracy: 0.8689
Epoch 51/100
3/3 [==============================] - 0s 19ms/step - loss: 3.7438 - accuracy: 0.8227 - val_loss: 3.6207 - val_accuracy: 0.8721
Epoch 52/100
3/3 [==============================] - 0s 16ms/step - loss: 3.7148 - accuracy: 0.8259 - val_loss: 3.5792 - val_accuracy: 0.8721
Epoch 53/100
3/3 [==============================] - 0s 25ms/step - loss: 3.6586 - accuracy: 0.8309 - val_loss: 3.5377 - val_accuracy: 0.8721
Epoch 54/100
3/3 [==============================] - 0s 27ms/step - loss: 3.6082 - accuracy: 0.8309 - val_loss: 3.4963 - val_accuracy: 0.8721
Epoch 55/100
3/3 [==============================] - 0s 23ms/step - loss: 3.5747 - accuracy: 0.8374 - val_loss: 3.4548 - val_accuracy: 0.8721
Epoch 56/100
3/3 [==============================] - 0s 19ms/step - loss: 3.5417 - accuracy: 0.8276 - val_loss: 3.4133 - val_accuracy: 0.8721
Epoch 57/100
3/3 [==============================] - 0s 24ms/step - loss: 3.4985 - accuracy: 0.8391 - val_loss: 3.3715 - val_accuracy: 0.8721
Epoch 58/100
3/3 [==============================] - 0s 25ms/step - loss: 3.4571 - accuracy: 0.8342 - val_loss: 3.3310 - val_accuracy: 0.8721
Epoch 59/100
3/3 [==============================] - 0s 19ms/step - loss: 3.4074 - accuracy: 0.8391 - val_loss: 3.2908 - val_accuracy: 0.8721
Epoch 60/100
3/3 [==============================] - 0s 22ms/step - loss: 3.3826 - accuracy: 0.8325 - val_loss: 3.2504 - val_accuracy: 0.8721
Epoch 61/100
3/3 [==============================] - 0s 15ms/step - loss: 3.3302 - accuracy: 0.8374 - val_loss: 3.2109 - val_accuracy: 0.8721
Epoch 62/100
3/3 [==============================] - 0s 19ms/step - loss: 3.3075 - accuracy: 0.8391 - val_loss: 3.1715 - val_accuracy: 0.8721
Epoch 63/100
3/3 [==============================] - 0s 15ms/step - loss: 3.2619 - accuracy: 0.8374 - val_loss: 3.1322 - val_accuracy: 0.8721
Epoch 64/100
3/3 [==============================] - 0s 18ms/step - loss: 3.1985 - accuracy: 0.8374 - val_loss: 3.0930 - val_accuracy: 0.8721
Epoch 65/100
3/3 [==============================] - 0s 17ms/step - loss: 3.1661 - accuracy: 0.8391 - val_loss: 3.0547 - val_accuracy: 0.8721
Epoch 66/100
3/3 [==============================] - 0s 15ms/step - loss: 3.1358 - accuracy: 0.8358 - val_loss: 3.0165 - val_accuracy: 0.8721
Epoch 67/100
3/3 [==============================] - 0s 17ms/step - loss: 3.0983 - accuracy: 0.8391 - val_loss: 2.9781 - val_accuracy: 0.8721
Epoch 68/100
3/3 [==============================] - 0s 16ms/step - loss: 3.0573 - accuracy: 0.8391 - val_loss: 2.9395 - val_accuracy: 0.8721
Epoch 69/100
3/3 [==============================] - 0s 24ms/step - loss: 3.0152 - accuracy: 0.8391 - val_loss: 2.9013 - val_accuracy: 0.8721
Epoch 70/100
3/3 [==============================] - 0s 17ms/step - loss: 2.9634 - accuracy: 0.8391 - val_loss: 2.8634 - val_accuracy: 0.8721
Epoch 71/100
3/3 [==============================] - 0s 17ms/step - loss: 2.9431 - accuracy: 0.8374 - val_loss: 2.8255 - val_accuracy: 0.8721
Epoch 72/100
3/3 [==============================] - 0s 29ms/step - loss: 2.9146 - accuracy: 0.8374 - val_loss: 2.7879 - val_accuracy: 0.8721
Epoch 73/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8723 - accuracy: 0.8391 - val_loss: 2.7503 - val_accuracy: 0.8721
Epoch 74/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8398 - accuracy: 0.8391 - val_loss: 2.7132 - val_accuracy: 0.8721
Epoch 75/100
3/3 [==============================] - 0s 21ms/step - loss: 2.7977 - accuracy: 0.8391 - val_loss: 2.6766 - val_accuracy: 0.8721
Epoch 76/100
3/3 [==============================] - 0s 25ms/step - loss: 2.7544 - accuracy: 0.8374 - val_loss: 2.6402 - val_accuracy: 0.8721
Epoch 77/100
3/3 [==============================] - 0s 16ms/step - loss: 2.7160 - accuracy: 0.8391 - val_loss: 2.6046 - val_accuracy: 0.8721
Epoch 78/100
3/3 [==============================] - 0s 24ms/step - loss: 2.6780 - accuracy: 0.8391 - val_loss: 2.5686 - val_accuracy: 0.8721
Epoch 79/100
3/3 [==============================] - 0s 17ms/step - loss: 2.6559 - accuracy: 0.8391 - val_loss: 2.5322 - val_accuracy: 0.8721
Epoch 80/100
3/3 [==============================] - 0s 17ms/step - loss: 2.6175 - accuracy: 0.8391 - val_loss: 2.4958 - val_accuracy: 0.8721
Epoch 81/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5721 - accuracy: 0.8391 - val_loss: 2.4598 - val_accuracy: 0.8721
Epoch 82/100
3/3 [==============================] - 0s 16ms/step - loss: 2.5289 - accuracy: 0.8391 - val_loss: 2.4237 - val_accuracy: 0.8721
Epoch 83/100
3/3 [==============================] - 0s 19ms/step - loss: 2.5030 - accuracy: 0.8391 - val_loss: 2.3877 - val_accuracy: 0.8721
Epoch 84/100
3/3 [==============================] - 0s 23ms/step - loss: 2.4805 - accuracy: 0.8374 - val_loss: 2.3518 - val_accuracy: 0.8721
Epoch 85/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4320 - accuracy: 0.8391 - val_loss: 2.3162 - val_accuracy: 0.8721
Epoch 86/100
3/3 [==============================] - 0s 26ms/step - loss: 2.3937 - accuracy: 0.8391 - val_loss: 2.2803 - val_accuracy: 0.8721
Epoch 87/100
3/3 [==============================] - 0s 19ms/step - loss: 2.3723 - accuracy: 0.8391 - val_loss: 2.2449 - val_accuracy: 0.8721
Epoch 88/100
3/3 [==============================] - 0s 25ms/step - loss: 2.3306 - accuracy: 0.8391 - val_loss: 2.2103 - val_accuracy: 0.8721
Epoch 89/100
3/3 [==============================] - 0s 25ms/step - loss: 2.2833 - accuracy: 0.8391 - val_loss: 2.1769 - val_accuracy: 0.8721
Epoch 90/100
3/3 [==============================] - 0s 27ms/step - loss: 2.2472 - accuracy: 0.8391 - val_loss: 2.1440 - val_accuracy: 0.8721
Epoch 91/100
3/3 [==============================] - 0s 16ms/step - loss: 2.2333 - accuracy: 0.8391 - val_loss: 2.1110 - val_accuracy: 0.8721
Epoch 92/100
3/3 [==============================] - 0s 17ms/step - loss: 2.1979 - accuracy: 0.8391 - val_loss: 2.0789 - val_accuracy: 0.8721
Epoch 93/100
3/3 [==============================] - 0s 16ms/step - loss: 2.1602 - accuracy: 0.8391 - val_loss: 2.0464 - val_accuracy: 0.8721
Epoch 94/100
3/3 [==============================] - 0s 22ms/step - loss: 2.1217 - accuracy: 0.8391 - val_loss: 2.0145 - val_accuracy: 0.8721
Epoch 95/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0938 - accuracy: 0.8391 - val_loss: 1.9832 - val_accuracy: 0.8721
Epoch 96/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0627 - accuracy: 0.8391 - val_loss: 1.9527 - val_accuracy: 0.8721
Epoch 97/100
3/3 [==============================] - 0s 17ms/step - loss: 2.0317 - accuracy: 0.8391 - val_loss: 1.9223 - val_accuracy: 0.8721
Epoch 98/100
3/3 [==============================] - 0s 16ms/step - loss: 2.0006 - accuracy: 0.8391 - val_loss: 1.8931 - val_accuracy: 0.8721
Epoch 99/100
3/3 [==============================] - 0s 16ms/step - loss: 1.9705 - accuracy: 0.8391 - val_loss: 1.8644 - val_accuracy: 0.8721
Epoch 100/100
3/3 [==============================] - 0s 17ms/step - loss: 1.9388 - accuracy: 0.8391 - val_loss: 1.8367 - val_accuracy: 0.8721
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 0s/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 1, 'hidden_units': 16, 'learning_rate_decay': 1.0000000000000001e-07, 'optimizer': 'momentum', 'l1': 0.1, 'l2': 0.001, 'dropout_rate': 0.3, 'momentum': 0.99, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'he_normal'}
Batch size: 256
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
3/3 [==============================] - 1s 111ms/step - loss: 5.7667 - accuracy: 0.2689 - val_loss: 5.7579 - val_accuracy: 0.2237
Epoch 2/100
3/3 [==============================] - 0s 22ms/step - loss: 5.7405 - accuracy: 0.2656 - val_loss: 5.7510 - val_accuracy: 0.2204
Epoch 3/100
3/3 [==============================] - 0s 15ms/step - loss: 5.7684 - accuracy: 0.2557 - val_loss: 5.7402 - val_accuracy: 0.2204
Epoch 4/100
3/3 [==============================] - 0s 25ms/step - loss: 5.7691 - accuracy: 0.2557 - val_loss: 5.7256 - val_accuracy: 0.2303
Epoch 5/100
3/3 [==============================] - 0s 25ms/step - loss: 5.7605 - accuracy: 0.2590 - val_loss: 5.7073 - val_accuracy: 0.2303
Epoch 6/100
3/3 [==============================] - 0s 27ms/step - loss: 5.7305 - accuracy: 0.2492 - val_loss: 5.6856 - val_accuracy: 0.2336
Epoch 7/100
3/3 [==============================] - 0s 21ms/step - loss: 5.7375 - accuracy: 0.2574 - val_loss: 5.6605 - val_accuracy: 0.2467
Epoch 8/100
3/3 [==============================] - 0s 24ms/step - loss: 5.7088 - accuracy: 0.2590 - val_loss: 5.6323 - val_accuracy: 0.2566
Epoch 9/100
3/3 [==============================] - 0s 25ms/step - loss: 5.6457 - accuracy: 0.2918 - val_loss: 5.6010 - val_accuracy: 0.2632
Epoch 10/100
3/3 [==============================] - 0s 25ms/step - loss: 5.5990 - accuracy: 0.3082 - val_loss: 5.5671 - val_accuracy: 0.2730
Epoch 11/100
3/3 [==============================] - 0s 25ms/step - loss: 5.5886 - accuracy: 0.3066 - val_loss: 5.5305 - val_accuracy: 0.2961
Epoch 12/100
3/3 [==============================] - 0s 26ms/step - loss: 5.5814 - accuracy: 0.2836 - val_loss: 5.4915 - val_accuracy: 0.3092
Epoch 13/100
3/3 [==============================] - 0s 16ms/step - loss: 5.5470 - accuracy: 0.3246 - val_loss: 5.4504 - val_accuracy: 0.3224
Epoch 14/100
3/3 [==============================] - 0s 21ms/step - loss: 5.4490 - accuracy: 0.3246 - val_loss: 5.4073 - val_accuracy: 0.3322
Epoch 15/100
3/3 [==============================] - 0s 17ms/step - loss: 5.4326 - accuracy: 0.3344 - val_loss: 5.3623 - val_accuracy: 0.3487
Epoch 16/100
3/3 [==============================] - 0s 17ms/step - loss: 5.3747 - accuracy: 0.3705 - val_loss: 5.3157 - val_accuracy: 0.3783
Epoch 17/100
3/3 [==============================] - 0s 29ms/step - loss: 5.3641 - accuracy: 0.3754 - val_loss: 5.2680 - val_accuracy: 0.4211
Epoch 18/100
3/3 [==============================] - 0s 17ms/step - loss: 5.3140 - accuracy: 0.3918 - val_loss: 5.2189 - val_accuracy: 0.4375
Epoch 19/100
3/3 [==============================] - 0s 24ms/step - loss: 5.2284 - accuracy: 0.4311 - val_loss: 5.1686 - val_accuracy: 0.4572
Epoch 20/100
3/3 [==============================] - 0s 25ms/step - loss: 5.1730 - accuracy: 0.4295 - val_loss: 5.1185 - val_accuracy: 0.4638
Epoch 21/100
3/3 [==============================] - 0s 25ms/step - loss: 5.1300 - accuracy: 0.4426 - val_loss: 5.0679 - val_accuracy: 0.4836
Epoch 22/100
3/3 [==============================] - 0s 17ms/step - loss: 5.0726 - accuracy: 0.4984 - val_loss: 5.0166 - val_accuracy: 0.5099
Epoch 23/100
3/3 [==============================] - 0s 51ms/step - loss: 5.0295 - accuracy: 0.4754 - val_loss: 4.9652 - val_accuracy: 0.5296
Epoch 24/100
3/3 [==============================] - 0s 29ms/step - loss: 4.9578 - accuracy: 0.5213 - val_loss: 4.9141 - val_accuracy: 0.5428
Epoch 25/100
3/3 [==============================] - 0s 26ms/step - loss: 4.9459 - accuracy: 0.5180 - val_loss: 4.8627 - val_accuracy: 0.5724
Epoch 26/100
3/3 [==============================] - 0s 24ms/step - loss: 4.8924 - accuracy: 0.5361 - val_loss: 4.8113 - val_accuracy: 0.5954
Epoch 27/100
3/3 [==============================] - 0s 17ms/step - loss: 4.8272 - accuracy: 0.5557 - val_loss: 4.7597 - val_accuracy: 0.6151
Epoch 28/100
3/3 [==============================] - 0s 16ms/step - loss: 4.7938 - accuracy: 0.5410 - val_loss: 4.7083 - val_accuracy: 0.6316
Epoch 29/100
3/3 [==============================] - 0s 17ms/step - loss: 4.7327 - accuracy: 0.5918 - val_loss: 4.6569 - val_accuracy: 0.6579
Epoch 30/100
3/3 [==============================] - 0s 17ms/step - loss: 4.6938 - accuracy: 0.5885 - val_loss: 4.6059 - val_accuracy: 0.6842
Epoch 31/100
3/3 [==============================] - 0s 17ms/step - loss: 4.6098 - accuracy: 0.6115 - val_loss: 4.5556 - val_accuracy: 0.7105
Epoch 32/100
3/3 [==============================] - 0s 17ms/step - loss: 4.5713 - accuracy: 0.6541 - val_loss: 4.5058 - val_accuracy: 0.7336
Epoch 33/100
3/3 [==============================] - 0s 17ms/step - loss: 4.5158 - accuracy: 0.6557 - val_loss: 4.4565 - val_accuracy: 0.7500
Epoch 34/100
3/3 [==============================] - 0s 22ms/step - loss: 4.4951 - accuracy: 0.6689 - val_loss: 4.4079 - val_accuracy: 0.7730
Epoch 35/100
3/3 [==============================] - 0s 25ms/step - loss: 4.4464 - accuracy: 0.6934 - val_loss: 4.3598 - val_accuracy: 0.7796
Epoch 36/100
3/3 [==============================] - 0s 22ms/step - loss: 4.3911 - accuracy: 0.7033 - val_loss: 4.3122 - val_accuracy: 0.7895
Epoch 37/100
3/3 [==============================] - 0s 17ms/step - loss: 4.3404 - accuracy: 0.7328 - val_loss: 4.2650 - val_accuracy: 0.7961
Epoch 38/100
3/3 [==============================] - 0s 17ms/step - loss: 4.2727 - accuracy: 0.7197 - val_loss: 4.2189 - val_accuracy: 0.8059
Epoch 39/100
3/3 [==============================] - 0s 25ms/step - loss: 4.2329 - accuracy: 0.7443 - val_loss: 4.1729 - val_accuracy: 0.8191
Epoch 40/100
3/3 [==============================] - 0s 17ms/step - loss: 4.2174 - accuracy: 0.7475 - val_loss: 4.1270 - val_accuracy: 0.8257
Epoch 41/100
3/3 [==============================] - 0s 25ms/step - loss: 4.1689 - accuracy: 0.7426 - val_loss: 4.0812 - val_accuracy: 0.8257
Epoch 42/100
3/3 [==============================] - 0s 25ms/step - loss: 4.1144 - accuracy: 0.7590 - val_loss: 4.0363 - val_accuracy: 0.8289
Epoch 43/100
3/3 [==============================] - 0s 25ms/step - loss: 4.0607 - accuracy: 0.7852 - val_loss: 3.9915 - val_accuracy: 0.8355
Epoch 44/100
3/3 [==============================] - 0s 25ms/step - loss: 4.0280 - accuracy: 0.7852 - val_loss: 3.9469 - val_accuracy: 0.8322
Epoch 45/100
3/3 [==============================] - 0s 26ms/step - loss: 3.9726 - accuracy: 0.8033 - val_loss: 3.9029 - val_accuracy: 0.8355
Epoch 46/100
3/3 [==============================] - 0s 26ms/step - loss: 3.9495 - accuracy: 0.7984 - val_loss: 3.8602 - val_accuracy: 0.8355
Epoch 47/100
3/3 [==============================] - 0s 24ms/step - loss: 3.9027 - accuracy: 0.8066 - val_loss: 3.8184 - val_accuracy: 0.8388
Epoch 48/100
3/3 [==============================] - 0s 24ms/step - loss: 3.8456 - accuracy: 0.8115 - val_loss: 3.7768 - val_accuracy: 0.8388
Epoch 49/100
3/3 [==============================] - 0s 24ms/step - loss: 3.7916 - accuracy: 0.8164 - val_loss: 3.7365 - val_accuracy: 0.8487
Epoch 50/100
3/3 [==============================] - 0s 26ms/step - loss: 3.7698 - accuracy: 0.8328 - val_loss: 3.6963 - val_accuracy: 0.8487
Epoch 51/100
3/3 [==============================] - 0s 26ms/step - loss: 3.7387 - accuracy: 0.8279 - val_loss: 3.6561 - val_accuracy: 0.8520
Epoch 52/100
3/3 [==============================] - 0s 24ms/step - loss: 3.6885 - accuracy: 0.8344 - val_loss: 3.6162 - val_accuracy: 0.8520
Epoch 53/100
3/3 [==============================] - 0s 27ms/step - loss: 3.6508 - accuracy: 0.8328 - val_loss: 3.5762 - val_accuracy: 0.8520
Epoch 54/100
3/3 [==============================] - 0s 24ms/step - loss: 3.6162 - accuracy: 0.8295 - val_loss: 3.5371 - val_accuracy: 0.8520
Epoch 55/100
3/3 [==============================] - 0s 24ms/step - loss: 3.5897 - accuracy: 0.8344 - val_loss: 3.4986 - val_accuracy: 0.8553
Epoch 56/100
3/3 [==============================] - 0s 25ms/step - loss: 3.5183 - accuracy: 0.8410 - val_loss: 3.4602 - val_accuracy: 0.8553
Epoch 57/100
3/3 [==============================] - 0s 17ms/step - loss: 3.4999 - accuracy: 0.8344 - val_loss: 3.4216 - val_accuracy: 0.8553
Epoch 58/100
3/3 [==============================] - 0s 16ms/step - loss: 3.4578 - accuracy: 0.8377 - val_loss: 3.3831 - val_accuracy: 0.8553
Epoch 59/100
3/3 [==============================] - 0s 16ms/step - loss: 3.4295 - accuracy: 0.8377 - val_loss: 3.3449 - val_accuracy: 0.8586
Epoch 60/100
3/3 [==============================] - 0s 23ms/step - loss: 3.3798 - accuracy: 0.8393 - val_loss: 3.3066 - val_accuracy: 0.8586
Epoch 61/100
3/3 [==============================] - 0s 17ms/step - loss: 3.3505 - accuracy: 0.8377 - val_loss: 3.2685 - val_accuracy: 0.8586
Epoch 62/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3120 - accuracy: 0.8393 - val_loss: 3.2302 - val_accuracy: 0.8586
Epoch 63/100
3/3 [==============================] - 0s 17ms/step - loss: 3.2698 - accuracy: 0.8410 - val_loss: 3.1919 - val_accuracy: 0.8586
Epoch 64/100
3/3 [==============================] - 0s 15ms/step - loss: 3.2248 - accuracy: 0.8410 - val_loss: 3.1538 - val_accuracy: 0.8586
Epoch 65/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1920 - accuracy: 0.8410 - val_loss: 3.1163 - val_accuracy: 0.8586
Epoch 66/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1621 - accuracy: 0.8443 - val_loss: 3.0790 - val_accuracy: 0.8586
Epoch 67/100
3/3 [==============================] - 0s 26ms/step - loss: 3.1180 - accuracy: 0.8410 - val_loss: 3.0416 - val_accuracy: 0.8586
Epoch 68/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0761 - accuracy: 0.8443 - val_loss: 3.0038 - val_accuracy: 0.8618
Epoch 69/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0324 - accuracy: 0.8443 - val_loss: 2.9657 - val_accuracy: 0.8618
Epoch 70/100
3/3 [==============================] - 0s 27ms/step - loss: 3.0006 - accuracy: 0.8426 - val_loss: 2.9280 - val_accuracy: 0.8618
Epoch 71/100
3/3 [==============================] - 0s 24ms/step - loss: 2.9553 - accuracy: 0.8410 - val_loss: 2.8907 - val_accuracy: 0.8618
Epoch 72/100
3/3 [==============================] - 0s 24ms/step - loss: 2.9201 - accuracy: 0.8426 - val_loss: 2.8534 - val_accuracy: 0.8618
Epoch 73/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8879 - accuracy: 0.8410 - val_loss: 2.8168 - val_accuracy: 0.8618
Epoch 74/100
3/3 [==============================] - 0s 22ms/step - loss: 2.8601 - accuracy: 0.8410 - val_loss: 2.7813 - val_accuracy: 0.8618
Epoch 75/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8297 - accuracy: 0.8443 - val_loss: 2.7461 - val_accuracy: 0.8618
Epoch 76/100
3/3 [==============================] - 0s 25ms/step - loss: 2.7745 - accuracy: 0.8410 - val_loss: 2.7106 - val_accuracy: 0.8618
Epoch 77/100
3/3 [==============================] - 0s 28ms/step - loss: 2.7500 - accuracy: 0.8426 - val_loss: 2.6750 - val_accuracy: 0.8618
Epoch 78/100
3/3 [==============================] - 0s 26ms/step - loss: 2.7091 - accuracy: 0.8443 - val_loss: 2.6389 - val_accuracy: 0.8618
Epoch 79/100
3/3 [==============================] - 0s 20ms/step - loss: 2.6845 - accuracy: 0.8443 - val_loss: 2.6031 - val_accuracy: 0.8618
Epoch 80/100
3/3 [==============================] - 0s 22ms/step - loss: 2.6298 - accuracy: 0.8443 - val_loss: 2.5670 - val_accuracy: 0.8618
Epoch 81/100
3/3 [==============================] - 0s 25ms/step - loss: 2.5915 - accuracy: 0.8443 - val_loss: 2.5314 - val_accuracy: 0.8618
Epoch 82/100
3/3 [==============================] - 0s 26ms/step - loss: 2.5649 - accuracy: 0.8443 - val_loss: 2.4963 - val_accuracy: 0.8618
Epoch 83/100
3/3 [==============================] - 0s 27ms/step - loss: 2.5296 - accuracy: 0.8443 - val_loss: 2.4621 - val_accuracy: 0.8618
Epoch 84/100
3/3 [==============================] - 0s 21ms/step - loss: 2.4944 - accuracy: 0.8443 - val_loss: 2.4290 - val_accuracy: 0.8618
Epoch 85/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4542 - accuracy: 0.8443 - val_loss: 2.3961 - val_accuracy: 0.8618
Epoch 86/100
3/3 [==============================] - 0s 17ms/step - loss: 2.4336 - accuracy: 0.8443 - val_loss: 2.3639 - val_accuracy: 0.8618
Epoch 87/100
3/3 [==============================] - 0s 16ms/step - loss: 2.4036 - accuracy: 0.8443 - val_loss: 2.3318 - val_accuracy: 0.8618
Epoch 88/100
3/3 [==============================] - 0s 18ms/step - loss: 2.3603 - accuracy: 0.8443 - val_loss: 2.3002 - val_accuracy: 0.8618
Epoch 89/100
3/3 [==============================] - 0s 29ms/step - loss: 2.3277 - accuracy: 0.8443 - val_loss: 2.2691 - val_accuracy: 0.8618
Epoch 90/100
3/3 [==============================] - 0s 17ms/step - loss: 2.3152 - accuracy: 0.8443 - val_loss: 2.2380 - val_accuracy: 0.8618
Epoch 91/100
3/3 [==============================] - 0s 16ms/step - loss: 2.2572 - accuracy: 0.8443 - val_loss: 2.2076 - val_accuracy: 0.8618
Epoch 92/100
3/3 [==============================] - 0s 17ms/step - loss: 2.2358 - accuracy: 0.8426 - val_loss: 2.1768 - val_accuracy: 0.8618
Epoch 93/100
3/3 [==============================] - 0s 19ms/step - loss: 2.2056 - accuracy: 0.8443 - val_loss: 2.1465 - val_accuracy: 0.8618
Epoch 94/100
3/3 [==============================] - 0s 31ms/step - loss: 2.1782 - accuracy: 0.8443 - val_loss: 2.1169 - val_accuracy: 0.8618
Epoch 95/100
3/3 [==============================] - 0s 28ms/step - loss: 2.1446 - accuracy: 0.8443 - val_loss: 2.0876 - val_accuracy: 0.8618
Epoch 96/100
3/3 [==============================] - 0s 19ms/step - loss: 2.1162 - accuracy: 0.8443 - val_loss: 2.0577 - val_accuracy: 0.8618
Epoch 97/100
3/3 [==============================] - 0s 23ms/step - loss: 2.0706 - accuracy: 0.8443 - val_loss: 2.0280 - val_accuracy: 0.8618
Epoch 98/100
3/3 [==============================] - 0s 24ms/step - loss: 2.0526 - accuracy: 0.8443 - val_loss: 1.9992 - val_accuracy: 0.8618
Epoch 99/100
3/3 [==============================] - 0s 26ms/step - loss: 2.0172 - accuracy: 0.8443 - val_loss: 1.9704 - val_accuracy: 0.8618
Epoch 100/100
3/3 [==============================] - 0s 21ms/step - loss: 2.0018 - accuracy: 0.8443 - val_loss: 1.9418 - val_accuracy: 0.8618
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Experiment number: 10
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 256
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
3/3 [==============================] - 1s 118ms/step - loss: 3.5288 - accuracy: 0.2414 - val_loss: 3.5060 - val_accuracy: 0.2164
Epoch 2/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5216 - accuracy: 0.2414 - val_loss: 3.5020 - val_accuracy: 0.2262
Epoch 3/100
3/3 [==============================] - 0s 23ms/step - loss: 3.5238 - accuracy: 0.2430 - val_loss: 3.4964 - val_accuracy: 0.2295
Epoch 4/100
3/3 [==============================] - 0s 25ms/step - loss: 3.5089 - accuracy: 0.2808 - val_loss: 3.4896 - val_accuracy: 0.2426
Epoch 5/100
3/3 [==============================] - 0s 18ms/step - loss: 3.4995 - accuracy: 0.2726 - val_loss: 3.4822 - val_accuracy: 0.2492
Epoch 6/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5019 - accuracy: 0.2562 - val_loss: 3.4741 - val_accuracy: 0.2590
Epoch 7/100
3/3 [==============================] - 0s 17ms/step - loss: 3.4851 - accuracy: 0.2594 - val_loss: 3.4657 - val_accuracy: 0.2590
Epoch 8/100
3/3 [==============================] - 0s 18ms/step - loss: 3.4795 - accuracy: 0.2972 - val_loss: 3.4570 - val_accuracy: 0.2787
Epoch 9/100
3/3 [==============================] - 0s 25ms/step - loss: 3.4694 - accuracy: 0.2906 - val_loss: 3.4481 - val_accuracy: 0.2885
Epoch 10/100
3/3 [==============================] - 0s 24ms/step - loss: 3.4548 - accuracy: 0.3021 - val_loss: 3.4392 - val_accuracy: 0.3049
Epoch 11/100
3/3 [==============================] - 0s 23ms/step - loss: 3.4589 - accuracy: 0.2841 - val_loss: 3.4301 - val_accuracy: 0.3213
Epoch 12/100
3/3 [==============================] - 0s 26ms/step - loss: 3.4355 - accuracy: 0.3235 - val_loss: 3.4211 - val_accuracy: 0.3246
Epoch 13/100
3/3 [==============================] - 0s 23ms/step - loss: 3.4210 - accuracy: 0.3498 - val_loss: 3.4121 - val_accuracy: 0.3311
Epoch 14/100
3/3 [==============================] - 0s 23ms/step - loss: 3.4246 - accuracy: 0.3333 - val_loss: 3.4031 - val_accuracy: 0.3410
Epoch 15/100
3/3 [==============================] - 0s 24ms/step - loss: 3.4039 - accuracy: 0.3859 - val_loss: 3.3942 - val_accuracy: 0.3541
Epoch 16/100
3/3 [==============================] - 0s 22ms/step - loss: 3.4094 - accuracy: 0.3580 - val_loss: 3.3852 - val_accuracy: 0.3705
Epoch 17/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3854 - accuracy: 0.3924 - val_loss: 3.3764 - val_accuracy: 0.3934
Epoch 18/100
3/3 [==============================] - 0s 17ms/step - loss: 3.3734 - accuracy: 0.4319 - val_loss: 3.3676 - val_accuracy: 0.4066
Epoch 19/100
3/3 [==============================] - 0s 23ms/step - loss: 3.3843 - accuracy: 0.3859 - val_loss: 3.3589 - val_accuracy: 0.4393
Epoch 20/100
3/3 [==============================] - 0s 27ms/step - loss: 3.3684 - accuracy: 0.4089 - val_loss: 3.3502 - val_accuracy: 0.4492
Epoch 21/100
3/3 [==============================] - 0s 24ms/step - loss: 3.3571 - accuracy: 0.4417 - val_loss: 3.3416 - val_accuracy: 0.4557
Epoch 22/100
3/3 [==============================] - 0s 16ms/step - loss: 3.3409 - accuracy: 0.4762 - val_loss: 3.3330 - val_accuracy: 0.4754
Epoch 23/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3549 - accuracy: 0.4138 - val_loss: 3.3246 - val_accuracy: 0.5016
Epoch 24/100
3/3 [==============================] - 0s 21ms/step - loss: 3.3293 - accuracy: 0.4696 - val_loss: 3.3161 - val_accuracy: 0.5213
Epoch 25/100
3/3 [==============================] - 0s 27ms/step - loss: 3.3121 - accuracy: 0.4680 - val_loss: 3.3078 - val_accuracy: 0.5311
Epoch 26/100
3/3 [==============================] - 0s 23ms/step - loss: 3.3143 - accuracy: 0.4745 - val_loss: 3.2995 - val_accuracy: 0.5410
Epoch 27/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3048 - accuracy: 0.4778 - val_loss: 3.2914 - val_accuracy: 0.5410
Epoch 28/100
3/3 [==============================] - 0s 26ms/step - loss: 3.2831 - accuracy: 0.5287 - val_loss: 3.2832 - val_accuracy: 0.5508
Epoch 29/100
3/3 [==============================] - 0s 17ms/step - loss: 3.2788 - accuracy: 0.5304 - val_loss: 3.2752 - val_accuracy: 0.5607
Epoch 30/100
3/3 [==============================] - 0s 16ms/step - loss: 3.2766 - accuracy: 0.5369 - val_loss: 3.2673 - val_accuracy: 0.5803
Epoch 31/100
3/3 [==============================] - 0s 22ms/step - loss: 3.2740 - accuracy: 0.5386 - val_loss: 3.2593 - val_accuracy: 0.6033
Epoch 32/100
3/3 [==============================] - 0s 27ms/step - loss: 3.2548 - accuracy: 0.5616 - val_loss: 3.2515 - val_accuracy: 0.6197
Epoch 33/100
3/3 [==============================] - 0s 26ms/step - loss: 3.2381 - accuracy: 0.6076 - val_loss: 3.2438 - val_accuracy: 0.6295
Epoch 34/100
3/3 [==============================] - 0s 25ms/step - loss: 3.2453 - accuracy: 0.6010 - val_loss: 3.2361 - val_accuracy: 0.6525
Epoch 35/100
3/3 [==============================] - 0s 16ms/step - loss: 3.2442 - accuracy: 0.5846 - val_loss: 3.2284 - val_accuracy: 0.6656
Epoch 36/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2352 - accuracy: 0.5616 - val_loss: 3.2208 - val_accuracy: 0.6754
Epoch 37/100
3/3 [==============================] - 0s 26ms/step - loss: 3.2227 - accuracy: 0.6010 - val_loss: 3.2133 - val_accuracy: 0.6820
Epoch 38/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1951 - accuracy: 0.6453 - val_loss: 3.2058 - val_accuracy: 0.6918
Epoch 39/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2067 - accuracy: 0.6190 - val_loss: 3.1984 - val_accuracy: 0.6984
Epoch 40/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2093 - accuracy: 0.6388 - val_loss: 3.1910 - val_accuracy: 0.7082
Epoch 41/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1976 - accuracy: 0.6355 - val_loss: 3.1837 - val_accuracy: 0.7115
Epoch 42/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1723 - accuracy: 0.6552 - val_loss: 3.1764 - val_accuracy: 0.7148
Epoch 43/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1619 - accuracy: 0.6782 - val_loss: 3.1692 - val_accuracy: 0.7279
Epoch 44/100
3/3 [==============================] - 0s 18ms/step - loss: 3.1609 - accuracy: 0.6798 - val_loss: 3.1621 - val_accuracy: 0.7246
Epoch 45/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1671 - accuracy: 0.6552 - val_loss: 3.1551 - val_accuracy: 0.7311
Epoch 46/100
3/3 [==============================] - 0s 20ms/step - loss: 3.1506 - accuracy: 0.6847 - val_loss: 3.1480 - val_accuracy: 0.7344
Epoch 47/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1504 - accuracy: 0.6765 - val_loss: 3.1411 - val_accuracy: 0.7410
Epoch 48/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1391 - accuracy: 0.6929 - val_loss: 3.1342 - val_accuracy: 0.7410
Epoch 49/100
3/3 [==============================] - 0s 19ms/step - loss: 3.1359 - accuracy: 0.6864 - val_loss: 3.1273 - val_accuracy: 0.7475
Epoch 50/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1248 - accuracy: 0.7028 - val_loss: 3.1205 - val_accuracy: 0.7475
Epoch 51/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1251 - accuracy: 0.6864 - val_loss: 3.1137 - val_accuracy: 0.7475
Epoch 52/100
3/3 [==============================] - 0s 17ms/step - loss: 3.1089 - accuracy: 0.6962 - val_loss: 3.1070 - val_accuracy: 0.7607
Epoch 53/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1030 - accuracy: 0.7225 - val_loss: 3.1003 - val_accuracy: 0.7639
Epoch 54/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0750 - accuracy: 0.7570 - val_loss: 3.0938 - val_accuracy: 0.7639
Epoch 55/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0906 - accuracy: 0.7340 - val_loss: 3.0872 - val_accuracy: 0.7639
Epoch 56/100
3/3 [==============================] - 0s 24ms/step - loss: 3.0815 - accuracy: 0.7323 - val_loss: 3.0807 - val_accuracy: 0.7639
Epoch 57/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0833 - accuracy: 0.7274 - val_loss: 3.0743 - val_accuracy: 0.7639
Epoch 58/100
3/3 [==============================] - 0s 26ms/step - loss: 3.0740 - accuracy: 0.7323 - val_loss: 3.0679 - val_accuracy: 0.7541
Epoch 59/100
3/3 [==============================] - 0s 17ms/step - loss: 3.0580 - accuracy: 0.7635 - val_loss: 3.0616 - val_accuracy: 0.7541
Epoch 60/100
3/3 [==============================] - 0s 15ms/step - loss: 3.0507 - accuracy: 0.7603 - val_loss: 3.0553 - val_accuracy: 0.7639
Epoch 61/100
3/3 [==============================] - 0s 24ms/step - loss: 3.0478 - accuracy: 0.7586 - val_loss: 3.0491 - val_accuracy: 0.7672
Epoch 62/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0444 - accuracy: 0.7422 - val_loss: 3.0429 - val_accuracy: 0.7705
Epoch 63/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0364 - accuracy: 0.7750 - val_loss: 3.0367 - val_accuracy: 0.7738
Epoch 64/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0337 - accuracy: 0.7652 - val_loss: 3.0306 - val_accuracy: 0.7770
Epoch 65/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0174 - accuracy: 0.7997 - val_loss: 3.0246 - val_accuracy: 0.7803
Epoch 66/100
3/3 [==============================] - 0s 18ms/step - loss: 3.0128 - accuracy: 0.8079 - val_loss: 3.0186 - val_accuracy: 0.7803
Epoch 67/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0138 - accuracy: 0.7701 - val_loss: 3.0126 - val_accuracy: 0.7869
Epoch 68/100
3/3 [==============================] - 0s 14ms/step - loss: 3.0089 - accuracy: 0.7734 - val_loss: 3.0067 - val_accuracy: 0.7902
Epoch 69/100
3/3 [==============================] - 0s 27ms/step - loss: 3.0004 - accuracy: 0.7833 - val_loss: 3.0008 - val_accuracy: 0.7902
Epoch 70/100
3/3 [==============================] - 0s 20ms/step - loss: 2.9925 - accuracy: 0.7800 - val_loss: 2.9950 - val_accuracy: 0.7902
Epoch 71/100
3/3 [==============================] - 0s 26ms/step - loss: 2.9796 - accuracy: 0.7980 - val_loss: 2.9892 - val_accuracy: 0.7902
Epoch 72/100
3/3 [==============================] - 0s 18ms/step - loss: 2.9688 - accuracy: 0.8210 - val_loss: 2.9834 - val_accuracy: 0.7934
Epoch 73/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9648 - accuracy: 0.8046 - val_loss: 2.9777 - val_accuracy: 0.7934
Epoch 74/100
3/3 [==============================] - 0s 24ms/step - loss: 2.9751 - accuracy: 0.7947 - val_loss: 2.9721 - val_accuracy: 0.7934
Epoch 75/100
3/3 [==============================] - 0s 26ms/step - loss: 2.9682 - accuracy: 0.8030 - val_loss: 2.9664 - val_accuracy: 0.7967
Epoch 76/100
3/3 [==============================] - 0s 18ms/step - loss: 2.9508 - accuracy: 0.8030 - val_loss: 2.9609 - val_accuracy: 0.7967
Epoch 77/100
3/3 [==============================] - 0s 16ms/step - loss: 2.9497 - accuracy: 0.8095 - val_loss: 2.9553 - val_accuracy: 0.8033
Epoch 78/100
3/3 [==============================] - 0s 17ms/step - loss: 2.9429 - accuracy: 0.8095 - val_loss: 2.9499 - val_accuracy: 0.8033
Epoch 79/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9314 - accuracy: 0.8144 - val_loss: 2.9444 - val_accuracy: 0.8033
Epoch 80/100
3/3 [==============================] - 0s 20ms/step - loss: 2.9326 - accuracy: 0.8013 - val_loss: 2.9390 - val_accuracy: 0.8033
Epoch 81/100
3/3 [==============================] - 0s 27ms/step - loss: 2.9205 - accuracy: 0.8309 - val_loss: 2.9336 - val_accuracy: 0.8066
Epoch 82/100
3/3 [==============================] - 0s 23ms/step - loss: 2.9197 - accuracy: 0.8210 - val_loss: 2.9282 - val_accuracy: 0.8098
Epoch 83/100
3/3 [==============================] - 0s 19ms/step - loss: 2.9248 - accuracy: 0.8210 - val_loss: 2.9229 - val_accuracy: 0.8098
Epoch 84/100
3/3 [==============================] - 0s 17ms/step - loss: 2.9083 - accuracy: 0.8325 - val_loss: 2.9176 - val_accuracy: 0.8098
Epoch 85/100
3/3 [==============================] - 0s 23ms/step - loss: 2.9087 - accuracy: 0.8095 - val_loss: 2.9123 - val_accuracy: 0.8098
Epoch 86/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8976 - accuracy: 0.8440 - val_loss: 2.9071 - val_accuracy: 0.8098
Epoch 87/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8886 - accuracy: 0.8292 - val_loss: 2.9020 - val_accuracy: 0.8098
Epoch 88/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8816 - accuracy: 0.8407 - val_loss: 2.8968 - val_accuracy: 0.8098
Epoch 89/100
3/3 [==============================] - 0s 23ms/step - loss: 2.8743 - accuracy: 0.8391 - val_loss: 2.8917 - val_accuracy: 0.8098
Epoch 90/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8775 - accuracy: 0.8292 - val_loss: 2.8866 - val_accuracy: 0.8098
Epoch 91/100
3/3 [==============================] - 0s 26ms/step - loss: 2.8770 - accuracy: 0.8259 - val_loss: 2.8816 - val_accuracy: 0.8098
Epoch 92/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8742 - accuracy: 0.8227 - val_loss: 2.8766 - val_accuracy: 0.8098
Epoch 93/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8554 - accuracy: 0.8407 - val_loss: 2.8717 - val_accuracy: 0.8098
Epoch 94/100
3/3 [==============================] - 0s 17ms/step - loss: 2.8654 - accuracy: 0.8342 - val_loss: 2.8667 - val_accuracy: 0.8098
Epoch 95/100
3/3 [==============================] - 0s 26ms/step - loss: 2.8434 - accuracy: 0.8506 - val_loss: 2.8618 - val_accuracy: 0.8131
Epoch 96/100
3/3 [==============================] - 0s 27ms/step - loss: 2.8371 - accuracy: 0.8424 - val_loss: 2.8569 - val_accuracy: 0.8131
Epoch 97/100
3/3 [==============================] - 0s 20ms/step - loss: 2.8364 - accuracy: 0.8374 - val_loss: 2.8521 - val_accuracy: 0.8131
Epoch 98/100
3/3 [==============================] - 0s 22ms/step - loss: 2.8363 - accuracy: 0.8374 - val_loss: 2.8473 - val_accuracy: 0.8131
Epoch 99/100
3/3 [==============================] - 0s 19ms/step - loss: 2.8263 - accuracy: 0.8506 - val_loss: 2.8425 - val_accuracy: 0.8164
Epoch 100/100
3/3 [==============================] - 0s 23ms/step - loss: 2.8279 - accuracy: 0.8407 - val_loss: 2.8378 - val_accuracy: 0.8164
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 256
X_current_train shape: (609, 11)
y_current_train shape: (609, 3)
Epoch 1/100
3/3 [==============================] - 1s 121ms/step - loss: 3.4552 - accuracy: 0.3448 - val_loss: 3.4413 - val_accuracy: 0.3377
Epoch 2/100
3/3 [==============================] - 0s 26ms/step - loss: 3.4541 - accuracy: 0.3383 - val_loss: 3.4376 - val_accuracy: 0.3443
Epoch 3/100
3/3 [==============================] - 0s 23ms/step - loss: 3.4581 - accuracy: 0.3186 - val_loss: 3.4324 - val_accuracy: 0.3607
Epoch 4/100
3/3 [==============================] - 0s 25ms/step - loss: 3.4411 - accuracy: 0.3793 - val_loss: 3.4263 - val_accuracy: 0.3770
Epoch 5/100
3/3 [==============================] - 0s 24ms/step - loss: 3.4198 - accuracy: 0.3875 - val_loss: 3.4194 - val_accuracy: 0.3869
Epoch 6/100
3/3 [==============================] - 0s 18ms/step - loss: 3.4336 - accuracy: 0.3793 - val_loss: 3.4120 - val_accuracy: 0.4033
Epoch 7/100
3/3 [==============================] - 0s 24ms/step - loss: 3.4267 - accuracy: 0.3793 - val_loss: 3.4041 - val_accuracy: 0.4098
Epoch 8/100
3/3 [==============================] - 0s 26ms/step - loss: 3.4141 - accuracy: 0.4220 - val_loss: 3.3961 - val_accuracy: 0.4230
Epoch 9/100
3/3 [==============================] - 0s 16ms/step - loss: 3.3983 - accuracy: 0.3892 - val_loss: 3.3879 - val_accuracy: 0.4590
Epoch 10/100
3/3 [==============================] - 0s 25ms/step - loss: 3.4012 - accuracy: 0.4154 - val_loss: 3.3796 - val_accuracy: 0.4656
Epoch 11/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3874 - accuracy: 0.4335 - val_loss: 3.3713 - val_accuracy: 0.4852
Epoch 12/100
3/3 [==============================] - 0s 19ms/step - loss: 3.3691 - accuracy: 0.4319 - val_loss: 3.3630 - val_accuracy: 0.5049
Epoch 13/100
3/3 [==============================] - 0s 19ms/step - loss: 3.3775 - accuracy: 0.4056 - val_loss: 3.3547 - val_accuracy: 0.5213
Epoch 14/100
3/3 [==============================] - 0s 23ms/step - loss: 3.3656 - accuracy: 0.4663 - val_loss: 3.3464 - val_accuracy: 0.5311
Epoch 15/100
3/3 [==============================] - 0s 24ms/step - loss: 3.3495 - accuracy: 0.4893 - val_loss: 3.3381 - val_accuracy: 0.5672
Epoch 16/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3471 - accuracy: 0.4877 - val_loss: 3.3299 - val_accuracy: 0.5803
Epoch 17/100
3/3 [==============================] - 0s 22ms/step - loss: 3.3450 - accuracy: 0.4926 - val_loss: 3.3216 - val_accuracy: 0.5902
Epoch 18/100
3/3 [==============================] - 0s 22ms/step - loss: 3.3329 - accuracy: 0.5057 - val_loss: 3.3135 - val_accuracy: 0.6098
Epoch 19/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3190 - accuracy: 0.5123 - val_loss: 3.3054 - val_accuracy: 0.6197
Epoch 20/100
3/3 [==============================] - 0s 18ms/step - loss: 3.3088 - accuracy: 0.5255 - val_loss: 3.2974 - val_accuracy: 0.6328
Epoch 21/100
3/3 [==============================] - 0s 25ms/step - loss: 3.3087 - accuracy: 0.5172 - val_loss: 3.2895 - val_accuracy: 0.6426
Epoch 22/100
3/3 [==============================] - 0s 27ms/step - loss: 3.2963 - accuracy: 0.5616 - val_loss: 3.2817 - val_accuracy: 0.6623
Epoch 23/100
3/3 [==============================] - 0s 17ms/step - loss: 3.3017 - accuracy: 0.5189 - val_loss: 3.2739 - val_accuracy: 0.6689
Epoch 24/100
3/3 [==============================] - 0s 24ms/step - loss: 3.2874 - accuracy: 0.5780 - val_loss: 3.2661 - val_accuracy: 0.6754
Epoch 25/100
3/3 [==============================] - 0s 25ms/step - loss: 3.2845 - accuracy: 0.5435 - val_loss: 3.2584 - val_accuracy: 0.6918
Epoch 26/100
3/3 [==============================] - 0s 25ms/step - loss: 3.2771 - accuracy: 0.5911 - val_loss: 3.2508 - val_accuracy: 0.6984
Epoch 27/100
3/3 [==============================] - 0s 30ms/step - loss: 3.2641 - accuracy: 0.5698 - val_loss: 3.2432 - val_accuracy: 0.7180
Epoch 28/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2597 - accuracy: 0.6059 - val_loss: 3.2357 - val_accuracy: 0.7180
Epoch 29/100
3/3 [==============================] - 0s 22ms/step - loss: 3.2361 - accuracy: 0.6273 - val_loss: 3.2283 - val_accuracy: 0.7213
Epoch 30/100
3/3 [==============================] - 0s 25ms/step - loss: 3.2457 - accuracy: 0.6026 - val_loss: 3.2209 - val_accuracy: 0.7279
Epoch 31/100
3/3 [==============================] - 0s 24ms/step - loss: 3.2323 - accuracy: 0.6453 - val_loss: 3.2136 - val_accuracy: 0.7246
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2291 - accuracy: 0.6223 - val_loss: 3.2064 - val_accuracy: 0.7475
Epoch 33/100
3/3 [==============================] - 0s 22ms/step - loss: 3.2156 - accuracy: 0.6404 - val_loss: 3.1992 - val_accuracy: 0.7508
Epoch 34/100
3/3 [==============================] - 0s 26ms/step - loss: 3.2094 - accuracy: 0.6273 - val_loss: 3.1921 - val_accuracy: 0.7541
Epoch 35/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2169 - accuracy: 0.6223 - val_loss: 3.1850 - val_accuracy: 0.7705
Epoch 36/100
3/3 [==============================] - 0s 34ms/step - loss: 3.1940 - accuracy: 0.6798 - val_loss: 3.1780 - val_accuracy: 0.7967
Epoch 37/100
3/3 [==============================] - 0s 26ms/step - loss: 3.1940 - accuracy: 0.6617 - val_loss: 3.1710 - val_accuracy: 0.8066
Epoch 38/100
3/3 [==============================] - 0s 16ms/step - loss: 3.1839 - accuracy: 0.6765 - val_loss: 3.1641 - val_accuracy: 0.8098
Epoch 39/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1857 - accuracy: 0.6749 - val_loss: 3.1572 - val_accuracy: 0.8098
Epoch 40/100
3/3 [==============================] - 0s 28ms/step - loss: 3.1675 - accuracy: 0.7028 - val_loss: 3.1503 - val_accuracy: 0.8164
Epoch 41/100
3/3 [==============================] - 0s 16ms/step - loss: 3.1537 - accuracy: 0.7192 - val_loss: 3.1435 - val_accuracy: 0.8164
Epoch 42/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1540 - accuracy: 0.7274 - val_loss: 3.1368 - val_accuracy: 0.8164
Epoch 43/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1589 - accuracy: 0.7126 - val_loss: 3.1301 - val_accuracy: 0.8197
Epoch 44/100
3/3 [==============================] - 0s 26ms/step - loss: 3.1469 - accuracy: 0.7356 - val_loss: 3.1235 - val_accuracy: 0.8295
Epoch 45/100
3/3 [==============================] - 0s 17ms/step - loss: 3.1443 - accuracy: 0.7258 - val_loss: 3.1169 - val_accuracy: 0.8295
Epoch 46/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1496 - accuracy: 0.6962 - val_loss: 3.1104 - val_accuracy: 0.8328
Epoch 47/100
3/3 [==============================] - 0s 21ms/step - loss: 3.1301 - accuracy: 0.7422 - val_loss: 3.1039 - val_accuracy: 0.8328
Epoch 48/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1281 - accuracy: 0.7110 - val_loss: 3.0974 - val_accuracy: 0.8328
Epoch 49/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1135 - accuracy: 0.7356 - val_loss: 3.0910 - val_accuracy: 0.8328
Epoch 50/100
3/3 [==============================] - 0s 26ms/step - loss: 3.1075 - accuracy: 0.7488 - val_loss: 3.0847 - val_accuracy: 0.8295
Epoch 51/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1125 - accuracy: 0.7340 - val_loss: 3.0784 - val_accuracy: 0.8295
Epoch 52/100
3/3 [==============================] - 0s 28ms/step - loss: 3.0823 - accuracy: 0.7767 - val_loss: 3.0722 - val_accuracy: 0.8328
Epoch 53/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0892 - accuracy: 0.7701 - val_loss: 3.0660 - val_accuracy: 0.8393
Epoch 54/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0845 - accuracy: 0.7537 - val_loss: 3.0599 - val_accuracy: 0.8393
Epoch 55/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0758 - accuracy: 0.7652 - val_loss: 3.0538 - val_accuracy: 0.8361
Epoch 56/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0661 - accuracy: 0.7635 - val_loss: 3.0478 - val_accuracy: 0.8361
Epoch 57/100
3/3 [==============================] - 0s 18ms/step - loss: 3.0662 - accuracy: 0.7816 - val_loss: 3.0418 - val_accuracy: 0.8393
Epoch 58/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0550 - accuracy: 0.7800 - val_loss: 3.0359 - val_accuracy: 0.8393
Epoch 59/100
3/3 [==============================] - 0s 26ms/step - loss: 3.0495 - accuracy: 0.7685 - val_loss: 3.0300 - val_accuracy: 0.8426
Epoch 60/100
3/3 [==============================] - 0s 16ms/step - loss: 3.0452 - accuracy: 0.7701 - val_loss: 3.0241 - val_accuracy: 0.8492
Epoch 61/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0396 - accuracy: 0.7865 - val_loss: 3.0182 - val_accuracy: 0.8492
Epoch 62/100
3/3 [==============================] - 0s 27ms/step - loss: 3.0407 - accuracy: 0.7931 - val_loss: 3.0124 - val_accuracy: 0.8492
Epoch 63/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0248 - accuracy: 0.7816 - val_loss: 3.0067 - val_accuracy: 0.8525
Epoch 64/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0320 - accuracy: 0.7783 - val_loss: 3.0009 - val_accuracy: 0.8525
Epoch 65/100
3/3 [==============================] - 0s 17ms/step - loss: 3.0155 - accuracy: 0.7980 - val_loss: 2.9952 - val_accuracy: 0.8590
Epoch 66/100
3/3 [==============================] - 0s 24ms/step - loss: 3.0168 - accuracy: 0.7849 - val_loss: 2.9896 - val_accuracy: 0.8590
Epoch 67/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0067 - accuracy: 0.7947 - val_loss: 2.9839 - val_accuracy: 0.8656
Epoch 68/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9975 - accuracy: 0.8013 - val_loss: 2.9783 - val_accuracy: 0.8656
Epoch 69/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9898 - accuracy: 0.8095 - val_loss: 2.9727 - val_accuracy: 0.8656
Epoch 70/100
3/3 [==============================] - 0s 23ms/step - loss: 2.9949 - accuracy: 0.8095 - val_loss: 2.9672 - val_accuracy: 0.8656
Epoch 71/100
3/3 [==============================] - 0s 26ms/step - loss: 2.9888 - accuracy: 0.8095 - val_loss: 2.9618 - val_accuracy: 0.8656
Epoch 72/100
3/3 [==============================] - 0s 17ms/step - loss: 2.9850 - accuracy: 0.8013 - val_loss: 2.9563 - val_accuracy: 0.8656
Epoch 73/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9760 - accuracy: 0.7980 - val_loss: 2.9509 - val_accuracy: 0.8689
Epoch 74/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9710 - accuracy: 0.7997 - val_loss: 2.9456 - val_accuracy: 0.8689
Epoch 75/100
3/3 [==============================] - 0s 19ms/step - loss: 2.9631 - accuracy: 0.8095 - val_loss: 2.9402 - val_accuracy: 0.8689
Epoch 76/100
3/3 [==============================] - 0s 23ms/step - loss: 2.9518 - accuracy: 0.8276 - val_loss: 2.9350 - val_accuracy: 0.8689
Epoch 77/100
3/3 [==============================] - 0s 21ms/step - loss: 2.9594 - accuracy: 0.8079 - val_loss: 2.9297 - val_accuracy: 0.8689
Epoch 78/100
3/3 [==============================] - 0s 28ms/step - loss: 2.9464 - accuracy: 0.8194 - val_loss: 2.9245 - val_accuracy: 0.8689
Epoch 79/100
3/3 [==============================] - 0s 19ms/step - loss: 2.9548 - accuracy: 0.8079 - val_loss: 2.9192 - val_accuracy: 0.8721
Epoch 80/100
3/3 [==============================] - 0s 22ms/step - loss: 2.9430 - accuracy: 0.8095 - val_loss: 2.9140 - val_accuracy: 0.8721
Epoch 81/100
3/3 [==============================] - 0s 22ms/step - loss: 2.9252 - accuracy: 0.8227 - val_loss: 2.9089 - val_accuracy: 0.8721
Epoch 82/100
3/3 [==============================] - 0s 23ms/step - loss: 2.9446 - accuracy: 0.8112 - val_loss: 2.9038 - val_accuracy: 0.8721
Epoch 83/100
3/3 [==============================] - 0s 24ms/step - loss: 2.9395 - accuracy: 0.8013 - val_loss: 2.8987 - val_accuracy: 0.8721
Epoch 84/100
3/3 [==============================] - 0s 26ms/step - loss: 2.9162 - accuracy: 0.8424 - val_loss: 2.8936 - val_accuracy: 0.8721
Epoch 85/100
3/3 [==============================] - 0s 22ms/step - loss: 2.9207 - accuracy: 0.8128 - val_loss: 2.8886 - val_accuracy: 0.8721
Epoch 86/100
3/3 [==============================] - 0s 22ms/step - loss: 2.9080 - accuracy: 0.8342 - val_loss: 2.8836 - val_accuracy: 0.8721
Epoch 87/100
3/3 [==============================] - 0s 17ms/step - loss: 2.9110 - accuracy: 0.8210 - val_loss: 2.8786 - val_accuracy: 0.8721
Epoch 88/100
3/3 [==============================] - 0s 21ms/step - loss: 2.9136 - accuracy: 0.8210 - val_loss: 2.8736 - val_accuracy: 0.8721
Epoch 89/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8948 - accuracy: 0.8210 - val_loss: 2.8687 - val_accuracy: 0.8721
Epoch 90/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8794 - accuracy: 0.8309 - val_loss: 2.8638 - val_accuracy: 0.8721
Epoch 91/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8963 - accuracy: 0.8177 - val_loss: 2.8589 - val_accuracy: 0.8721
Epoch 92/100
3/3 [==============================] - 0s 18ms/step - loss: 2.8841 - accuracy: 0.8325 - val_loss: 2.8541 - val_accuracy: 0.8721
Epoch 93/100
3/3 [==============================] - 0s 16ms/step - loss: 2.8777 - accuracy: 0.8243 - val_loss: 2.8493 - val_accuracy: 0.8721
Epoch 94/100
3/3 [==============================] - 0s 23ms/step - loss: 2.8711 - accuracy: 0.8391 - val_loss: 2.8445 - val_accuracy: 0.8721
Epoch 95/100
3/3 [==============================] - 0s 22ms/step - loss: 2.8610 - accuracy: 0.8407 - val_loss: 2.8397 - val_accuracy: 0.8721
Epoch 96/100
3/3 [==============================] - 0s 23ms/step - loss: 2.8642 - accuracy: 0.8391 - val_loss: 2.8349 - val_accuracy: 0.8721
Epoch 97/100
3/3 [==============================] - 0s 21ms/step - loss: 2.8545 - accuracy: 0.8473 - val_loss: 2.8302 - val_accuracy: 0.8721
Epoch 98/100
3/3 [==============================] - 0s 22ms/step - loss: 2.8590 - accuracy: 0.8325 - val_loss: 2.8255 - val_accuracy: 0.8721
Epoch 99/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8485 - accuracy: 0.8325 - val_loss: 2.8208 - val_accuracy: 0.8721
Epoch 100/100
3/3 [==============================] - 0s 23ms/step - loss: 2.8359 - accuracy: 0.8342 - val_loss: 2.8161 - val_accuracy: 0.8721
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 2ms/step
Model parameters: {'learning_rate': 0.0001, 'hidden_layers': 4, 'hidden_units': 256, 'learning_rate_decay': 1e-05, 'optimizer': 'momentum', 'l1': 0.001, 'l2': 0.1, 'dropout_rate': 0.4, 'momentum': 0.9, 'adam_beta_1': None, 'adam_beta_2': None, 'rho': None, 'batch_norm': False, 'initializers': 'glorot_uniform'}
Batch size: 256
X_current_train shape: (610, 11)
y_current_train shape: (610, 3)
Epoch 1/100
3/3 [==============================] - 1s 120ms/step - loss: 3.5887 - accuracy: 0.2393 - val_loss: 3.5813 - val_accuracy: 0.1809
Epoch 2/100
3/3 [==============================] - 0s 26ms/step - loss: 3.5969 - accuracy: 0.2066 - val_loss: 3.5768 - val_accuracy: 0.1875
Epoch 3/100
3/3 [==============================] - 0s 20ms/step - loss: 3.5809 - accuracy: 0.2475 - val_loss: 3.5708 - val_accuracy: 0.2007
Epoch 4/100
3/3 [==============================] - 0s 23ms/step - loss: 3.5916 - accuracy: 0.2016 - val_loss: 3.5635 - val_accuracy: 0.2138
Epoch 5/100
3/3 [==============================] - 0s 24ms/step - loss: 3.5729 - accuracy: 0.2230 - val_loss: 3.5554 - val_accuracy: 0.2237
Epoch 6/100
3/3 [==============================] - 0s 19ms/step - loss: 3.5709 - accuracy: 0.2426 - val_loss: 3.5467 - val_accuracy: 0.2434
Epoch 7/100
3/3 [==============================] - 0s 17ms/step - loss: 3.5450 - accuracy: 0.2541 - val_loss: 3.5376 - val_accuracy: 0.2566
Epoch 8/100
3/3 [==============================] - 0s 21ms/step - loss: 3.5566 - accuracy: 0.2754 - val_loss: 3.5282 - val_accuracy: 0.2730
Epoch 9/100
3/3 [==============================] - 0s 23ms/step - loss: 3.5464 - accuracy: 0.2721 - val_loss: 3.5186 - val_accuracy: 0.2895
Epoch 10/100
3/3 [==============================] - 0s 23ms/step - loss: 3.5311 - accuracy: 0.2787 - val_loss: 3.5089 - val_accuracy: 0.3026
Epoch 11/100
3/3 [==============================] - 0s 21ms/step - loss: 3.5142 - accuracy: 0.3180 - val_loss: 3.4991 - val_accuracy: 0.3257
Epoch 12/100
3/3 [==============================] - 0s 19ms/step - loss: 3.4950 - accuracy: 0.3279 - val_loss: 3.4893 - val_accuracy: 0.3520
Epoch 13/100
3/3 [==============================] - 0s 16ms/step - loss: 3.4903 - accuracy: 0.3262 - val_loss: 3.4796 - val_accuracy: 0.3553
Epoch 14/100
3/3 [==============================] - 0s 18ms/step - loss: 3.4956 - accuracy: 0.3098 - val_loss: 3.4700 - val_accuracy: 0.3618
Epoch 15/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4853 - accuracy: 0.3508 - val_loss: 3.4603 - val_accuracy: 0.3783
Epoch 16/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4769 - accuracy: 0.3508 - val_loss: 3.4507 - val_accuracy: 0.3980
Epoch 17/100
3/3 [==============================] - 0s 25ms/step - loss: 3.4641 - accuracy: 0.3557 - val_loss: 3.4412 - val_accuracy: 0.4013
Epoch 18/100
3/3 [==============================] - 0s 21ms/step - loss: 3.4467 - accuracy: 0.3836 - val_loss: 3.4317 - val_accuracy: 0.4145
Epoch 19/100
3/3 [==============================] - 0s 16ms/step - loss: 3.4551 - accuracy: 0.3770 - val_loss: 3.4223 - val_accuracy: 0.4243
Epoch 20/100
3/3 [==============================] - 0s 23ms/step - loss: 3.4483 - accuracy: 0.3918 - val_loss: 3.4129 - val_accuracy: 0.4507
Epoch 21/100
3/3 [==============================] - 0s 20ms/step - loss: 3.4323 - accuracy: 0.3787 - val_loss: 3.4036 - val_accuracy: 0.4638
Epoch 22/100
3/3 [==============================] - 0s 27ms/step - loss: 3.4219 - accuracy: 0.4344 - val_loss: 3.3944 - val_accuracy: 0.4704
Epoch 23/100
3/3 [==============================] - 0s 28ms/step - loss: 3.4130 - accuracy: 0.4148 - val_loss: 3.3852 - val_accuracy: 0.4836
Epoch 24/100
3/3 [==============================] - 0s 22ms/step - loss: 3.3898 - accuracy: 0.4508 - val_loss: 3.3761 - val_accuracy: 0.5033
Epoch 25/100
3/3 [==============================] - 0s 18ms/step - loss: 3.3890 - accuracy: 0.4574 - val_loss: 3.3671 - val_accuracy: 0.5099
Epoch 26/100
3/3 [==============================] - 0s 24ms/step - loss: 3.3865 - accuracy: 0.4672 - val_loss: 3.3582 - val_accuracy: 0.5263
Epoch 27/100
3/3 [==============================] - 0s 28ms/step - loss: 3.3797 - accuracy: 0.4639 - val_loss: 3.3493 - val_accuracy: 0.5428
Epoch 28/100
3/3 [==============================] - 0s 22ms/step - loss: 3.3630 - accuracy: 0.4803 - val_loss: 3.3406 - val_accuracy: 0.5658
Epoch 29/100
3/3 [==============================] - 0s 24ms/step - loss: 3.3500 - accuracy: 0.4885 - val_loss: 3.3319 - val_accuracy: 0.5822
Epoch 30/100
3/3 [==============================] - 0s 21ms/step - loss: 3.3632 - accuracy: 0.4820 - val_loss: 3.3233 - val_accuracy: 0.5987
Epoch 31/100
3/3 [==============================] - 0s 22ms/step - loss: 3.3348 - accuracy: 0.5066 - val_loss: 3.3148 - val_accuracy: 0.6020
Epoch 32/100
3/3 [==============================] - 0s 20ms/step - loss: 3.3214 - accuracy: 0.5230 - val_loss: 3.3063 - val_accuracy: 0.6053
Epoch 33/100
3/3 [==============================] - 0s 16ms/step - loss: 3.3297 - accuracy: 0.5148 - val_loss: 3.2979 - val_accuracy: 0.6086
Epoch 34/100
3/3 [==============================] - 0s 26ms/step - loss: 3.3208 - accuracy: 0.5295 - val_loss: 3.2896 - val_accuracy: 0.6184
Epoch 35/100
3/3 [==============================] - 0s 20ms/step - loss: 3.3025 - accuracy: 0.5328 - val_loss: 3.2813 - val_accuracy: 0.6316
Epoch 36/100
3/3 [==============================] - 0s 19ms/step - loss: 3.3058 - accuracy: 0.5443 - val_loss: 3.2731 - val_accuracy: 0.6414
Epoch 37/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2947 - accuracy: 0.5508 - val_loss: 3.2650 - val_accuracy: 0.6480
Epoch 38/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2763 - accuracy: 0.5852 - val_loss: 3.2569 - val_accuracy: 0.6579
Epoch 39/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2692 - accuracy: 0.6033 - val_loss: 3.2489 - val_accuracy: 0.6579
Epoch 40/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2552 - accuracy: 0.6016 - val_loss: 3.2410 - val_accuracy: 0.6645
Epoch 41/100
3/3 [==============================] - 0s 21ms/step - loss: 3.2554 - accuracy: 0.5770 - val_loss: 3.2332 - val_accuracy: 0.6711
Epoch 42/100
3/3 [==============================] - 0s 16ms/step - loss: 3.2557 - accuracy: 0.6246 - val_loss: 3.2253 - val_accuracy: 0.6743
Epoch 43/100
3/3 [==============================] - 0s 24ms/step - loss: 3.2419 - accuracy: 0.6082 - val_loss: 3.2176 - val_accuracy: 0.6776
Epoch 44/100
3/3 [==============================] - 0s 26ms/step - loss: 3.2321 - accuracy: 0.6279 - val_loss: 3.2099 - val_accuracy: 0.6842
Epoch 45/100
3/3 [==============================] - 0s 19ms/step - loss: 3.2333 - accuracy: 0.6164 - val_loss: 3.2023 - val_accuracy: 0.6908
Epoch 46/100
3/3 [==============================] - 0s 17ms/step - loss: 3.2150 - accuracy: 0.6426 - val_loss: 3.1947 - val_accuracy: 0.6941
Epoch 47/100
3/3 [==============================] - 0s 25ms/step - loss: 3.2112 - accuracy: 0.6164 - val_loss: 3.1872 - val_accuracy: 0.7039
Epoch 48/100
3/3 [==============================] - 0s 23ms/step - loss: 3.2051 - accuracy: 0.6459 - val_loss: 3.1797 - val_accuracy: 0.7039
Epoch 49/100
3/3 [==============================] - 0s 20ms/step - loss: 3.2097 - accuracy: 0.6426 - val_loss: 3.1723 - val_accuracy: 0.7105
Epoch 50/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1942 - accuracy: 0.6557 - val_loss: 3.1650 - val_accuracy: 0.7171
Epoch 51/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1803 - accuracy: 0.6803 - val_loss: 3.1576 - val_accuracy: 0.7270
Epoch 52/100
3/3 [==============================] - 0s 34ms/step - loss: 3.1692 - accuracy: 0.6590 - val_loss: 3.1504 - val_accuracy: 0.7368
Epoch 53/100
3/3 [==============================] - 0s 29ms/step - loss: 3.1666 - accuracy: 0.6557 - val_loss: 3.1432 - val_accuracy: 0.7467
Epoch 54/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1644 - accuracy: 0.6820 - val_loss: 3.1360 - val_accuracy: 0.7500
Epoch 55/100
3/3 [==============================] - 0s 34ms/step - loss: 3.1591 - accuracy: 0.6721 - val_loss: 3.1289 - val_accuracy: 0.7533
Epoch 56/100
3/3 [==============================] - 0s 27ms/step - loss: 3.1350 - accuracy: 0.6984 - val_loss: 3.1219 - val_accuracy: 0.7533
Epoch 57/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1309 - accuracy: 0.7016 - val_loss: 3.1149 - val_accuracy: 0.7533
Epoch 58/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1227 - accuracy: 0.7148 - val_loss: 3.1080 - val_accuracy: 0.7566
Epoch 59/100
3/3 [==============================] - 0s 24ms/step - loss: 3.1287 - accuracy: 0.7066 - val_loss: 3.1012 - val_accuracy: 0.7599
Epoch 60/100
3/3 [==============================] - 0s 22ms/step - loss: 3.1174 - accuracy: 0.7000 - val_loss: 3.0944 - val_accuracy: 0.7697
Epoch 61/100
3/3 [==============================] - 0s 25ms/step - loss: 3.1214 - accuracy: 0.7230 - val_loss: 3.0877 - val_accuracy: 0.7697
Epoch 62/100
3/3 [==============================] - 0s 23ms/step - loss: 3.1182 - accuracy: 0.7131 - val_loss: 3.0811 - val_accuracy: 0.7697
Epoch 63/100
3/3 [==============================] - 0s 34ms/step - loss: 3.0966 - accuracy: 0.7410 - val_loss: 3.0745 - val_accuracy: 0.7697
Epoch 64/100
3/3 [==============================] - 0s 26ms/step - loss: 3.0959 - accuracy: 0.7311 - val_loss: 3.0679 - val_accuracy: 0.7697
Epoch 65/100
3/3 [==============================] - 0s 22ms/step - loss: 3.0812 - accuracy: 0.7295 - val_loss: 3.0613 - val_accuracy: 0.7697
Epoch 66/100
3/3 [==============================] - 0s 29ms/step - loss: 3.0729 - accuracy: 0.7393 - val_loss: 3.0548 - val_accuracy: 0.7697
Epoch 67/100
3/3 [==============================] - 0s 26ms/step - loss: 3.0617 - accuracy: 0.7672 - val_loss: 3.0484 - val_accuracy: 0.7796
Epoch 68/100
3/3 [==============================] - 0s 29ms/step - loss: 3.0594 - accuracy: 0.7393 - val_loss: 3.0420 - val_accuracy: 0.7796
Epoch 69/100
3/3 [==============================] - 0s 30ms/step - loss: 3.0702 - accuracy: 0.7344 - val_loss: 3.0356 - val_accuracy: 0.7829
Epoch 70/100
3/3 [==============================] - 0s 18ms/step - loss: 3.0510 - accuracy: 0.7328 - val_loss: 3.0292 - val_accuracy: 0.7862
Epoch 71/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0392 - accuracy: 0.7705 - val_loss: 3.0229 - val_accuracy: 0.7928
Epoch 72/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0423 - accuracy: 0.7443 - val_loss: 3.0167 - val_accuracy: 0.8059
Epoch 73/100
3/3 [==============================] - 0s 24ms/step - loss: 3.0368 - accuracy: 0.7410 - val_loss: 3.0106 - val_accuracy: 0.8059
Epoch 74/100
3/3 [==============================] - 0s 25ms/step - loss: 3.0169 - accuracy: 0.7738 - val_loss: 3.0045 - val_accuracy: 0.8059
Epoch 75/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0337 - accuracy: 0.7525 - val_loss: 2.9984 - val_accuracy: 0.8059
Epoch 76/100
3/3 [==============================] - 0s 21ms/step - loss: 3.0216 - accuracy: 0.7672 - val_loss: 2.9923 - val_accuracy: 0.8059
Epoch 77/100
3/3 [==============================] - 0s 23ms/step - loss: 3.0121 - accuracy: 0.7623 - val_loss: 2.9863 - val_accuracy: 0.8092
Epoch 78/100
3/3 [==============================] - 0s 27ms/step - loss: 3.0054 - accuracy: 0.7803 - val_loss: 2.9804 - val_accuracy: 0.8092
Epoch 79/100
3/3 [==============================] - 0s 26ms/step - loss: 2.9977 - accuracy: 0.7738 - val_loss: 2.9744 - val_accuracy: 0.8092
Epoch 80/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9922 - accuracy: 0.7705 - val_loss: 2.9686 - val_accuracy: 0.8092
Epoch 81/100
3/3 [==============================] - 0s 26ms/step - loss: 2.9840 - accuracy: 0.7869 - val_loss: 2.9628 - val_accuracy: 0.8125
Epoch 82/100
3/3 [==============================] - 0s 23ms/step - loss: 2.9804 - accuracy: 0.7820 - val_loss: 2.9570 - val_accuracy: 0.8125
Epoch 83/100
3/3 [==============================] - 0s 23ms/step - loss: 2.9723 - accuracy: 0.7787 - val_loss: 2.9513 - val_accuracy: 0.8125
Epoch 84/100
3/3 [==============================] - 0s 22ms/step - loss: 2.9702 - accuracy: 0.7918 - val_loss: 2.9456 - val_accuracy: 0.8125
Epoch 85/100
3/3 [==============================] - 0s 22ms/step - loss: 2.9592 - accuracy: 0.7934 - val_loss: 2.9399 - val_accuracy: 0.8125
Epoch 86/100
3/3 [==============================] - 0s 20ms/step - loss: 2.9631 - accuracy: 0.7918 - val_loss: 2.9343 - val_accuracy: 0.8158
Epoch 87/100
3/3 [==============================] - 0s 17ms/step - loss: 2.9522 - accuracy: 0.7820 - val_loss: 2.9287 - val_accuracy: 0.8158
Epoch 88/100
3/3 [==============================] - 0s 17ms/step - loss: 2.9486 - accuracy: 0.8033 - val_loss: 2.9231 - val_accuracy: 0.8158
Epoch 89/100
3/3 [==============================] - 0s 25ms/step - loss: 2.9386 - accuracy: 0.8049 - val_loss: 2.9176 - val_accuracy: 0.8158
Epoch 90/100
3/3 [==============================] - 0s 26ms/step - loss: 2.9342 - accuracy: 0.8016 - val_loss: 2.9121 - val_accuracy: 0.8224
Epoch 91/100
3/3 [==============================] - 0s 23ms/step - loss: 2.9271 - accuracy: 0.8049 - val_loss: 2.9066 - val_accuracy: 0.8257
Epoch 92/100
3/3 [==============================] - 0s 24ms/step - loss: 2.9282 - accuracy: 0.8049 - val_loss: 2.9012 - val_accuracy: 0.8257
Epoch 93/100
3/3 [==============================] - 0s 22ms/step - loss: 2.9272 - accuracy: 0.7902 - val_loss: 2.8958 - val_accuracy: 0.8289
Epoch 94/100
3/3 [==============================] - 0s 19ms/step - loss: 2.9047 - accuracy: 0.7951 - val_loss: 2.8905 - val_accuracy: 0.8322
Epoch 95/100
3/3 [==============================] - 0s 24ms/step - loss: 2.9020 - accuracy: 0.8082 - val_loss: 2.8851 - val_accuracy: 0.8322
Epoch 96/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8999 - accuracy: 0.7951 - val_loss: 2.8799 - val_accuracy: 0.8322
Epoch 97/100
3/3 [==============================] - 0s 26ms/step - loss: 2.8839 - accuracy: 0.8180 - val_loss: 2.8746 - val_accuracy: 0.8322
Epoch 98/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8892 - accuracy: 0.7934 - val_loss: 2.8694 - val_accuracy: 0.8322
Epoch 99/100
3/3 [==============================] - 0s 24ms/step - loss: 2.8768 - accuracy: 0.8197 - val_loss: 2.8643 - val_accuracy: 0.8355
Epoch 100/100
3/3 [==============================] - 0s 25ms/step - loss: 2.8925 - accuracy: 0.8049 - val_loss: 2.8591 - val_accuracy: 0.8355
No description has been provided for this image
No description has been provided for this image 
10/10 [==============================] - 0s 1ms/step
Best score: 0.8708836640782284
Best parameters: {'learning_rate': 0.01, 'hidden_layers': 2, 'hidden_units': 32, 'batch_size': 512, 'learning_rate_decay': 0.001, 'optimizer': 'Adam', 'l1': 0.001, 'l2': 0.001, 'dropout_rate': 0.2, 'adam_beta_1': 0.9, 'adam_beta_2': 0.999, 'batch_norm': False, 'initializers': 'random_normal'}
Best model is in 10 experiment

Experiment 4 Result Analysis¶

Including early stopping in the training process and finally saw an improvement in results.

  • Early Stopping

    By incorporating early stopping, the training process was halted before the model could overfit to the training data, thereby improving its generalization to unseen data. Additionally, early stopping helped in identifying the optimal number of epochs to train, which is when the model achieves the best performance on the validation dataset.

Finalize the Model¶

Now that training process has been outlined that includes a mechanism to prevent overfitting and to stop at the peak of the model's performance, it is time to finalize the model. Here are the next steps:

Finalize Hyperparameters: The last set of hyperparameters are associated with the best validation performance during tuning.

Re-train Model: Use these hyperparameters to re-train the model on the full training dataset.

Performance Evaluation: After re-training, evaluate the model on the held-out test set to confirm that the improvements hold on completely unseen data.

In [73]:
best_model_params = {k:v for k, v in best_params.items() if k != 'batch_size'}
best_model = create_model(**best_model_params)
history = best_model.fit(
    X_train, y_train, 
    epochs=100, 
    batch_size=best_params['batch_size'],
    verbose=2,
    validation_data=(X_val, y_val)
)
plot_loss(history)
plot_accuracy(history)
y_test_pred = best_model.predict(X_test)
y_pred_class = np.argmax(y_test_pred, axis=1)
y_true_classes = np.argmax(y_test, axis=1)

test_accuracy = accuracy_score(y_true_classes, y_pred_class)
print(test_accuracy)

Epoch 1/100
2/2 - 1s - loss: 1.0964 - accuracy: 0.6083 - val_loss: 0.9402 - val_accuracy: 0.8618 - 967ms/epoch - 484ms/step
Epoch 2/100
2/2 - 0s - loss: 0.9211 - accuracy: 0.8490 - val_loss: 0.7854 - val_accuracy: 0.8618 - 44ms/epoch - 22ms/step
Epoch 3/100
2/2 - 0s - loss: 0.7731 - accuracy: 0.8501 - val_loss: 0.6670 - val_accuracy: 0.8618 - 42ms/epoch - 21ms/step
Epoch 4/100
2/2 - 0s - loss: 0.6733 - accuracy: 0.8501 - val_loss: 0.5810 - val_accuracy: 0.8618 - 46ms/epoch - 23ms/step
Epoch 5/100
2/2 - 0s - loss: 0.5971 - accuracy: 0.8501 - val_loss: 0.5259 - val_accuracy: 0.8618 - 41ms/epoch - 20ms/step
Epoch 6/100
2/2 - 0s - loss: 0.5539 - accuracy: 0.8501 - val_loss: 0.4955 - val_accuracy: 0.8618 - 42ms/epoch - 21ms/step
Epoch 7/100
2/2 - 0s - loss: 0.5184 - accuracy: 0.8501 - val_loss: 0.4803 - val_accuracy: 0.8618 - 46ms/epoch - 23ms/step
Epoch 8/100
2/2 - 0s - loss: 0.4970 - accuracy: 0.8501 - val_loss: 0.4719 - val_accuracy: 0.8618 - 41ms/epoch - 21ms/step
Epoch 9/100
2/2 - 0s - loss: 0.4875 - accuracy: 0.8501 - val_loss: 0.4657 - val_accuracy: 0.8618 - 44ms/epoch - 22ms/step
Epoch 10/100
2/2 - 0s - loss: 0.4797 - accuracy: 0.8501 - val_loss: 0.4602 - val_accuracy: 0.8651 - 43ms/epoch - 22ms/step
Epoch 11/100
2/2 - 0s - loss: 0.4551 - accuracy: 0.8556 - val_loss: 0.4557 - val_accuracy: 0.8750 - 48ms/epoch - 24ms/step
Epoch 12/100
2/2 - 0s - loss: 0.4375 - accuracy: 0.8676 - val_loss: 0.4527 - val_accuracy: 0.8717 - 42ms/epoch - 21ms/step
Epoch 13/100
2/2 - 0s - loss: 0.4357 - accuracy: 0.8709 - val_loss: 0.4509 - val_accuracy: 0.8586 - 45ms/epoch - 22ms/step
Epoch 14/100
2/2 - 0s - loss: 0.4275 - accuracy: 0.8665 - val_loss: 0.4495 - val_accuracy: 0.8487 - 41ms/epoch - 20ms/step
Epoch 15/100
2/2 - 0s - loss: 0.4264 - accuracy: 0.8512 - val_loss: 0.4462 - val_accuracy: 0.8388 - 47ms/epoch - 23ms/step
Epoch 16/100
2/2 - 0s - loss: 0.4168 - accuracy: 0.8589 - val_loss: 0.4412 - val_accuracy: 0.8421 - 42ms/epoch - 21ms/step
Epoch 17/100
2/2 - 0s - loss: 0.4158 - accuracy: 0.8742 - val_loss: 0.4327 - val_accuracy: 0.8553 - 41ms/epoch - 20ms/step
Epoch 18/100
2/2 - 0s - loss: 0.4052 - accuracy: 0.8731 - val_loss: 0.4242 - val_accuracy: 0.8618 - 49ms/epoch - 25ms/step
Epoch 19/100
2/2 - 0s - loss: 0.3975 - accuracy: 0.8807 - val_loss: 0.4166 - val_accuracy: 0.8618 - 42ms/epoch - 21ms/step
Epoch 20/100
2/2 - 0s - loss: 0.3918 - accuracy: 0.8589 - val_loss: 0.4103 - val_accuracy: 0.8618 - 44ms/epoch - 22ms/step
Epoch 21/100
2/2 - 0s - loss: 0.3992 - accuracy: 0.8611 - val_loss: 0.4048 - val_accuracy: 0.8618 - 42ms/epoch - 21ms/step
Epoch 22/100
2/2 - 0s - loss: 0.3815 - accuracy: 0.8731 - val_loss: 0.4002 - val_accuracy: 0.8586 - 43ms/epoch - 22ms/step
Epoch 23/100
2/2 - 0s - loss: 0.3825 - accuracy: 0.8698 - val_loss: 0.3966 - val_accuracy: 0.8684 - 41ms/epoch - 20ms/step
Epoch 24/100
2/2 - 0s - loss: 0.3708 - accuracy: 0.8753 - val_loss: 0.3934 - val_accuracy: 0.8651 - 42ms/epoch - 21ms/step
Epoch 25/100
2/2 - 0s - loss: 0.3753 - accuracy: 0.8687 - val_loss: 0.3908 - val_accuracy: 0.8586 - 36ms/epoch - 18ms/step
Epoch 26/100
2/2 - 0s - loss: 0.3677 - accuracy: 0.8720 - val_loss: 0.3883 - val_accuracy: 0.8618 - 38ms/epoch - 19ms/step
Epoch 27/100
2/2 - 0s - loss: 0.3638 - accuracy: 0.8676 - val_loss: 0.3849 - val_accuracy: 0.8586 - 46ms/epoch - 23ms/step
Epoch 28/100
2/2 - 0s - loss: 0.3637 - accuracy: 0.8753 - val_loss: 0.3824 - val_accuracy: 0.8618 - 90ms/epoch - 45ms/step
Epoch 29/100
2/2 - 0s - loss: 0.3561 - accuracy: 0.8753 - val_loss: 0.3800 - val_accuracy: 0.8618 - 45ms/epoch - 22ms/step
Epoch 30/100
2/2 - 0s - loss: 0.3560 - accuracy: 0.8807 - val_loss: 0.3778 - val_accuracy: 0.8651 - 41ms/epoch - 20ms/step
Epoch 31/100
2/2 - 0s - loss: 0.3552 - accuracy: 0.8764 - val_loss: 0.3758 - val_accuracy: 0.8651 - 49ms/epoch - 24ms/step
Epoch 32/100
2/2 - 0s - loss: 0.3527 - accuracy: 0.8589 - val_loss: 0.3739 - val_accuracy: 0.8651 - 52ms/epoch - 26ms/step
Epoch 33/100
2/2 - 0s - loss: 0.3512 - accuracy: 0.8731 - val_loss: 0.3728 - val_accuracy: 0.8651 - 48ms/epoch - 24ms/step
Epoch 34/100
2/2 - 0s - loss: 0.3555 - accuracy: 0.8709 - val_loss: 0.3712 - val_accuracy: 0.8651 - 54ms/epoch - 27ms/step
Epoch 35/100
2/2 - 0s - loss: 0.3421 - accuracy: 0.8687 - val_loss: 0.3697 - val_accuracy: 0.8651 - 48ms/epoch - 24ms/step
Epoch 36/100
2/2 - 0s - loss: 0.3397 - accuracy: 0.8818 - val_loss: 0.3683 - val_accuracy: 0.8651 - 50ms/epoch - 25ms/step
Epoch 37/100
2/2 - 0s - loss: 0.3443 - accuracy: 0.8775 - val_loss: 0.3675 - val_accuracy: 0.8651 - 50ms/epoch - 25ms/step
Epoch 38/100
2/2 - 0s - loss: 0.3446 - accuracy: 0.8775 - val_loss: 0.3660 - val_accuracy: 0.8684 - 53ms/epoch - 27ms/step
Epoch 39/100
2/2 - 0s - loss: 0.3362 - accuracy: 0.8796 - val_loss: 0.3656 - val_accuracy: 0.8651 - 48ms/epoch - 24ms/step
Epoch 40/100
2/2 - 0s - loss: 0.3438 - accuracy: 0.8775 - val_loss: 0.3648 - val_accuracy: 0.8717 - 45ms/epoch - 22ms/step
Epoch 41/100
2/2 - 0s - loss: 0.3366 - accuracy: 0.8818 - val_loss: 0.3632 - val_accuracy: 0.8717 - 58ms/epoch - 29ms/step
Epoch 42/100
2/2 - 0s - loss: 0.3325 - accuracy: 0.8742 - val_loss: 0.3615 - val_accuracy: 0.8717 - 45ms/epoch - 22ms/step
Epoch 43/100
2/2 - 0s - loss: 0.3270 - accuracy: 0.8829 - val_loss: 0.3597 - val_accuracy: 0.8717 - 46ms/epoch - 23ms/step
Epoch 44/100
2/2 - 0s - loss: 0.3336 - accuracy: 0.8764 - val_loss: 0.3582 - val_accuracy: 0.8717 - 52ms/epoch - 26ms/step
Epoch 45/100
2/2 - 0s - loss: 0.3254 - accuracy: 0.8786 - val_loss: 0.3562 - val_accuracy: 0.8717 - 39ms/epoch - 20ms/step
Epoch 46/100
2/2 - 0s - loss: 0.3333 - accuracy: 0.8807 - val_loss: 0.3545 - val_accuracy: 0.8717 - 46ms/epoch - 23ms/step
Epoch 47/100
2/2 - 0s - loss: 0.3325 - accuracy: 0.8742 - val_loss: 0.3539 - val_accuracy: 0.8717 - 43ms/epoch - 22ms/step
Epoch 48/100
2/2 - 0s - loss: 0.3198 - accuracy: 0.8753 - val_loss: 0.3541 - val_accuracy: 0.8717 - 44ms/epoch - 22ms/step
Epoch 49/100
2/2 - 0s - loss: 0.3295 - accuracy: 0.8786 - val_loss: 0.3540 - val_accuracy: 0.8717 - 41ms/epoch - 21ms/step
Epoch 50/100
2/2 - 0s - loss: 0.3284 - accuracy: 0.8796 - val_loss: 0.3553 - val_accuracy: 0.8651 - 42ms/epoch - 21ms/step
Epoch 51/100
2/2 - 0s - loss: 0.3216 - accuracy: 0.8840 - val_loss: 0.3541 - val_accuracy: 0.8717 - 38ms/epoch - 19ms/step
Epoch 52/100
2/2 - 0s - loss: 0.3219 - accuracy: 0.8775 - val_loss: 0.3528 - val_accuracy: 0.8717 - 43ms/epoch - 22ms/step
Epoch 53/100
2/2 - 0s - loss: 0.3240 - accuracy: 0.8796 - val_loss: 0.3517 - val_accuracy: 0.8750 - 43ms/epoch - 21ms/step
Epoch 54/100
2/2 - 0s - loss: 0.3247 - accuracy: 0.8753 - val_loss: 0.3491 - val_accuracy: 0.8750 - 43ms/epoch - 22ms/step
Epoch 55/100
2/2 - 0s - loss: 0.3171 - accuracy: 0.8796 - val_loss: 0.3479 - val_accuracy: 0.8750 - 42ms/epoch - 21ms/step
Epoch 56/100
2/2 - 0s - loss: 0.3242 - accuracy: 0.8764 - val_loss: 0.3485 - val_accuracy: 0.8783 - 39ms/epoch - 19ms/step
Epoch 57/100
2/2 - 0s - loss: 0.3160 - accuracy: 0.8840 - val_loss: 0.3501 - val_accuracy: 0.8717 - 44ms/epoch - 22ms/step
Epoch 58/100
2/2 - 0s - loss: 0.3220 - accuracy: 0.8829 - val_loss: 0.3492 - val_accuracy: 0.8651 - 42ms/epoch - 21ms/step
Epoch 59/100
2/2 - 0s - loss: 0.3175 - accuracy: 0.8807 - val_loss: 0.3482 - val_accuracy: 0.8717 - 36ms/epoch - 18ms/step
Epoch 60/100
2/2 - 0s - loss: 0.3214 - accuracy: 0.8720 - val_loss: 0.3473 - val_accuracy: 0.8783 - 50ms/epoch - 25ms/step
Epoch 61/100
2/2 - 0s - loss: 0.3137 - accuracy: 0.8851 - val_loss: 0.3470 - val_accuracy: 0.8816 - 42ms/epoch - 21ms/step
Epoch 62/100
2/2 - 0s - loss: 0.3179 - accuracy: 0.8731 - val_loss: 0.3473 - val_accuracy: 0.8750 - 39ms/epoch - 20ms/step
Epoch 63/100
2/2 - 0s - loss: 0.3160 - accuracy: 0.8840 - val_loss: 0.3479 - val_accuracy: 0.8717 - 40ms/epoch - 20ms/step
Epoch 64/100
2/2 - 0s - loss: 0.3221 - accuracy: 0.8807 - val_loss: 0.3476 - val_accuracy: 0.8651 - 37ms/epoch - 19ms/step
Epoch 65/100
2/2 - 0s - loss: 0.3134 - accuracy: 0.8862 - val_loss: 0.3467 - val_accuracy: 0.8684 - 39ms/epoch - 20ms/step
Epoch 66/100
2/2 - 0s - loss: 0.3143 - accuracy: 0.8818 - val_loss: 0.3452 - val_accuracy: 0.8684 - 40ms/epoch - 20ms/step
Epoch 67/100
2/2 - 0s - loss: 0.3142 - accuracy: 0.8873 - val_loss: 0.3427 - val_accuracy: 0.8750 - 44ms/epoch - 22ms/step
Epoch 68/100
2/2 - 0s - loss: 0.3118 - accuracy: 0.8829 - val_loss: 0.3410 - val_accuracy: 0.8783 - 44ms/epoch - 22ms/step
Epoch 69/100
2/2 - 0s - loss: 0.3171 - accuracy: 0.8829 - val_loss: 0.3408 - val_accuracy: 0.8750 - 44ms/epoch - 22ms/step
Epoch 70/100
2/2 - 0s - loss: 0.3164 - accuracy: 0.8775 - val_loss: 0.3404 - val_accuracy: 0.8750 - 42ms/epoch - 21ms/step
Epoch 71/100
2/2 - 0s - loss: 0.3084 - accuracy: 0.8796 - val_loss: 0.3397 - val_accuracy: 0.8750 - 41ms/epoch - 21ms/step
Epoch 72/100
2/2 - 0s - loss: 0.3123 - accuracy: 0.8840 - val_loss: 0.3398 - val_accuracy: 0.8750 - 44ms/epoch - 22ms/step
Epoch 73/100
2/2 - 0s - loss: 0.3164 - accuracy: 0.8764 - val_loss: 0.3401 - val_accuracy: 0.8717 - 40ms/epoch - 20ms/step
Epoch 74/100
2/2 - 0s - loss: 0.3092 - accuracy: 0.8873 - val_loss: 0.3396 - val_accuracy: 0.8684 - 41ms/epoch - 20ms/step
Epoch 75/100
2/2 - 0s - loss: 0.3146 - accuracy: 0.8829 - val_loss: 0.3388 - val_accuracy: 0.8684 - 43ms/epoch - 21ms/step
Epoch 76/100
2/2 - 0s - loss: 0.3047 - accuracy: 0.8840 - val_loss: 0.3366 - val_accuracy: 0.8783 - 42ms/epoch - 21ms/step
Epoch 77/100
2/2 - 0s - loss: 0.3135 - accuracy: 0.8796 - val_loss: 0.3354 - val_accuracy: 0.8783 - 42ms/epoch - 21ms/step
Epoch 78/100
2/2 - 0s - loss: 0.3149 - accuracy: 0.8775 - val_loss: 0.3356 - val_accuracy: 0.8783 - 43ms/epoch - 22ms/step
Epoch 79/100
2/2 - 0s - loss: 0.3108 - accuracy: 0.8807 - val_loss: 0.3359 - val_accuracy: 0.8651 - 36ms/epoch - 18ms/step
Epoch 80/100
2/2 - 0s - loss: 0.3061 - accuracy: 0.8807 - val_loss: 0.3363 - val_accuracy: 0.8618 - 43ms/epoch - 21ms/step
Epoch 81/100
2/2 - 0s - loss: 0.3137 - accuracy: 0.8884 - val_loss: 0.3334 - val_accuracy: 0.8750 - 41ms/epoch - 21ms/step
Epoch 82/100
2/2 - 0s - loss: 0.3103 - accuracy: 0.8786 - val_loss: 0.3325 - val_accuracy: 0.8750 - 41ms/epoch - 21ms/step
Epoch 83/100
2/2 - 0s - loss: 0.3076 - accuracy: 0.8873 - val_loss: 0.3325 - val_accuracy: 0.8750 - 46ms/epoch - 23ms/step
Epoch 84/100
2/2 - 0s - loss: 0.3051 - accuracy: 0.8851 - val_loss: 0.3348 - val_accuracy: 0.8717 - 44ms/epoch - 22ms/step
Epoch 85/100
2/2 - 0s - loss: 0.3120 - accuracy: 0.8818 - val_loss: 0.3368 - val_accuracy: 0.8586 - 46ms/epoch - 23ms/step
Epoch 86/100
2/2 - 0s - loss: 0.3075 - accuracy: 0.8818 - val_loss: 0.3362 - val_accuracy: 0.8618 - 43ms/epoch - 21ms/step
Epoch 87/100
2/2 - 0s - loss: 0.3086 - accuracy: 0.8775 - val_loss: 0.3358 - val_accuracy: 0.8618 - 46ms/epoch - 23ms/step
Epoch 88/100
2/2 - 0s - loss: 0.3098 - accuracy: 0.8807 - val_loss: 0.3331 - val_accuracy: 0.8750 - 41ms/epoch - 20ms/step
Epoch 89/100
2/2 - 0s - loss: 0.3074 - accuracy: 0.8851 - val_loss: 0.3321 - val_accuracy: 0.8750 - 46ms/epoch - 23ms/step
Epoch 90/100
2/2 - 0s - loss: 0.3089 - accuracy: 0.8829 - val_loss: 0.3325 - val_accuracy: 0.8750 - 39ms/epoch - 19ms/step
Epoch 91/100
2/2 - 0s - loss: 0.3053 - accuracy: 0.8884 - val_loss: 0.3341 - val_accuracy: 0.8651 - 43ms/epoch - 22ms/step
Epoch 92/100
2/2 - 0s - loss: 0.3036 - accuracy: 0.8840 - val_loss: 0.3351 - val_accuracy: 0.8586 - 42ms/epoch - 21ms/step
Epoch 93/100
2/2 - 0s - loss: 0.3043 - accuracy: 0.8873 - val_loss: 0.3335 - val_accuracy: 0.8651 - 40ms/epoch - 20ms/step
Epoch 94/100
2/2 - 0s - loss: 0.3095 - accuracy: 0.8786 - val_loss: 0.3306 - val_accuracy: 0.8783 - 42ms/epoch - 21ms/step
Epoch 95/100
2/2 - 0s - loss: 0.2998 - accuracy: 0.8840 - val_loss: 0.3308 - val_accuracy: 0.8750 - 39ms/epoch - 19ms/step
Epoch 96/100
2/2 - 0s - loss: 0.3026 - accuracy: 0.8862 - val_loss: 0.3317 - val_accuracy: 0.8717 - 41ms/epoch - 21ms/step
Epoch 97/100
2/2 - 0s - loss: 0.3041 - accuracy: 0.8851 - val_loss: 0.3320 - val_accuracy: 0.8684 - 42ms/epoch - 21ms/step
Epoch 98/100
2/2 - 0s - loss: 0.3073 - accuracy: 0.8796 - val_loss: 0.3312 - val_accuracy: 0.8684 - 47ms/epoch - 24ms/step
Epoch 99/100
2/2 - 0s - loss: 0.3032 - accuracy: 0.8851 - val_loss: 0.3295 - val_accuracy: 0.8684 - 45ms/epoch - 23ms/step
Epoch 100/100
2/2 - 0s - loss: 0.3002 - accuracy: 0.8840 - val_loss: 0.3277 - val_accuracy: 0.8750 - 40ms/epoch - 20ms/step
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8/8 [==============================] - 0s 2ms/step
0.8820960698689956

Limitation and Discussion¶

This investigation represents a comprehensive examination of hyperparameter optimization, encompassing an extensive range of tunable parameters. It has facilitated a more profound comprehension of the roles hyperparameters play within the training process. The exploration began with a critical assessment of the parameter space, marking the first occasion where serious consideration was given to the impact of varying ranges. Employing both hold-out and K-fold cross-validation concurrently offered valuable insights into their operational mechanics and their advantages, particularly for smaller datasets.

Nonetheless, limitation is obviousints. The peak accuracy attained by the optimal model configuration is approximately 88.2%, which, while substantial, is ideal enoughlary. The potential reasons for this are multifaceted:

  • Dataset Size: In an effort to expedite the training cycle and conserve computational resources, a smaller dataset was deliberately chosen. This decision likely impeded the model's capacity for further refinement and evolution.
  • Impact of Data Volume: The modest scale of the dataset may have also restricted the full potential of the experimental procedures.

Future Directions: The progression of this research has culminated in the establishment of a solid foundational model. Prospective explorations could encompass:

  • Further Hyperparameter Tuning: Additional adjustments and tuning of hyperparameters may yield further improvements.
  • Ensemble Techniques: Integrating multiple models might enhance overall performance.
  • Feature Engineering: The development or enhancement of features could significantly bolster the model's ability to discern more complex data patterns.

In conclusion, this investigation stands as a successful conceptual proof of hyperparameter optimization's efficacy.